J. P Morgan - Flat market_ fat tails

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					                                                                                                                               Asia Pacific Equity Research
                                                                                                                               31 May 2013




Flat market, fat tails
Chinese equities when policy is constrained


 Investors are disappointed. H-shares are down YTD. Despite a                                                                 Asian Equity Strategy & Emerging
  significant increase in total social financing, economic momentum is                                                         Market Equity Strategy
  disappointing. Policy makers are responding to the side effect of easy                                                       Adrian Mowat
                                                                                                                                                      AC

  credit (inflation of the property bubble). The central bank is concerned                                                     (852) 2800-8599
  that the combination of a tight labor market and rising rents are driving                                                    adrian.mowat@jpmorgan.com

  urban core inflation. Fiscal flexibility is limited, with a deficit of                                                       Joanne Cheung
  2%/GDP. Local-government-guaranteed-debt is reported to be                                                                   (852) 2800-8596
                                                                                                                               joanne.cy.cheung@jpmorgan.com
  RMB20trillion (40%/GDP) (source: Bloomberg). Premier Li Keqiang
  noted that “China is confronted by huge challenges”. The reports we                                                          Equity Derivatives Strategy
                                                                                                                                                    AC
  have published on these challenges are: China 20:20: 130 million swing:                                                      Tony SK Lee
  How demographics change the economy (May 2011, see page 27) on                                                               (852) 2800-8857
                                                                                                                               tony.sk.lee@jpmorgan.com
  labor shortage, EM equities as China slows: Managing the downside
  risk if China continues to slow (February 2012, see page 53) and China                                                       Quantitative Strategy
  challenged: Lessons from other Asian bubbles (June 2012, see page 83).                                                       Robert Smith
                                                                                                                                                      AC

                                                                                                                               (852) 2800 8569
 Our base case is policy limbo: Growth slows gradually and the market is                                                      robert.z.smith@jpmorgan.com
  range bound (see page 14). The tails to this view are: (1) 2H12                                                              Director of Asia Pacific Equity
  monetary stimulus is successful, just with an extended lag, in                                                               Research & Asia Technical
  stabilizing economic activity - positive for Chinese equities and deep                                                       Strategy
  cyclicals; (2) the PBoC, conscious of the core inflation drivers of a tight                                                  Sunil Garg
                                                                                                                                                 AC

  labor market and rising property prices, tightens policy while growth                                                        (852) 2800-8518
  momentum is weak - bearish for Chinese equities and deep cyclicals.                                                          sunil.garg@jpmorgan.com
  Our view is closer to the latter, near consensus. The current limbo period                                                   J.P. Morgan Securities (Asia Pacific) Limited
  results in an alpha-rich but beta-poor market (note the dispersion of
  returns on page 10). The dispersion of stock returns is high (pages 5 to
  11). Note that Quant helped with relative EPS revisions driving                                                                     Please see page 13 for key
  dispersion (page 11). Policy matters, but at the sector level.                                                                         questions on China.

Figure 1: China needs jobs for graduates, not in pouring concrete or                   Figure 2: China total social financing to GDP
manufacturing: Change in the non-graduate available workforce 15-
39 year olds                                                                            190%
                                                                                                              Deposits        Loans        TSF
%oya, Millions
                                                                                        170%
   3%                                                                            600
   2%                                        %oya            Number
                                                                                 500    150%
   1%
   0%                                                                            400
  -1%                                                                                   130%
                                                                                 300
  -2%
  -3%                                                                            200
                                                                                        110%
  -4%
                                                                                 100
  -5%
  -6%                                                                            0       90%
                                                                                                99         01       03        04      06        08        09        11        13
        1990
        1993
        1996
        1999
        2002
        2005
        2008
        2011
        2014
        2017
        2020
        2023
        2026
        2029
        2032
        2035
        2038
        2041
        2044
        2047




                                                                                       Source: CEIC, PBoC, J.P. Morgan calculation. Note: The PBoC does not disclose the stock of
Source: PRC NBS, Ministry of Education PRC, US Census, J.P. Morgan calculation         total social financing (TSF). To calculate TSF we use the actual total loans outstanding each
                                                                                       month and add the cumulative net financing of non-loans. The chart is representative of growth.




See page 98 for analyst certification and important disclosures, including non-US analyst disclosures.
J.P. Morgan does and seeks to do business with companies covered in its research reports. As a result, investors should be aware that the
firm may have a conflict of interest that could affect the objectivity of this report. Investors should consider this report as only a single factor in
making their investment decision. In the United States, this information is available only to persons who have received the proper option risk
disclosure documents. Please contact your J.P. Morgan representative or visit http://www.optionsclearing.com/publications/risks/riskstoc.pdf.

                                                                                                                                      www.jpmorganmarkets.com
Adrian Mowat                                             Asia Pacific Equity Research
(852) 2800-8599                                          31 May 2013
adrian.mowat@jpmorgan.com




Figure 3: China inflation, interest rates and market performance
    150         Premier Zhu tightened the                                                                                                                                                                                              30
                                                                              MSCI China (LHS)             RRR ( RHS)                1y Lending Rate (RHS)              CPI (RHS)
               economy amid overheating
                      concerns.

                                                                                                                                                            Market crashed due to sub-
                                                                                                                                                              prime mortgage crisis                                                    25
                                                                   SCRC published the                                                                                                          11 RRR hikes in Jan
    120                                                              rules to sell non-                                      Announcement of the                                               10 -Jun11 (from 15%
                                                                  tradable shares to the                                    DII scheme. Mkt rallied.                                           to 21%)
                                                                      A-share market.                                                                                          Rmb4 trillion
                                                                                                   21 Feb 04: Ministry of Land and                     18 RRR hikes in         stimulative package                                     20
                                                                                                    Resources requests all local                       July06 -June08 (from
                                                                                                      governments to suspend                           7.5% to 17.5%)                                         5 directives
                                                                                                        approvals of villas.                                                                             tightening policy on
     90                                                   8 consecutive interest rate                                                                                                                    property to oontinue
                                                                                             Issued warnings that the   On 27th Feb 2004, CBRC limits                                                                                   15
                                                          cuts in May 96 - Feb 02 (1                                    banks’ outstanding loans to the                                                                   Additional
                                                            year lending rate from           government may step in
                                                                                                 to curb irrational     property sector at 30% of total                                  Rmb900 billion public         property control
                                                              12.06% to 5.31%)                                          loans.                                                                                             policies
                                                                                              investment in Dec-03.                             Enforcement of                           housing plan
                                                                                                                                                         LAT.                                                            announced
                                                                                              State Council limits                 15-point measures;                                                                                   10
     60                                                                                       approvals for new                   5.5% tax on sales for
                                                                                              investment projects in             flat resale witihin 5 yrs
                                                                                              Dec-03.                                  of purchase

        Announced policies to halt                                                                State Council published                                                                                                              5
          IPO, provide funding to                                                                 9 points as guidelines
        securities firms, and attract                                                               to A-share reform
     30
        foreign capital into A-share
                                                                                                       QFII started                                                                        "New 10 measures" to Premier Wen
                                                                                                                                                                                             curb property price reiterarated 0
                         Announced new Securities Law                                                                                           The expansion of                                                   tightening policy
                       which forbade trust companies to run                                                                      A-share reform QDII program.
                          securities houses. Securities                                CSRC promised to                            kicked off              MOF announced to increase the Preferential policies on
                          business faced restructuring.                               "stablize the market" In July-03, PBOC tightened                          stamp duty tax for stock    auto, home appliance
                                                                                                            lendings to the property sector.                transactionsfrom 0.1% to 0.3%.       and property
      0                                                                                                                                                                                                                              -5
          94        95           96          97           98          99           00         01         02       03          04         05       06        07         08         09       10        11         12          13
Source: Bloomberg, J.P. Morgan research.
Note: The peak of each equity market; Japan: Dec1989, Taiwan: Feb1990, China: Oct 2007.




2
Adrian Mowat                                                   Asia Pacific Equity Research
(852) 2800-8599                                                31 May 2013
adrian.mowat@jpmorgan.com




                                                               Stop waiting for policy
Figure 4: A/H price movement over                              This time last year as growth slowed investors looked forward to policy support,
the past year                                                  which arrived in August 2012 as monetary conditions eased. The evidence was the
 130                                                           increase in total social financing. The PBoC reports the change in the stock of TSF.
                   HSCEI Index        SHCOMP Index             Then the year-over-year growth in the change of TSF is often quoted. We prefer the
                                                               stock of TSF divided by nominal GDP. An increase in the ratio indicates a monetary
 120                                                           stimulus (see page 7). There is also a fiscal stimulus. The official fiscal deficit is
                                                               2%/GDP. This does not account for the change in government-guaranteed-liabilities
                                                               (i.e. LGFVs loans, railway bonds, etc).
 110

                                                               Our base case is policy limbo: Growth slows gradually and the market is range
                                                               bound (see page 14). The tails to this view are: (1) 2H12 monetary stimulus is
 100                                                           successful, just with an extended lag, in stabilizing economic activity - positive for
                                                               Chinese equities and deep cyclical; (2) the PBoC, conscious of the core inflation
                                                               drivers of a tight labor market and rising property prices, tightens policy while
  90                                                           growth momentum is weak - bearish for Chinese equities and deep cyclicals. Our
                                                               view is closer to the latter, near consensus. The current limbo period results in an
                                                               alpha rich but beta poor market (note the dispersion of returns on page 10).
  80
   May/12 Jul/12   Sep/12 Nov/12 Jan/13 Mar/13 May/13

Source: Bloomberg.                                             This report reviews EPS downgrades (page 4), the dispersion of stock returns (page
                                                               5), disconnect between high growth in total social financing yet weak growth (page 7)
                                                               and the worrying message on inventories (page 9). Our conclusion is that stock
                                                               analysts rather than strategists will add more value in a policy constrained world.

Figure 5: Intensity of cement use; per-capita consumption of cement (tonnes) vs. adjusted per-capita nominal GDP




Source: US Geological Survey and J.P. Morgan estimates.
Note: The GDP per capita is restated for today’s dollars by adjusting the deflator series.

                                                                                                                                                        3
Adrian Mowat                                                                     Asia Pacific Equity Research
(852) 2800-8599                                                                  31 May 2013
adrian.mowat@jpmorgan.com




The fundamentals were poor…..but not as bad as EM
MSCI China’s forecast EPS integer is 7% lower today                                                                      Table 1: EPS revisions for Chinese industry groups
than 12 months ago. Note the dispersion in EPS                                                                           MSCI China 2013 EPS revisions (%)                      3M              6M              12M
revisions in Table 1. Utilities benefited from lower fuel                                                                Energy                                                -0.6             -3.6           -16.2
costs. Bank credit costs were lower and NIMs higher                                                                      Materials                                             -5.4             -7.7           -31.7
than first feared.                                                                                                       Industrials                                           -4.0             -7.5           -23.2
                                                                                                                         Consumer Discretionary                                -1.2             -3.8           -20.5
                                                                                                                         Consumer Staples                                      -5.1            -10.7           -24.5
Despite the large stimulus, deep cyclical’s EPS forecasts                                                                Healthcare                                            -1.7             -3.4            -5.0
continue to decline. Weak demand was compounded by                                                                       Financials                                             5.1             6.0             -1.9
excessive capacity expansion. This was particularly true                                                                   Banks                                                7.8             10.1            1.8
                                                                                                                           Insurance                                           -0.5             -3.0           -15.0
in steel and building materials.                                                                                           Real Estate                                          3.2             3.1             0.1
                                                                                                                         IT                                                     1.0             1.3             -7.2
The downgrade in retail stocks is notable with a nasty                                                                   Telecommunication Services                             1.6             0.0             -1.5
                                                                                                                         Utilities                                              8.3             11.9            21.4
combination of slowing same store sales growth and less                                                                  MSCI China                                             2.6             2.0             -7.1
store expansion. This was an expensive sector that
                                                                                                                         Source: MSCI, IBES, Datastream
suffered from both EPS downgrades and de-rating.
                                                                                                                         Table 2: MSCI China sector valuation
The downgrade of consumer staples is surprising.
                                                                                                                                                                                EPS growth
Earnings forecasts were revised down the most in the
                                                                                                                                                                       2013E                       2014E
past six months. The drivers of the downgrade were:                                                                      MSCI China                                     10%                          9%
China Foods (FY12 earnings miss and lower FY13                                                                           Consumer Disc.                                 14%                         19%
earnings on close-to-break-even for Kitchen Food                                                                         Cons. Staples                                  11%                         19%
division), China Agri-Ind (challenging environment for                                                                   Energy                                         -3%                          0%
                                                                                                                         Financials                                     11%                         11%
rice may persist), Tingyi (disappointing 1Q13 results,                                                                     Banks                                         7%                         10%
increase in Opex), CRE (retail sales weaker than                                                                           Insurance                                    83%                         16%
expected, slight improvement in beer EBITDA margins)                                                                       Real Estate                                  12%                         14%
and China Mingniu Dairy (FY13 EPS revised down by                                                                        Health Care                                    15%                         18%
                                                                                                                         Industrials                                    24%                         17%
16%).                                                                                                                    IT                                             40%                         12%
                                                                                                                         Materials                                      38%                         17%
Figure 6: MSCI China EPS revision relative to MSCI EM                                                                    Telecom                                         0%                         -4%
    1.15                                                                                                                 Utilities                                      25%                         12%
                                                                                                                         Source: Bloomberg and J.P. Morgan. Updated as of 30th May 2013.
                                                                2013E       2014E
     1.1
                                                                                                                         Figure 7: Slower than hoped .Chinese GDP forecast revisions
                                                                                                                          9.3
                                                                                                                                                                                 2013 E                2014E
    1.05                                                                                                                  9.1

                                                                                                                          8.9
      1
                                                                                                                          8.7

                                                                                                                          8.5
    0.95
       Feb 12 Mar 12 Apr 12 May 12 Jun 12 Jul 12 Aug 12 Sep 12 Oct 12 Nov 12 Dec 12 Jan 13 Feb 13 Mar 13 Apr 13 May 13    8.3

                                                                                                                          8.1
Source: MSCI, IBES, Datastream
                                                                                                                          7.9

Our analysts forecast 10% EPS growth in 2013. This is                                                                     7.7

more bearish than consensus. A lack of supply discipline                                                                  7.5
with weak (note GDP downgrades) demand is likely to                                                                         Jan-12       Apr-12           Jul-12      Oct-12          Jan-13            Apr-13

lead to further downgrades. There is little visibility on                                                                Source: J.P. Morgan economics.
bank NIMs and credit costs.




4
Adrian Mowat                           Asia Pacific Equity Research
(852) 2800-8599                        31 May 2013
adrian.mowat@jpmorgan.com




The devil is in the detail
Consumer: The preference is staples versus                            Figure 8: Consumer staples outperformed discretionary YTD
discretionary. This year our analysts are cautious on                   130
apparel and footwear. Excess inventory, limited pricing                 120
component in SSSG and increasing competition from                       110
international brands are the key headwinds. China                       100
                                                                         90
Mengniu is the top sector pick in staples (+20%YTD
                                                                         80
(MXCN -4.3%YTD). We expect 2-year CAGR EPS                               70
growth at 24% given the focus on high-end products.                      60
Retailers generally underperformed, including Parkson                    50
Retail (-42%YTD) and Golden Eagle (-32%YTD)                               Jan 13           Feb 13        Mar 13           Apr 13         May 13
(MXCN: -4.3%YTD). See ‘China /HK Consumer:
                                                                                        Golden Eagle              China Mengniu              Parkson
Leave P/E aside, focus on intrinsic value’, Ebru et al, 1
                                                                      Source: Datastream. Chart shows share prices relative to MXCN
May 2013, for more on this sector.
                                                                      Figure 9: Macau casinos outperformed significantly YTD
Macau gaming: Macau casinos are in MSCI Hong
                                                                        135
Kong. These companies are a good proxy on Chinese                       130
consumption. We are positive on the sector due to strong                125
mass revenue momentum, customer yield enhancements,                     120
strengthening Chinese consumption and recovering VIP                    115
                                                                        110
trends. The announcement of final/special dividends was                 105
positive. The sector rallied 37% YTD, outperforming the                 100
HSI by 36%. Our top pick in January was Sands China.                     95
Wynn Macau became our preferred play in April, due to                    90
                                                                          Jan 13           Feb 13        Mar 13           Apr 13         May 13
market share gain in VIP and mass segments as well as
margin expansion.                                                                               Sands China                        Wynn Macau
                                                                      Source: Datastream. Chart shows share prices relative to MXCN
Oil: We are bearish on the energy sector. In a relatively
weak demand scenario, refining capacity ex China is                   Figure 10: Oil companies underperformed MSCI China YTD
excessive, while excess Chinese capacity is a further risk              110
if they export more. Sinopec (-6%YTD) has been the                      105
outperformer on refining reversal and undemanding                       100
valuations. Petrochina has dropped 14%YTD due to                          95
natural gas import loss. CNOOC has fallen 17%YTD.                         90
                                                                          85
Telco: Our telco team downgraded China Mobile to UW
                                                                          80
on 13 January. They forecast lower margins due to the                      Jan 13          Feb 13        Mar 13           Apr 13         May 13
low-return data business, accelerated cannibalization of                                         CNOOC              Petrochina            Sinopec
internet OTT and increase in operating expense. They
                                                                      Source: Datastream. Chart shows share prices relative to MXCN
also downgraded China Telecom to Neutral in March due
to significant increase in capex on 4G. We prefer China
                                                                      Figure 11: China Unicom outperformed from recent trough in
Unicom and expect the company to benefit from 3G                      April
penetration. China Unicom is the only telco that can                    115
execute a capex efficient hot spot strategy in 4G network
                                                                        110
build out.
                                                                        105

                                                                        100

                                                                          95

                                                                          90
                                                                          04/15/13          04/25/13         05/05/13         05/15/13        05/25/13

                                                                                          China Unicom                 CMHK               China Tel

                                                                      Source: Datastream. Chart shows share prices relative to MXCN



                                                                                                                                                         5
Adrian Mowat                           Asia Pacific Equity Research
(852) 2800-8599                        31 May 2013
adrian.mowat@jpmorgan.com




The devil is in the detail (continued)
Property: Our property team is positive, due to strong                Figure 12: Ctry Garden, CRLand and Vanke are the outperformers
market momentum, reduction in funding costs and                         150
positive earning revisions (please see ‘China Property                  140
2013 Outlook: Growth potential more relevant when                       130
cash-flow risks are low’, Kwong et al, 17 January 2013).                120
The Chinese property sector is outperforming. Their                     110
preference is developers with stronger contracted sales                 100
and earnings growth. Sector top-picks: Country Garden,                    90
China Resources Land and China Vanke.                                     80
                                                                           Jan 13          Feb 13        Mar 13           Apr 13          May 13

Autos: Our auto team’s preference is passenger vehicle                                  CRLand                China Vanke                Country Garden
(PV) over commercial vehicle (CV). They forecast 10-                  Source: Datastream. Chart shows share prices relative to MXCN
12% growth in PV in 2013, driven by SUV demand.
Their view is that SUV manufacturers will enjoy both                  Figure 13: Passenger vehicle players outperformed significantly
multiple expansion and earnings upgrades (please see                   160
‘China Auto Drivers: Will PV sales ever slow down?’
Nick Lai et al, 24 May 2013, and ‘China's SUV fever -                  140
Part 3: We expect GWM's 1Q earnings to beat and
Geely's 3Q sales to surge’, Nick Lai et al, 19 April 2013.             120
We are OW on Great Wall (+47%YTD) and Geely
(+5%YTD) and UW on Zhongsheng (-16%YTD) and                            100

Dongfeng Motor (0%YTD) (MXCN: -4.3%YTD).
                                                                         80
                                                                          Jan 13           Feb 13        Mar 13           Apr 13          May 13
Infrastructure: The infrastructure team is bullish on                              GreatWall           Dongfeng Motor                 Geely         Zhongsheng
railway civil work contractors. The drivers are                       Source: Datastream. Chart shows share prices relative to MXCN
accelerated railway investment and margin expansion
(efficiency gains plus greater contributions from higher-             Figure 14: Railway stocks outperformed marginally since 1Q13
margin subway constructions). They reiterated their                    110
positive view on CRG, CRCC and CCCC following the
                                                                       105
1Q13 results. They are cautious on Zoomlion (down
30%YTD, MXCN -4.3%) due to industry condition,                         100
deteriorating receivable collectability and destocking                  95
pressure.
                                                                        90

Small caps: Snap, crackle and pop! The SMID cap                         85
sector is alpha rich. Investors are looking for ideas                   80
beyond range-bound large caps. The teams’ OW calls are                  04/01/13      04/11/13      04/21/13     05/01/13     05/11/13        05/21/13
Skyworth and Techtronic (38%YTD and 40%YTD                                              CCCC              CRG               CRCC               Zoomlion
respectively). Material stocks were weak with Kingboard               Source: Datastream. Chart shows share prices relative to MXCN
Chemical and Fufeng down 25%YTD and 12%YTD
respectively (MXCN -4.3%). Please see HK/China                        Figure 15: Small cap consumer plays strongly performed YTD
Small-/Mid-Caps Cross-Sector View: Snap, Crackle and                   180
Pop II, Chik et al, 29 May 2013.                                       160

                                                                       140

                                                                       120

                                                                       100

                                                                         80
                                                                          Jan 13           Feb 13        Mar 13           Apr 13          May 13
                                                                                                  Techtronic                             Skyworth
                                                                      Source: Datastream. Chart shows share prices relative to MXCN


6
Adrian Mowat                                               Asia Pacific Equity Research
(852) 2800-8599                                            31 May 2013
adrian.mowat@jpmorgan.com




Table 3: A mixed picture: Chinese activity data for April
                 Data points                             March 2013                                    April 2013                         Seasonally adjusted          YTD
                                                    Absolute     %oya ,              Absolute           %oya,            %oya                 (% 3M/3M)                %oya
                                                                 3mmva                                 3mmva
Consumption
Passenger vehicle sales (mn units)                     1.6            17.2              1.4              6.3                12.5                                        16.0
Passenger vehicle sales, sa (mn units)                 1.4            14.8              1.4              5.1                                       (3.8)
Retail Sales (Value, billion Yuan)                    1762            12.4             1760             12.6                12.8                                        12.5

Industrial Activity
Commercial Vehicle sales (mn units)                      0.4          (2.1)             0.4             (4.0)               16.2                                        2.5
Commercial Vehicle sales, sa (mn units)                  0.3          (2.9)             0.3             (7.8)                                      (13.5)
Steel production (mn tons)*
                                   NBS, nsa           66.3             10.1                                                                                             10.1
                                    NBS, sa           64.1             10.1
                                      CISA            64.3             12.5            63.7               9.1               4.9                                         10.4
Cement Production, nsa (mn tons)                     187.0              7.4           214.9               6.2               9.3                                          8.0
Cement Production, sa (mn tons)                      195.8              7.6           197.9               5.8                                      10.6
Clinker Production, nsa (mn tons)**                  113.0             (0.3)          125.7               5.4               12.1                                        3.4
Clinker Production, sa (mn tons)**                   112.8             (0.5)          118.4               4.8                                       9.7
Excavator sales volume (units)                       21770            (25.5)          16257             (18.7)              5.8                                        (17.4)
Residential Starts, sa (sqm mn)                       93.6              4.4           116.1               1.6                                       3.8
Residential Sales, sa (sqm mn)                        98.1             45.9            93.3              41.3                                       4.1
Residential Starts, nsa (sqm mn)                     117.5             (0.8)          121.5              (1.7)               8.7                                         1.8
Residential Sales, nsa (sqm mn)                       94.1             41.2            79.3              38.5               41.0                                        41.1
Industrial Production(Billion Yuan,1990)             1103               9.5            1042               9.3                9.3                                         9.4
Total China Power Demand (bn KWH)*                   424.0              4.1                                                                                              4.1
China Heavy Industry Demand (bn KWH)*                269.0              3.5                                                                                              3.5
Total China Power generation (bn KWH)                419.4             (5.6)           399.4            (0.9)               7.4                                         (2.4)

Imports Volume : Commodities and Oil*
Iron Ore (Million, tons)                              64.6             (0.4)           67.2               1.4             16.4                                           3.6
Crude Petroleum Oil (mn tons)                         23.1             (2.3)           23.1              (3.7)             3.7                                          (0.9)
Refined Petroleum Products (mn tons)                  3.13             (3.4)           3.89              (4.2)            28.8                                           3.6
Steel Products (mn tons)                              1.23             (3.1)           1.26              (6.4)            11.5                                          (1.1)
Copper (mn tons)                                      0.32            (28.8)           0.30             (30.9)           (21.2)                                        (27.2)
Aluminium (mn tons)                                   0.07            (45.3)           0.06             (47.1)           (32.0)                                        (42.4)
Source: CEIC, National Bureau of Statistics, CISA, PBOC, J.P. Morgan calculations. * NBS steel production data and China power demand data are as of March 2013.


Table 4: China: PMI and monetary growth aggregates
Datapoint                                                YTD              Apr 13               Mar 13               Dec 12                Sep 12            Jun 12              Mar 12
PMI- Manufacturing
NBS                                                                           50.6              50.9                 50.6                  49.8              50.2                53.1
HSBC-Markit                                                                   50.4              51.6                 51.5                  47.9              48.2                48.3
Monetary aggregates
M1 Money supply growth                                   12.1                 11.9              11.9                 6.5                   7.3                4.7                4.4
M2 Money supply growth                                   15.7                 16.1              15.7                 13.8                  14.8              13.6                13.4
Social Financing                                         63.0                 81.9              36.3                 27.6                 284.7              63.7                2.7
Loan growth                                              15.0                 14.9              14.9                14.96                  16.2              16.0                15.7
Deposit Growth                                           15.6                 16.2              15.6                 13.3                  13.3              12.3                12.5
Source: Bloomberg, J.P. Morgan Economics.


Table 5: China: Change in total social financing (%oya in the change in stock of total social financing)
                                              April 13           March 13            1Q 2013             4Q 2012                   YTD             2012              2011         2010
Total Social Financing                          82                  36                  58                  33                      58               23               (8)           1
New Loans (RMB)                                 16                   6                  12                 (17)                     12               10               (6)         (17)
New Loans (Foreign Currency)                   782                  59                 235                 305                     235               60               18          (48)
Entrusted Loan                                  90                 127                  86                  86                      86              (1)               48           29
Trust Loans                                    5178                323                 361                 396                     358              534              (47)         (11)
Bank Acceptance Bill                           692                  (3)                189                 543                     189               2               (56)          407
Net Corporate Bond Financing                   114                  96                  90                  31                      89               65               23          (11)
Non Fin Enterprise Equity                       44                 (63)                (29)                (62)                    (29)            (43)              (24)          73
Source: CEIC. *For Not Meaningful %oya, we have shown absolute numbers. Please refer to table 4 on page 6 for absolute numbers of all components



                                                                                                                                                                                         7
Adrian Mowat                             Asia Pacific Equity Research
(852) 2800-8599                          31 May 2013
adrian.mowat@jpmorgan.com




The disconnect; strong TSF growth yet soft economic data
China’s economic success in the last three decades is                   Total social financing to GDP exceeds 180% (see Figure
amazing. This was built on liberalization, large                        16). This is the same as deposits to GDP. It is possible
underemployment (at the start), an industrious workforce                that the TSF data double counts, with companies drawing
and good demographics. In the last decade growth was                    low interest rate loans to finance higher return wealth
increasingly driven by a more capital intensive model.                  management products.
However, this model may be faltering. Despite a
significant increase in total social financing, economic                Figure 16: China total social financing to GDP
momentum is disappointing. Policy makers are
responding to the side-effect of easy credit, inflation of               190%
the property bubble, with new administrative measures.                                         Deposits         Loans        TSF

The central bank is concerned that the combination of a                  170%
tight labor market and rising rents are driving urban
core inflation. Fiscal flexibility is limited, with a deficit            150%
of 2%/GDP. Local-government-guaranteed-debt is
                                                                         130%
reported to be RMB20trillion (40%/GDP) (source:
Bloomberg). Premier Li Keqiang noted that “China is                      110%
confronted by huge challenges”. The reports we
published on these challenges are China 2020 (May                         90%
2011) on labor shortage, EM equities as China slows                             99         01         03       04        06      08        09        11       13
(February 2012) managing the risk and China challenged                  Source: CEIC, PBoC, J.P. Morgan calculation. Note: The PBoC does not disclose the
                                                                        stock of total social financing (TSF). To calculate TSF we use the actual total loans
(June 2012) lessons from other Asian bubbles.                           outstanding each month and add the cumulative net financing of non-loans. The chart is
                                                                        representative of growth.

Our core view is policy limbo. Economic growth
gradually slows. The tails to this view are:                            Figure 17: PMIs and IPs
                                                                                                   Markit PMI ( LHS)              NBS PMI ( LHS)
 Positive for Chinese equities and deep cyclicals:                                                IP ( RHS)
                                                                          60                                                                                   40
  The large monetary stimulus that started in August
  2012 is successful, just with an extended lag, in                       55                                                                                   30
  stabilizing economic activity. Confidence in Chinese                    50                                                                                   20
  growth increases.
                                                                          45                                                                                   10
 Bearish for Chinese equities and deep cyclicals:                        40                                                                                   0
  PBoC recognizing that a tight labor market and rising
                                                                          35                                                                                   -10
  property costs are driving core inflation pre-empts
  higher inflation and removes the current stimulus.                      30                                                                                  -20
  The removal of the stimulus has a higher risk as the                      Apr 05             Apr 07             Apr 09             Apr 11             Apr 13
  expansion in lending was from shadow banking.                         Source: CEIC, J.P. Morgan.
  Another risk is policies to manage the property
  bubble.                                                               Figure 18: China: Decelerating growth in passenger vehicles
                                                                        sales
Our view is closer to the latter. It is increasingly                      120                        Passenger Vehicle Sales (3mmva, %oya)                         30
difficult to compound high growth in                                                                 Retail Sales (%oya, 3mma, RHS)
infrastructure/investment financed by debt.                               100
Demographics are a significant headwind. But we                                                                                                                    25
                                                                            80
acknowledge that confidence is low, commodities and
                                                                            60
cyclical equities did decline in 1Q13, valuations are                                                                                                              20
superficially cheap and Chinese equities, in-line with                      40
EM, are rising. Positioning is bearish energy and                           20                                                                                     15
materials. This strategy has worked very well. A period
                                                                             0
of short covering is reasonable, but arguably this
occurred in the past month with China reversing some of                    -20                                                                                 10
April’s underperformance.                                                    Apr-06     Apr-07     Apr-08     Apr-09     Apr-10    Apr-11     Apr-12     Apr-13
                                                                        Source: CEIC, J.P. Morgan, April 2013


8
Adrian Mowat                          Asia Pacific Equity Research
(852) 2800-8599                       31 May 2013
adrian.mowat@jpmorgan.com

JPM Research Sentiment Index: The analysts PMI to help track the economy
 What is JSI? We launched the monthly J.P. Morgan                          weak. Notably, trend in commodities appears to be on
  Research Analyst Sentiment Index (JSI) in August                          the uplift. Latest month data shows 15 sectors with
  2012. Think of this as a PMI survey where sector                          above 50 readings vs. 14 in April.
  analysts act as the purchasing managers. This takes                Figure 19: Aggregate JSI
  advantage of J.P. Morgan’s extensive sector and                      70.0                                                3ma                 64.3
  company coverage in China. We believe a broad-based,                                             61.2            59.8
                                                                       60.0                                               57.2
  bottom-up leading indicator tracking aggregate                                 44.2     48.5             49.2
                                                                                                                                                                   46.9
                                                                       50.0
  company-level performance is useful information for                                                                                                    38.4
                                                                                                                                      39.4
  investors. The JSI is designed to complement the wide                40.0
  range of macro data tracking China’s economy,                        30.0
  including the official NBS and the HSBC Markit PMIs.                 20.0

 How is the JSI constructed? - Our approach in                        10.0
  constructing the JSI is based on the principle behind all             0.0
  purchasing managers’ indices (PMI/ISMs). The                               Aug-12                       Nov-12                    Feb-13                        May-13
                                                                     Source: J.P. Morgan.
  questions are modified in order to be relevant to the
                                                                     Figure 20: No of sectors above 50 readings
  company/sector covered. Our analysts are asked if
                                                                       25
  conditions have improved, worsened or remained                                                                          3ma
                                                                                                                                                   20
  unchanged compared to the previous month, on key                     20                                                  18
                                                                                                                   17
  issues for their industries. These include output                                     16
                                                                                                   16      16
                                                                                                                                                             14
                                                                                                                                                                    15
  volume, sales, order book, costs, gross margin,                      15
                                                                                13
  inventory to sales condition and industry EPS. We then                                                                              11

  calculate the JSI reading for each sector and a MSCI                 10

  China weighted aggregate for our coverage universe.                   5
 How to interpret the JSI? - The JSI readings could
                                                                        0
  be interpreted from two different perspectives. A time                   Aug-12                         Nov-12                    Feb-13                        May-13
  series of the aggregate reading would represent how                Source: J.P. Morgan.
  the aggregate China space has changed during                       Figure 21: JSI factor reading
  different stages of the cycle. A cross section                                                                                                        67
                                                                                 Order book
  comparison of the readings across different sectors                                                                                    43
                                                                                                                                               55
  represents the relative performance of each sector at a                                                                                51
                                                                               Gross Margin                                         47
  particular time.                                                                                                             40
                                                                                                                                         50
Latest JSI 46.9 from 38.4 April, but still below 50 for                              Volume                               35                                 74
the first time.                                                                                                                     45
                                                                              EPS Revisions                                    35
 JSI & Macro picture – New 2013 GDP forecast 7.6%                                                                                        53
   (from 7.8%). Manufacturing investment is slowing,                                                                           40
                                                                                   Inventory                                                        63
   with IP weaker than expected. Inventories are                                                                                          53
   building.                                                                   Industry Cost
                                                                                                                           38
                                                                                                                                               53
                                                                                                                          34
 JSI & Other PMIs – Latest JSI readings came along
                                                                                               0            20            40                  60             80
  with the weaker-than-expected flash May Markit PMI,
  which indicated that underlying momentum in the                                                           May-13             Apr-13               1Q13
  industrial sector remained modest.                                 Source: J.P. Morgan.

 Sectoral Dispersion & Trends – On a trend basis,
  sentiment for autos, consumer and financials remains




                                                                                                                                                                           9
Adrian Mowat                                               Asia Pacific Equity Research
(852) 2800-8599                                            31 May 2013
adrian.mowat@jpmorgan.com




Alpha rich beta poor: The dispersion of returns
Table 6: MSCI China constituents’ performance (85% by market cap)– ranked by YTD performance
Name                        Code           Sector         Weg (%)        Rating        Price       Fwd PE (x)        DY (%)               Performance (%)
                                                          in MXCN                                                             YTD   3M          6M        12M   36M
Chin.Longyuan Pwr.           916          Utilities          0.4           OW           8.0            14.7            1.0     49   16           65        74    12
Great Wall Motor            2333        Cons.Disc.           0.7           OW           36.1           11.4            2.0     47   18           45       144   660
China Ste.Con.              3311        Industrials          0.4           OW           12.1           15.6            1.3     30   15           28        85   385
China Vanke 'B'            200002        Property            0.4           OW           16.1           8.5             1.4     29     8          46        72   120
Enn Energy                  2688          Utilities          0.6           OW           42.7           17.8            1.0     27   14           23        55    93
Hengan Intl.                1044        Cons.Stap.           1.2            N           86.8           24.0            2.0     24   11           25        13    66
Tencent                      700             IT              5.7           OW          299.4           24.3            0.3     20   13           17        40   103
China Mengniu               2319        Cons.Stap.           0.6           OW           26.5           21.3            0.8     20   19           22        28    25
China Gas                    384          Utilities          0.4            N           7.3            19.3            0.8     20     7          41        92    86
Beijing Enterprises          392        Industrials          0.6           OW           60.6           16.2            1.2     20     5          20        46    28
Guangzhou Auto              2238        Cons.Disc.           0.3           OW           8.2            13.9            4.1     19   24           39        28   n.a.
GDI                          270          Utilities          0.3           OW           7.1            13.4            2.8     16     8          16        34    96
Huaneng Power                902          Utilities          0.5           UW           8.2            9.3             3.2     15     6          29        70    78
Shimao Property              813         Property            0.4           OW           16.6           7.0             3.3     14     5           7        66    46
CRLand                      1109         Property            0.9           OW           23.2           13.2            1.5     10     5          15        70    55
Country Garden              2007         Property            0.4           OW           4.5            7.6             3.9     10   16           27        59   114
Lenovo Group                 992             IT              0.9           OW           7.7            13.5            2.4      9   -10           7        14    53
Want Want China              151        Cons.Stap.           1.3            N           11.6           27.4            1.9      9   13            3        25    99
China Min. Banking          1988          Banks              0.9           UW           9.6            5.1             3.9      7    -5          29        35    52
Bank Of China               3988          Banks              5.1            N           3.7            5.5             6.0      6     0          13        29    -4
Bank Of Comms.              3328          Banks              1.0            N           6.0            5.7             5.0      3     0           7        19   -13
China Res.Power              836          Utilities          0.7            N           20.2           9.6             2.5      2    -4          18        46    33
China Con.Bank               939          Banks              8.5           OW           6.3            5.8             5.3      1     0           6        23     4
China Oilfield Svs.         2883          Energy             0.5            N           16.1           10.5            2.4      1     1           7        55    77
China Mrch.Hdg.              144        Industrials          0.5           UW           25.0           13.9            2.8      1    -9           5         8     4
China Comms.Con.            1800        Industrials          0.6           OW           7.5            6.8             3.1      1     2           8         4    18
China Os.Ld.& Inv.           688         Property            1.8            N           23.1           9.3             1.7      0     4           3        47    48
Dongfeng Motor               489        Cons.Disc.           0.6           UW           12.0           8.0             1.6      0     4          13        -5    33
Cosco Pacific               1199        Industrials          0.3           OW           10.8           9.6             3.6     -2   -11          -1        19    17
ICBC'H'                     1398          Banks              6.5           OW           5.4            5.7             5.5     -2    -2           3        16    -2
MSCI China                                                                              60.1           9.1             3.1     -4    -3           1        14     3
ABC                         1288          Banks              1.5            N           3.7            5.6             5.4     -5    -9           8        16   n.a.
China Citic Bank             998          Banks              0.6           UW           4.4            4.6             4.3     -5   -10           8         5     0
Anhui Conch                  914         Materials           0.6           OW           26.6           12.2            1.2     -6    -5           4        18    70
China Mer. Bank             3968          Banks              1.2            N           16.1           6.0             4.9     -6    -4          11        10   -12
China Pac.In.               2601        Insurance            1.3           NR           26.8           17.7            1.6     -6    -5           6        21   -11
China Ptl.& Chm.             386          Energy             3.0           NR           8.2            7.3             4.6     -6    -6          -2        16    36
Inner Mongolia Yitai       900948         Energy             0.5           NR           5.3            8.0             2.2     -7    -8          -2        -3    22
Tingyi                       322        Cons.Stap.           0.7           UW           19.9           26.6            1.3     -7    -5          -9        -1    25
China Mobile                 941           Telco             9.3           UW           82.9           10.6            5.1     -8    -3          -6         4    12
Kunlun Energy                135          Energy             0.9           OW           14.8           13.8            1.6     -9    -6          -4        21    46
Brilliance China            1114        Cons.Disc.           0.4           OW           8.7            10.5            0.0     -9   -17          -5        24   260
Sinopharm Group             1099         Health C            0.4           OW           22.0           16.5            1.4     -9   -11         -11        26   -24
Ping An Insurance           2318        Insurance            2.1           NR           58.7           12.1            1.0    -10    -9          -1         2    -4
China Telecom                728           Telco             1.0            N           3.9            12.6            2.2    -10    -3         -12         7    12
China Unicom                 762           Telco             1.0           OW           11.1           16.4            1.4    -11    -1         -11        -3    20
Longfor Properties           960         Property            0.3            N           13.5           8.6             1.9    -11    -1          -4        18    79
Picc Prop & Clty.           2328          Banks              0.5           NR           9.6            8.4             2.7    -11   -11          -5        18    44
Sun Art Retail              6808        Cons.Stap.           0.5           NR           10.5           26.8            1.1    -12    -4          -7         8   n.a.
CRE                          291        Cons.Stap.           0.5           NR           24.5           22.4            1.2    -12    -4          -7        -1    -4
Petrochina                   857          Energy             3.7           NR           9.5            9.7             3.8    -14   -12          -8        -6    14
Cnooc                        883          Energy             4.6           NR           13.9           7.7             3.4    -17    -9         -16        -2    12
China Life Ins              2628        Insurance            2.9           NR           20.8           14.9            0.8    -18   -10          -9        16   -39
China Nat.Bldg.Mra.         3323         Materials           0.5            N           8.8            5.0             2.2    -22   -24         -11        -6    46
China Shenhua En.           1088          Energy             1.6           OW           26.0           8.4             4.6    -23   -10         -20        -6   -14
Jiangxi Copper               358         Materials           0.4           NR           15.4           9.1             4.1    -24   -16         -22        -3     2
Evergrande Real             3333         Property            0.4           OW           3.2            4.6             0.0    -25   -17         -13       -16    59
Belle International         1880        Cons.Disc.           1.0            N           12.0           15.5            1.7    -29   -17         -24        -6    28
China Coal Energy           1898          Energy             0.4           OW           5.3            7.2             4.9    -37   -28         -32       -26   -49
Source: MSCI, IBES, Datastream, J.P. Morgan. Price as of 24 May 2013. Remark: Share price in US$ for Inner Mongolia Yitan.




10
Adrian Mowat                                               Asia Pacific Equity Research
(852) 2800-8599                                            31 May 2013
adrian.mowat@jpmorgan.com




Table 7: Q-scores helped… (top 85% by market cap) – ranked by YTD performance
         Name                   RIC             Sector          Rec       Price       FF Mkt        Value   Earn    Qlty    Price   Overall   FY13EPS   Re/de-rating
                                                                                        Cap                                                      rev     (Fwd PE)
                                                                                     (US$bn)        Score   Score   Score   Score   Q-score       6m         6m
Chin.Longyuan Pwr.              916            Utilities        OW         8.0          2.8          12%     51%     15%     56%     17%         -4%        54%
Great Wall Motor               2333          Cons.Disc.         OW        36.1          4.8          40%     96%     72%     99%     97%        33%          1%
China Ste.Con.                 3311          Industrials        OW        12.1          2.7          21%     74%     94%     90%     74%          0%        14%
China Vanke 'B'               200002          Property          OW        16.1          2.7          31%     49%     91%     91%     68%          7%        22%
Enn Energy                     2688            Utilities        OW        42.7          4.1          16%     24%     98%     48%     29%          2%        10%
Hengan Intl.                   1044          Cons.Stap.          N        86.8          8.2          28%     82%     91%     47%     70%         -3%        17%
Tencent                         700               IT            OW        299.4         39.3         50%     21%     90%     36%     37%          2%         3%
China Mengniu                  2319          Cons.Stap.         OW        26.5          4.2          37%     82%     34%     57%     63%        -16%        30%
China Gas                       384            Utilities         N         7.3          3.0          42%     95%     26%     97%     86%        22%          5%
Beijing Enterprises             392          Industrials        OW        60.6          4.0          38%     90%     36%     95%     93%          0%         9%
Guangzhou Auto                 2238          Cons.Disc.         OW         8.2          2.3          69%     59%      5%     18%     26%        -25%        58%
GDI                             270            Utilities        OW         7.1          2.3           6%     91%     75%     93%     81%          3%         9%
Huaneng Power                   902            Utilities        UW         8.2          3.4          93%     29%     38%     73%     71%        25%         -2%
Shimao Property                 813           Property          OW        16.6          3.0          96%     71%     61%     89%     96%        14%        -13%
CRLand                         1109           Property          OW        23.2          6.1          34%     92%     41%     96%     78%        11%         -7%
Country Garden                 2007           Property          OW         4.5          2.6          51%     81%     83%     71%     77%        12%          5%
Lenovo Group                    992               IT            OW         7.7          6.1          81%     80%     79%     35%     94%          0%        -2%
Want Want China                 151          Cons.Stap.          N        11.6          8.9          22%     57%     99%     90%     73%          0%        -7%
China Min. Banking             1988            Banks            UW         9.6          6.5          66%     76%     93%     81%     84%        26%         -1%
Bank Of China                  3988            Banks             N         3.7          35.5         50%     69%     63%     53%     67%        12%         -2%
Bank Of Comms.                 3328            Banks             N         6.0          6.8          32%     38%     57%     41%     33%        11%         -6%
China Res.Power                 836            Utilities         N        20.2          5.0          75%     90%     66%     60%     88%        17%         -5%
China Con.Bank                  939            Banks            OW         6.3          58.5         45%    100%     96%     59%     91%        10%         -7%
China Oilfield Svs.            2883            Energy            N        16.1          3.2           9%     19%     74%     86%     26%          2%         1%
China Mrch.Hdg.                 144          Industrials        UW        25.0          3.6          64%     85%     65%     50%     72%         -4%         4%
China Comms.Con.               1800          Industrials        OW         7.5          4.3          91%     94%     92%      7%     96%          5%        -2%
China Os.Ld.& Inv.              688           Property           N        23.1          12.2         55%     79%     93%     81%     82%          5%        -9%
Dongfeng Motor                  489          Cons.Disc.         UW        12.0          4.2          74%     46%     37%     14%     49%         -1%        10%
Cosco Pacific                  1199          Industrials        OW        10.8          2.3          79%      8%     67%     61%     53%         -7%         1%
ICBC'H'                        1398            Banks            OW         5.4          45.2         46%     85%     96%     41%     74%          8%        -8%
MSCI China                                                                60.1         690.6                                                      2%        -1%
ABC                            1288             Banks            N         3.7          10.1         56%    43%     86%     44%      57%          9%        -6%
China Citic Bank                998             Banks           UW         4.4          4.2          74%    37%     56%     19%      52%          2%         2%
Anhui Conch Cement              914            Materials        OW        26.6          4.2          41%    83%     70%     88%      83%          5%        -8%
China Mer. Bank                3968             Banks            N        16.1          8.1          33%    87%     88%     29%      68%        17%         -8%
China Pac.In.                  2601           Insurance         NR        26.8          9.1          14%    21%     17%     53%      13%         -9%         5%
China Ptl.& Chm.                386             Energy          NR         8.2          20.8         90%    97%     52%     84%      98%          5%       -10%
Inner Mongolia Yitai          900948            Energy          NR         5.3          3.2          64%    46%     99%     34%      65%        -14%         6%
Tingyi                          322          Cons.Stap.         UW        19.9          5.0          17%     4%     39%     56%       9%        -20%         2%
China Mobile                    941              Telco          UW        82.9          64.4         59%     9%     85%     33%      38%          1%        -5%
Kunlun Energy                   135             Energy          OW        14.8          6.1          23%    35%     71%     79%      50%         -5%        -7%
Brilliance China               1114          Cons.Disc.         OW         8.7          2.8          72%    10%     45%     42%      32%         -4%       -12%
Sinopharm Group                1099          Health Care        OW        22.0          2.8          27%    88%     88%     85%      75%         -1%       -19%
Ping An Insurance              2318           Insurance         NR        58.7          14.2         20%    29%     45%     23%      21%          1%       -10%
China Telecom                   728              Telco           N         3.9          6.9          24%    65%     29%     36%      40%         -6%       -16%
China Unicom                    762              Telco          OW        11.1          6.7          18%    44%     10%     21%      18%         -2%       -23%
Longfor Properties              960            Property          N        13.5          2.4          34%    18%     58%     12%      22%         -6%        -6%
Picc Prop & Clty.              2328             Banks           NR         9.6          3.3           8%     0%     77%     49%       8%         -1%        -7%
Sun Art Retail                 6808          Cons.Stap.         NR        10.5          3.2          15%    65%     62%     83%      60%         -2%       -13%
CRE                             291          Cons.Stap.         NR        24.5          3.8           3%     1%     23%     80%       4%        -17%         5%
Petrochina                      857             Energy          NR         9.5          25.7         52%    48%     35%     44%      46%         -6%        -5%
Cnooc                           883             Energy          NR        13.9          32.0         70%    93%     61%     47%      79%         -3%       -14%
China Life Ins                 2628           Insurance         NR        20.8          19.9         18%    15%     12%     30%      10%         -3%       -16%
China Nat.Bldg.Mra.            3323            Materials         N         8.8          3.3          98%    35%     80%     67%      80%          6%       -23%
China Shenhua En.              1088             Energy          OW        26.0          11.4         49%    56%     69%     50%      58%         -2%       -20%
Jiangxi Copper                  358            Materials        NR        15.4          2.8          36%    13%     48%     52%      15%        -17%        -4%
Evergrande Real                3333            Property         OW         3.2          2.6          88%     3%     66%      3%      29%        -21%         2%
Belle International            1880          Cons.Disc.          N        12.0          7.1          47%     2%     60%     33%      19%        -12%       -20%
China Coal Energy              1898             Energy          OW         5.3          2.8          94%     5%     24%     31%      35%        -13%       -25%
Source: MSCI, IBES, Factset, Datastream, J.P. Morgan. Remark: Share price in US$ for Inner Mongolia Yitan




                                                                                                                                                             11
Adrian Mowat                              Asia Pacific Equity Research
(852) 2800-8599                           31 May 2013
adrian.mowat@jpmorgan.com




The J.P. Morgan Q-score                                                   shown to constantly explain some of this return. The aim
The J.P. Morgan Q-Score provides an indication of a                       is to outperform the benchmark by targeting our
company’s expected return versus both its country peers                   portfolios toward those stocks with positive factor
and its regional industry peers using a balanced multi-                   exposures and away from those with negative factor
factor quantitative approach. The goal is a simple one. To                exposures.
bias stock selection towards cheap, successful, quality
companies with solid earnings and away from expensive,                    The Q-Score is generated by evaluating the companies’
poor quality, unsuccessful companies with poor earnings.                  prospects based on combining 10 such factors
                                                                          categorized into four factor families. These families are
The higher the company scores, the higher the expected                    current valuation, recent success or momentum, quality
return (or Alpha) relative to the considered universe. A                  attributes and a consideration of recent changes in
score of 50% indicates that this company is expected to                   earnings and sentiment. The detail for each factor
perform in line with the benchmark universe. A score                      family is shown in the table below.
greater than 50% indicates an expected outperformer, and
a score less than 50% indicates an expected under-                        Liquidity/investibility criteria
performer. All scores are expressed as a percentile rank                     Market cap greater than US$2 billion;
from 0% to 100%.
                                                                             Daily turnover greater than US$5 million.
How is the Q-Score calculated?                                            Exception: Minimum of 5 stocks per market.
Share prices are affected by many different factors.
Quant practitioners attempt to isolate factors that can be

                        Value Q-score                                                          Earnings Q-score
Many quant researchers have explored the ‘Value Anomaly’ and           The market is not efficient at incorporating new information and a
it is widely recognized that low P/E stocks outperform high P/E        window of opportunity exists to exploit recent analyst revisions in
stocks over the long term. Similar analysis has shown consistent    earnings and recommendations. Similarly analyst behavioral biases lead
results using P/Sales, P/Dividend and P/Book ratios. Our studies      to subsequent changes suggesting an exploitable serial correlation in
have also shown that Earnings Growth can complement straight                            earnings upgrades/downgrades.
                 Value factors in many markets.

                    Component Factors                                                        Component Factors
            12M Forward P/E vs Market (34%)                              Earnings Momentum 3M avg FY1&FY2, Risk Adjusted (34%)
         12M Forward P/E vs Country Sector (33%)                               1M change in consensus recommendations (33%)
     EPS Growth; forecast FY1 mean to FY2 mean (33%)                     Net Revisions (upgrades-downgrades) to mean FY2 EPS (33%)
                     Momentum Q-score                                                           Quality Q-score
Momentum theory for stock prices suggests that companies that        Whilst arguably less readily observable than some other factors, it is
do well in one (long term) investment period will continue to do     generally accepted that it is desirable to tilt portfolios towards highly
   well in the subsequent investment horizon. Over short time       profitable and good quality businesses. Similarly over the long term the
frames (<1month) studies have also highlighted the tendency of       market also appears to reward 'earnings certainty' and penalize those
  stocks to overreact leading to short term reversion. We have                  stocks that carry a large degree of earnings risk.
     widely observed these phenomenon in our own testing


                     Component Factors                                                        Component Factors
                 12M Price Momentum (75%)                                    ROE: average of FY1 and FY2 mean forecast (50%)
                  1M Price Reversion (25%)                               Earnings Risk: Variation in FY1 and FY2 forecast EPS (50%)




12
Adrian Mowat                           Asia Pacific Equity Research
(852) 2800-8599                        31 May 2013
adrian.mowat@jpmorgan.com




Questions that equity investors should ask
Policy and reform                                                     11. Property prices are too high relative to household
1. What are the government’s reform priorities in 2013?                   income. Will the government impose stricter
   See Revitalizing China through Reform, Hand on                         restrictions in the property market?
   China, Ulrich et al 29 May 2013.                                   Shadow banking/financial risk
2. What are the sector implications of reforms?                        12. Is China's capital intensive growth model now
                                                                           constrained by excess debt?
3. Can the service sector (45% GDP, 36% of
   employment and growing at 8.3%oya (faster than                     13. How serious is the risk from shadow banking? See
   GDP)) drive growth? What steps are being taken to                      China Banks: Reality Check on April Data: Kept
   increase the service sector’s share of GDP and                         Afloat by Liquidity, Lei et al, 20 May 2013.
   employment? See Can China’s Service Sector Propel
                                                                      14. Will Chinese authorities remain supportive of the
   Growth, Hands on China, Ulrich et al, 10 May 2013.
                                                                          development of shadow banking? See China Banks:
4. Will the trend of real GDP growth forecast                             New Regulation on Bond Trading May Further
   downgrades continue? J.P. Morgan’s 2013 GDP                            Lower Yield of WMP – ALERT, Lei et al, 16 May
   growth forecast is now 7.6%.                                           2013.
5. What factors could cause a re-acceleration in                      15. Can China’s overdependence on debt result in a
   economic growth and/or an equity market rally in                       financial crisis?
   2H13?
                                                                      Equity market
6. Will RMB appreciation continue? The RMB real                       16. MSCI China 2013 consensus EPS growth forecast is
   effective exchange rate appreciation is significant.                   12%. How much is the downside risk to EPS
7. What would be the impact of further JPY                                forecasts? Which sectors are likely to suffer further
   depreciation on RMB?                                                   EPS downgrades?

8. Can China’s new leadership deliver on its reform                   17. Will the SoEs (75% of the benchmark) remain cheap
   objectives?                                                            as investors fear adverse policy?

9. Pollution is a serious issue. How willing are policy               18. Can utilities, staples and IT maintain their premium
   makers to forego growth in order to deal with this                     valuations?
   significant health issue?                                          19. Which sectors should benefit/lose if the Fed exits
Inflation                                                                 QE earlier than expected?
10. Will the PBOC, recognizing the core inflation drivers             20. Has corporate governance of Chinese companies
    of a tight labor market and rising property prices,                   improved?
    tighten policy despite slower growth?




                                                                                                                               13
  Adrian Mowat                          Asia Pacific Equity Research
  (852) 2800-8599                       31 May 2013
  adrian.mowat@jpmorgan.com


                                                                                           Asia Technical Analysis Research
                                                                                           Sunil GargAC
                                                                                           (852) 2800-8518

 Rotation - Into China?                                                                    sunil.garg@jpmorgan.com
                                                                                           J.P. Morgan Securities (Asia Pacific) Limited
 Asia Technicals Strategy: Charting the Course
 Priced on 30 May 2013




 Rotational Trades – We see a rotational bias in markets in Asia with a real possibility of both SHCOMP and
  MSCI China building on recent outperformance (since mid-Apr) backed by absolute levels supported at the
  bottom end of trading ranges. While both indices need clear breakouts from ranges (see levels below) to
  establish direction, an absolute trading bounce seems well supported.
 Is the China Move for Real? – Until we see clear evidence of a breakout past 62.5 and 66.5 on MSCI China
  and 2470 on SHCOMP, we are reluctant to call for anything other than a trading bounce. We do however keep
  the possibility open for a larger rally developing, should these levels be exceeded.
 MSCI China – Absolute View – MXCN's                Figure 22: MSCI China Relative to MXAPJ – Weekly Chart
 fundamental trading view is well matched on
 the charts with a breakout of 57-62.5 range
 needed to determine conclusive direction. For
 now, protecting 60 (40wma/ 200dma/ recent
 lows) is important to retain any long bias. The
 bigger picture view suggests that the uptrend
 (yes!) from Oct’11 lows remains in place for
 now and gets affirmed above 66.5.
 Recommendation – (1) Hold long for a
 trading bounce/ STOPS at 57 (2) Short below
 57 and enter new longs above 62.5
 SHCOMP – Absolute View - Despite being
 stuck in a tight trading range (even more so
 than MXCN), SHCOMP is looking much more
 constructive on a near-term basis with the
 likelihood of a stab at 2440-70 upside and a
 meaningful move if it gets past that.
 Recommendation – (1) Hold long for a
 trading bounce/ STOPS at 2250 (2) Short
 below 2161 and enter new longs above 2470

 MSCI China vs. MXAPJ - MSCI China has
 been in a 10% pt relative performance trading
 zone since late 2011 and has recently bounced
 off the lows of this trading range, backed by a
 positive MACD cross-over on weekly charts.
 Currently at 167, the relative index should
 face initial resistance at 168.7 (40wma) and if
 that is cleared, there is no major resistance
 until 177-78. Daily chart is facing resistance
 on its 200dma.                                     Source: Bloomberg.




  14
Adrian Mowat                           Asia Pacific Equity Research
(852) 2800-8599                        31 May 2013
adrian.mowat@jpmorgan.com




MSCI China – Absolute View
                                       Figure 23: MSCI China - Weekly Chart
Recommendation


(1)   Hold long for a trading
      bounce/ STOPS at 57

(2)   Short below 57 and enter
      new longs above 62.5



Weekly Chart – Rally from Apr’13
lows was halted at Feb’12
resistance in the 62.5 area. Decline
from the Feb'12 high, is now sitting
on 40wma support (60.4) and also
uptrend lines from Oct’11/ Sep ’12.
Current week potentially forms a
reversal week/ “doji” suggesting
support from current levels. Do
note the MACD remains in sell
mode for now.




                                       Source: Bloomberg.


                                       Figure 24: MSCI China - DAILY Chart
Daily Chart – Similar to the weekly
chart, daily MXCN is sitting
precariously in its 200dma (60.2)
as also the 24th May low of 59.8.
These are critical support levels.
Upside is capped, for now, at twin
highs in May at 62.7. MACD
remains in a sell mode.




                                       Source: Bloomberg.

                                                                              15
Adrian Mowat                         Asia Pacific Equity Research
(852) 2800-8599                      31 May 2013
adrian.mowat@jpmorgan.com




SHCOMP – Absolute View
Recommendation                       Figure 25: SHCOMP - Weekly Chart

(1)   Hold long for a trading
      bounce/ STOPS at 2250

(2)   Short below 2161 and enter
      new longs above 2470




Weekly Chart – SHCOMP’s
weekly chart is much more stuck in
a range (when compared to
MXCN) YET, it also looks much
more promising for a short-term
bounce, following support from a
rising 40wma. Next important
resistance is 2440-70 range. On
the downside, 2161 is important to
protect to stay constructive.
IMPORTANTLY, weekly MACD
appears to be in early stages of a
positive cross-over.




                                     Source: Bloomberg.


                                     Figure 26: SHCOMP - DAILY Chart




Daily Chart – MACD is in a buy
mode since Apr’13, in sync with
inflection point and is supporting
the up-move, as is the RSI. Golden
cross on May 27 supports a near-
term positive stance.




                                     Source: Bloomberg.




16
Adrian Mowat                           Asia Pacific Equity Research
(852) 2800-8599                        31 May 2013
adrian.mowat@jpmorgan.com




MSCI China – Relative to MXAPJ
                                       Figure 27: MSCI China vs. MXAPJ – Weekly Chart
MSCI China has been in a 10% pt
relative performance trading
zone since late 2011 and has
recently bounced off the lows of
this trading range, backed by a
positive MACD cross-over on
weekly charts. Currently at 167,
the relative index will face initial
resistance at 168.7 (40wma) and
if that is cleared, there is no
major resistance until 177-78.
Daily chart is facing resistance
on its 200dma.




                                       Source: Bloomberg.




                                                                                        17
Adrian Mowat                                        Asia Pacific Equity Research
(852) 2800-8599                                     31 May 2013
adrian.mowat@jpmorgan.com




Valuations: the good, the bad and the ugly
Figure 28: 12m forward PER – High PE growth                                        Figure 29: PBR – High PE growth
 35                                                                                 10           Hth Care
                       Hth Care                                                                  IT
                       IT                                                            8           Con. Staples
 30
                       Con. Staples
 25                                                                                  6

                                                                                     4
 20
                                                                                     2
 15
                                                                                     0
 10                                                                                   Apr-03     Apr-05         Apr-07      Apr-09       Apr-11    Apr-13
  May-03         May-05           May-07   May-09        May-11      May-13
Figure 30: 12m forward PER – Cyclicals                                             Figure 31: PBR - Cyclicals
 25                                                               Cons. Disc.        5           Con. Disc.
                                                                  Materials                      Materials
                                                                                     4           Energy
 20                                                               Energy
                                                                                                 Industrials
                                                                  Industrials        3
 15
                                                                                     2

 10                                                                                  1

                                                                                     0
  5                                                                                   Apr-03     Apr-05         Apr-07      Apr-09       Apr-11    Apr-13
  May-03         May-05           May-07   May-09        May-11      May-13
Figure 32: 12m forward PER – Telecom and utilities                                 Figure 33: PBR – Telecom and utilities
 20                     Utilities                    Peak PE -                       5           Utilities                           Peak PB -
                                                     Util: 22x on 19Oct07                                                            Util: 3.3x
                        Telecom                                                                  Telecom
 18                                                  Telco: 28x on 2Nov07                                                            Telco: 7.2x
                                                                                     4                                               on 31Oct07
 16
                                                                                     3
 14

 12                                                                                  2

 10
                                                                                     1
  8                                                                                   Apr-03     Apr-05         Apr-07      Apr-09       Apr-11    Apr-13
  May-03         May-05           May-07   May-09        May-11      May-13
Figure 34: 12m forward PER – Financials                                            Figure 35: PBR – Financials
 30                                                               Banks              7            Banks
                                                                  R.Estate                        R. Estate
 25                                                                                  6
                                                                  Insurance                       Insurance
                                                                                     5
 20
                                                                                     4
 15
                                                                                     3
 10                                                                                  2

  5                                                                                  1
                                                                                     0
  0                                                                                   Apr-03     Apr-05         Apr-07      Apr-09       Apr-11    Apr-13
  May-03         May-05           May-07   May-09        May-11      May-13
Source: MSCI, IBES, Datastream.




18
Adrian Mowat                                             Asia Pacific Equity Research
(852) 2800-8599                                          31 May 2013
adrian.mowat@jpmorgan.com




Table 8: J.P. Morgan China Universe
Price as of                                                                                    Price        Target Price    Mkt   Avg. Daily       EPS     EPS Y/Y Growth      P/E         P/BV        ROE     Div. Yield
May 28, 2013                                       Analyst               Rec   RIC Ticker           D/D            Upside   Cap    Turnover    FY1E FY2E FY1E      FY2E   FY1E FY2E FY1E FY2E FY1E FY2E FY1E FY2E
Exchange rate = 6.12                                                                        (HKD) (%)     (HKD)     (%)   (US$MM) (US$MM)      (HKD) (HKD) (%)      (%)    (x)     (x) (x)      (x) (%)   (%) (%)     (%)
Apparel & Textile
Anta Sports Products Ltd.**                        Li, Shen Wei          UW     2020.HK      7.3   -1.4   3.30    -54.5    2,332      4.3      0.35   0.28   -36.1   -18.9   16.4   20.3   2.0   2.0   12.4    9.8   3.7   3.0
China Lilang Ltd.**                                Li, Shen Wei           N     1234.HK      4.6    0.4   3.70    -19.7     713       1.2      0.42   0.43   -19.9    2.8     8.7    8.5   1.7   1.6   20.5   19.6   6.3   6.6
Mkt Cap Weighted Aggregates                                                                                                3,045      5.4      0.4    0.3    -32.4   -13.1   14.6   17.5   2.0   1.9   14.3   12.1   4.3   3.8
Auto & Auto Parts
Brilliance China Automotive**                      Lai, Nick YC          OW     1114.HK      8.9    2.7   11.00   24.2     5,735     19.0      0.46   0.52   25.8    14.0    15.3   13.4   3.8   3.0   28.3   24.7   0.0   0.0
China ZhengTong Auto Service Holding Limited**     Lai, Nick YC          OW     1728.HK      4.3    3.8   8.50     96.3    1,233      4.3      0.27   0.60    8.6    NM      12.5   5.7    1.1   0.9    9.2   17.3   1.5   0.9
DongFeng Motor Co., Ltd.**                         Lai, Nick YC          UW     0489.HK     12.2    0.3   7.50    -38.3   13,495     23.7      1.06   1.04   -13.3   -1.8     9.1   9.3    1.5   1.3   18.1   15.5   1.9   1.9
Great Wall Motor Company Limited**                 Lai, Nick YC          OW     2333.HK     37.1    3.9   40.00    7.8    17,305     34.1      2.50   2.89   33.5    15.8    11.7   10.1   3.9   3.0   34.3   33.6   1.0   1.0
Geely Automobile Holdings Ltd.**                   Lai, Nick YC          OW     0175.HK      3.8    0.5   7.00    82.3     4,092     33.5      0.22   0.41    0.6    83.0    13.6   7.4    1.5   1.3   12.4   18.9   1.3   1.9
Guangzhou Automobile Group Co. Ltd.**              Lai, Nick YC          OW     2238.HK      8.6   -0.6   12.00    39.2    8,809      8.0      0.35   0.67   94.3    94.0    19.6   10.1   1.3   1.2    6.9   12.2   0.3   1.0
Minth Group**                                      Lai, Nick YC           N     0425.HK     13.7    5.9   11.00   -19.8    1,912      2.1      0.78   0.90    6.7    15.3    13.9   12.0   1.8   1.7   13.5   14.6   2.5   2.2
Weichai Power**                                    Li, Karen             UW     2338.HK     30.5    3.2   18.50   -39.3    7,790     12.8      1.82   2.02   21.4    11.4    13.2   11.9   1.7   1.5   13.8   13.7   1.8   0.4
Xinyi Glass                                        Chik, Leon            OW     0868.HK      6.8    6.8   8.00    18.5     3,293     11.8      0.50   0.70   58.6    39.5    13.4   9.6    2.3   2.1   18.3   22.8   3.4   4.7
Mkt Cap Weighted Aggregates                                                                                               63,665     149.3     1.3    1.5    20.6    16.5    13.0   10.2   2.4   2.0   20.7   21.2   1.3   1.3
Building Materials & Construction
Anhui Conch Cement Company Limited - A             Lai, Nick YC          OW    600585.SS    17.5    3.3   22.00   25.9    15,934     85.7      1.56   1.65   30.6     6.0    11.2   10.6   1.4   1.2   13.5   12.6   1.4   1.3
Anhui Conch Cement Company Limited - H**           Lai, Nick YC          OW     0914.HK     27.0    1.9   32.00   18.5    15,934     47.4      1.56   1.65   30.6     6.0    13.6   12.9   1.7   1.5   15.3   14.3   1.6   1.2
BBMG Corp**                                        Lai, Nick YC          N      2009.HK      5.7   -1.9   6.00     4.9     4,118      6.8      0.58   0.72   -16.0   23.5    7.8    6.3    0.9   0.8   11.1   13.1   1.6   2.6
China Communications Construction Co. Ltd.**       Li, Karen             OW     1800.HK      7.4   -0.7    9.00   21.1    13,967     18.5      0.71   0.77   -10.2    7.7    8.2    7.6    1.1   1.0   13.9   13.3   3.0   3.2
China National Building Material**                 Lai, Nick YC           N     3323.HK      8.7    1.6   10.00   15.1     6,043     57.7      1.11   1.44    7.3    30.2    6.2    4.7    1.1   0.9   12.8   14.4   2.3   3.2
China Railway Construction Corporation Limited**   Li, Karen             OW     1186.HK      7.8    1.0   11.60   49.1    10,780     12.8      0.71   0.84   11.4    18.5    8.6    7.3    1.0   0.9   12.6   13.5   3.5   4.1
China Railway Group Limited**                      Li, Karen             OW     0390.HK      4.1    2.0   5.80    40.8    10,274     10.7      0.35   0.41    9.9    19.6    9.4    7.9    0.9   0.8   9.8    10.7   2.1   2.5
China Resources Cement**                           Lai, Nick YC           N     1313.HK      4.3    0.9   5.50    28.8     3,586      6.9      0.36   0.52   -44.4   45.4    9.4    6.5    1.0   0.9   11.2   14.4   1.8   1.1
China Liansu**                                     Hsu, Andrew Tak Jun   OW     2128.HK      4.6    3.2   5.60    22.3     1,796      4.6      0.49   0.58    19.8   17.4    7.3    6.2    1.5   1.3   22.3   22.4   3.3   4.0
Yuanda China Holdings Ltd**                        Chik, Leon            OW     2789.HK      0.8    3.7   0.80    -4.8     672        0.6      0.11   0.13   55.1    12.1    5.9    5.2    0.9   0.8   15.3   16.0   7.5   8.4
Mkt Cap Weighted Aggregates                                                                                               83,104     251.8     1.0    1.1    15.1    11.2    9.9    8.8    1.2   1.1   13.3   13.4   2.3   2.4
Chemicals
China BlueChemical Ltd**                           Handa, Akhil          OW     3983.HK      5.1   -1.2   7.60    50.2     3,005      3.3      0.41   0.52   60.2    26.2    9.8    7.7    1.6   1.4   16.8   19.1   3.5   5.6
Mkt Cap Weighted Aggregates                                                                                                3,005      3.3      0.4    0.5    60.2    26.2    9.8    7.7    1.6   1.4   16.8   19.1   3.5   5.6
Consumer Goods
China Mengniu Dairy Co. Ltd.**                     Sener, Kurumlu Ebru   OW     2319.HK     26.6    1.0   24.00   -9.6     6,093     17.6      0.87   1.08   22.2    23.9    24.1   19.5   2.8   2.5   12.1   13.8   0.9   1.1
China Resources Enterprise                         Sener, Kurumlu Ebru   NR     0291.HK     25.8    6.0     -      -       7,984     15.5      1.38   1.53   -16.3   11.2    18.7   16.8   1.4   1.4   4.3    4.9    2.0   2.2
China Agri-Industries                              Chan, Ying-Jian       OW     0606.HK      3.9    2.4   5.40    40.3     2,603      6.3      0.35   0.42    21.9   21.2    11.1    9.2   0.7   0.7   6.6    7.5    2.3   2.7
Fufeng Group**                                     Chik, Leon            OW     0546.HK      2.8    0.4   3.70    30.7     762        1.4      0.30   0.41   23.1    37.4    7.4    5.4    1.0   0.8   13.3   16.3   0.0   0.0
Hengan International Group Ltd                     Sener, Kurumlu Ebru    N     1044.HK     88.7    3.4   73.00   -17.7   14,069     27.2      3.33   3.91   16.3    17.6    26.6   22.7   7.0   6.3   31.2   34.1   2.6    3.0
NVC Lighting Holdings Ltd*                         Chik, Leon            OW     2222.HK      2.6   -1.5    2.90    12.4    1,040      3.7      0.14   0.20   NM      45.4     2.5    1.7   0.3   0.2   11.6   15.2   8.1   11.8
Tibet 5100 Water Resources Holdings Ltd**          Sener, Kurumlu Ebru   NR     1115.HK      2.8    0.4     -       -      910        0.9      0.19   0.21   16.0    12.8    11.7   10.4   2.2   1.8   15.7   15.5   0.0   0.0


                                                                                                                                                                                                                                  19
Adrian Mowat                                          Asia Pacific Equity Research
(852) 2800-8599                                       31 May 2013
adrian.mowat@jpmorgan.com




Price as of                                                                                 Price          Target Price      Mkt       Avg. Daily          EPS          EPS Y/Y Growth         P/E                P/BV            ROE         Div. Yield
May 28, 2013                                    Analyst               Rec   RIC Ticker           D/D              Upside     Cap       Turnover     FY1E     FY2E       FY1E    FY2E     FY1E FY2E FY1E FY2E FY1E FY2E FY1E FY2E
Exchange rate = 6.12                                                                     (HKD)   (%)      (HKD)    (%)     (US$MM)     (US$MM)      (HKD)    (HKD)      (%)     (%)      (x)         (x)    (x)          (x)   (%)    (%)     (%)    (%)
Tingyi (Cayman Islands) Holding Corp*           Sener, Kurumlu Ebru   UW     0322.HK     20.5       2.2   14.20   -30.7     14,771        19.2      0.08         0.10   -6.7    25.2     34.8        27.8   41.0     36.3      15.9   17.9    1.1    1.4
Tsingtao Brewery - H**                          Sener, Kurumlu Ebru   UW     0168.HK     56.0       3.7   36.00   -35.7     9,151          9.5      1.49         1.74   14.4    17.0     29.7        25.3   4.2      3.7       15.1   15.5    0.7    0.8
Tsingtao Brewery - A                            Sener, Kurumlu Ebru   UW    600600.SS    38.9       1.4   29.00   -25.5     9,151         14.2      1.49         1.74   14.4    17.0     26.1        22.3   3.7      3.3       15.1   15.5    0.8    0.9
Uni-President China Holdings Ltd**              Sener, Kurumlu Ebru   N      0220.HK      8.6       1.2   8.00     -7.0     3,987         10.4      0.30         0.36   25.7    20.6     22.7        18.8   2.8      2.5       13.2   14.2    0.9    1.1
Want Want China Holdings Ltd*                   Sener, Kurumlu Ebru   N      0151.HK     11.8       0.7   9.50    -19.5     20,105        22.7      0.05         0.06   24.4    22.8     29.2        23.8   11.0     9.6       40.4   43.4    2.3    2.9
Mkt Cap Weighted Aggregates                                                                                                 90,624       148.5      1.1          1.2    11.1    17.3     26.7        22.2   11.5     10.2      21.8   23.6    1.7    2.0
Financial Services
Agricultural Bank of China - H**                Lei, Katherine        N      1288.HK      3.7       1.9   4.10     10.2    146,349        62.4      0.50         0.55   12.6    8.5      5.8         5.4    1.1      1.0       20.3   19.2    6.0    6.5
Bank of China - H**                             Lei, Katherine        N      3988.HK      3.8       2.2   4.00     6.1     135,790       159.7      0.52         0.55    3.2    7.3      5.8         5.4    0.9      0.8       16.5   15.9    6.1    6.5
Bank of China - A                               Lei, Katherine        N     601988.SS     3.0       1.0   3.20     7.4     135,790        16.8      0.52         0.55    3.2    7.3      5.8         5.4    0.9      0.8       16.5   15.9    6.1    6.5
Bank of Communications Co**                     Lei, Katherine         N     3328.HK      6.1       1.2   6.00     -1.6     58,287        25.6      0.85         0.90   -4.2     6.8     5.7         5.3    0.8      0.7       15.6   14.8    3.5    3.8
China Citic Bank - H Share**                    Lei, Katherine        UW     0998.HK      4.5       2.5   3.95    -11.8     31,781        26.6      0.67         0.75    1.6    11.9     5.2         4.7    0.7      0.7       15.0   14.9    4.8    5.3
China Construction Bank**                       Lei, Katherine        OW     0939.HK      6.4       1.4   7.70     20.1    206,114       204.2      0.84         0.95    8.8    12.8     6.0         5.3    1.2      1.0       20.7   20.3    5.8    6.6
China Merchants Bank – H**                      Lei, Katherine        N      3968.HK     16.3       1.2   17.90    9.5      47,940        38.7      2.16         2.29    2.8    6.2      6.0         5.6    1.2      1.0       21.5   19.7    5.0    5.3
China Merchants Bank Co., Ltd - A               Lei, Katherine         N    600036.SS    13.8       2.8   14.30    3.9      47,940       176.8      2.16         2.29    2.8    6.2      6.4         6.0    1.3      1.1       21.5   19.7    4.7    5.0
China Minsheng Banking - A                      Lei, Katherine        UW    600016.SS    10.7       2.8    7.80   -27.4     47,012       376.2      1.37         1.49    1.8    8.6      7.8         7.2    1.5      1.3       21.1   19.3    3.2    3.4
China Minsheng Banking – H**                    Lei, Katherine        UW     1988.HK      9.9       2.5   9.70     -2.2     47,012        61.2      1.37         1.49    1.8    8.6      5.7         5.3    1.1      0.9       21.1   19.3    4.3    4.7
CITIC Securities Co Ltd - A                     Klaczek, Josh A       N     600030.SS    13.3       3.0   11.50   -13.2     23,949       218.6       -            -       -      -        -           -     0.0      0.0       3.0      3.9    -      -
CITIC Securities Co Ltd - H**                   Klaczek, Josh A        N     6030.HK     17.5     2.7     14.00   -19.9     23,949        22.0      0.40         0.53   -67.2   31.6     34.0        25.9   1.8      1.7        5.2    6.6    1.1    1.5
Chongqing Rural Commercial Bank**               Lei, Katherine        UW     3618.HK      4.0    -1.5      3.90    -1.3      4,732        10.1      0.62         0.70    7.3    12.5      5.0         4.5   0.8      0.7       16.9   16.8    6.0    6.7
Haitong Securities - A                          Klaczek, Josh A       N     600837.SS    12.0       4.8   9.00    -25.1     18,108       207.8      0.35         0.38   -7.2    8.4      34.4        31.7   2.0      1.9       6.1      5.9   1.3    1.2
Haitong Securities - H**                        Klaczek, Josh A       OW     6837.HK     11.5       4.7   11.00    -4.7     18,108        21.3      0.35         0.38   -7.2    8.4      26.0        24.0   1.5      1.4       6.1      5.9   1.7    1.6
Industrial and Commercial Bank of China - H**   Lei, Katherine        OW     1398.HK      5.5       1.7   6.85     24.5    241,400       205.6      0.72         0.79    5.5    9.1      6.0         5.5    1.2      1.0       20.8   19.8    5.8    6.3
Industrial and Commercial Bank of China - A     Lei, Katherine        OW    601398.SS     4.2       1.5   5.50     31.3    241,400        36.4      0.72         0.79    5.5    9.1      5.8         5.3    1.1      1.0        0.2    0.2    6.0    6.6
Noah Holdings Ltd                               Klaczek, Josh A       OW      NOAH       12.4       3.4   9.50    -23.4      680          0.9       0.70         0.82   70.1    16.9     17.7        15.2   3.6      3.3       21.0   22.8     -      -
PICC group**                                    Kim, MW               NR     1339.HK      4.0       2.6   0.00    -100.0    21,858        26.7      0.19         0.25   16.4    34.4     17.0        12.6   2.2      1.9       15.6   16.4    0.6    0.9
Ping An Bank Co Ltd                             Kim, MW               NR    000001.SZ    21.6       5.8   0.00    -100.0    18,078       224.3      2.54         2.70   26.5    6.4      8.5         8.0     -       1.1       15.9   14.6    0.5    0.6
Mkt Cap Weighted Aggregates                                                                                                1,516,275    2,122.1     0.8          0.9     3.5    9.0      7.1         6.4    1.1      1.0       15.4   14.8    5.2    5.7
Healthcare
China Shineway Pharmaceutical Group Limited**   Wu, Sean              N      2877.HK     15.1       2.2   15.00    -0.4     1,604         2.0       0.91         1.05   16.3    15.8     13.0        11.3   2.2      1.9       17.7   18.1    2.3    2.7
China Medical System*                           Wu, Sean              OW     0867.HK      7.2    -0.1     8.80     21.9     2,246         3.6       0.05         0.06   31.6    26.6     20.1        15.8   4.4      3.7       23.2   25.4    2.0    2.5
Concord Medical Services Holdings Limited       Wu, Sean              OW      CCM         4.1       0.0    5.50    33.8      195           0.1      0.62         0.80   40.1    28.9      6.6         5.1   0.6      0.6        6.7    8.0    0.0    0.0
Fosun Pharmaceutical-A                          Wu, Sean              OW    600196.SS    12.2       1.3   14.00    15.0     4,408         33.5      0.80         0.91   -0.1    14.2     15.3        13.4   1.8      1.7       12.6   13.1    1.7    2.0
Fosun Pharmaceutical-H**                        Wu, Sean              OW     2196.HK     14.4    -1.2     17.00    18.4     4,408         4.9       0.80         0.91   -0.1    14.2     14.2        12.4   1.7      1.5       12.6   13.1    1.9    2.1
MicroPort Scientific Corp**                     Wu, Sean              N      0853.HK      6.2       1.0   5.20    -15.4     1,115         2.2       0.24         0.27   -4.1    10.9     20.2        18.2   2.7      2.4       13.6   13.6    1.3    1.4
Mindray Medical                                  Wu, Sean             OW       MR        41.2       0.4   39.00    -5.4     4,769         26.7      1.89         2.13   22.5    12.7     21.8        19.3   3.1      2.7       15.4   15.1    1.5    1.6
Shandong Weigao Group Medical Polymer Co. Ltd.** Wu, Sean             OW     1066.HK      8.7       8.3    9.50     8.7     5,039         10.3      0.22         0.25    2.0    10.6     31.0        28.0   3.5      3.2       11.7   11.9    1.0    1.1
Shanghai Pharmaceutical-A                       Wu, Sean              N     601607.CH    12.7       1.1   12.00    -5.3     5,478         31.1      0.81         0.90    6.5    10.6     15.6        14.1   1.2      1.1       7.7      8.1   1.6    1.8



20
Adrian Mowat                                            Asia Pacific Equity Research
(852) 2800-8599                                         31 May 2013
adrian.mowat@jpmorgan.com




Price as of                                                                                   Price          Target Price      Mkt     Avg. Daily          EPS          EPS Y/Y Growth         P/E                P/BV            ROE         Div. Yield
May 28, 2013                                      Analyst               Rec   RIC Ticker           D/D              Upside    Cap      Turnover     FY1E     FY2E       FY1E    FY2E     FY1E FY2E FY1E FY2E FY1E FY2E FY1E FY2E
Exchange rate = 6.12                                                                       (HKD)   (%)      (HKD)    (%)     (US$MM)   (US$MM)      (HKD)    (HKD)      (%)     (%)      (x)         (x)    (x)          (x)   (%)    (%)     (%)    (%)
Shanghai Pharmaceutical-H**                       Wu, Sean              N      2607.HK     15.2       1.6   15.00    -1.2     5,478       5.1       0.81         0.90    6.5    10.6     14.7        13.3   1.1      1.1       7.7      8.1   1.7    1.9
Sihuan Pharmaceutical Holdings**                  Wu, Sean              OW     0460.HK      4.8       2.1    4.50    -5.9     3,186        5.5      0.20         0.22   12.8    11.9     19.3        17.2   2.6      2.4       13.8   14.4    2.7    2.9
Sinopharm**                                       Wu, Sean              OW     1099.HK     21.7       3.3   31.00    43.2     7,162       17.0      1.01         1.27   23.4    25.4     16.8        13.4   2.2      2.0       13.6   15.4    1.7    2.2
Sino Biopharmaceutical                            Wu, Sean              OW     1177.HK      5.4       3.7   6.00     12.1     3,405       11.3      0.23         0.27   27.4    15.9     23.3        20.1   5.1      4.4       23.4   23.3    1.5    1.7
The United Laboratories**                         Wu, Sean              N      3933.HK      3.0       1.0   3.90     31.8      620        1.7       0.13         0.23   20.4    71.0     22.2        13.0   0.8      0.7       3.5      5.8   1.7    3.0
Mkt Cap Weighted Aggregates                                                                                                  49,112       155       0.7          0.9    12.5    15.3     18.8        16.3   2.4      2.2       13.2   13.8    1.7    1.9
Insurance
China Life Insurance - A                          Kim, MW               NR    601628.SS    16.9       2.2   0.00    -100.0   77,562       48.3      1.18         1.41   NM      19.0     14.3        12.0   1.9      1.7       14.2   15.1    1.8    2.4
China Life Insurance - H**                        Kim, MW               NR     2628.HK     21.1       1.2   0.00    -100.0   77,562      101.7      1.18         1.41   NM      19.0     14.0        11.8   1.9      1.7       14.2   15.1    1.8    2.4
China Pacific Insurance Group - A                 Kim, MW               NR    601601.SS    19.2       2.9   0.00    -100.0   29,625       64.0      0.65         1.20   -33.0   84.7     29.7        16.1   1.8      1.7       6.7    11.0    1.9    2.1
China Pacific Insurance Group - H**               Kim, MW               NR     2601.HK     27.6       2.2   0.00    -100.0   29,625       38.4      0.65         1.20   -33.0   84.7     33.6        18.2   2.1      1.9        6.7   11.0    1.7    1.8
New China Life Insurance Company Ltd - A          Kim, MW               NR    601336.SS    25.5       5.3   0.00    -100.0   12,373       36.0      1.52         1.96    61.9   28.4     16.7        13.0   2.0      1.7       12.4   14.1    0.6    0.8
New China Life Insurance Company Ltd - H**        Kim, MW               NR     1336.HK     27.8       2.6   0.00    -100.0   12,373       9.8       1.52         1.96   61.9    28.4     14.4        11.2   1.7      1.5       12.4   14.1    0.7    0.9
Ping An Insurance Group - A                       Kim, MW               NR    601318.SS    40.7       3.2   0.00    -100.0   56,047      213.9      3.92         4.32   54.9    10.1     10.4        9.4    1.8      1.6       18.4   17.8    1.1    1.4
Ping An Insurance Group - H**                     Kim, MW               NR     2318.HK     60.1       1.7   0.00    -100.0   56,047       97.0      3.92         4.32   54.9     10.1    12.1        11.0   2.1      1.8       18.4   17.8    1.0    1.2
PICC Property and Casualty**                      Kim, MW               NR     2328.HK      9.3       0.0   0.00    -100.0   15,182       23.2      0.79         0.71   15.2    -10.6     9.3        10.4   1.9      1.6       23.8   17.1    2.9    1.1
Mkt Cap Weighted Aggregates                                                                                                  366,397     632.5      1.9          2.3    63.3    17.0     16.0        12.2   1.9      1.7       14.6   15.3    1.5    1.8
Leisure Products & Leisure Time
Ajisen China Holdings Ltd                         Sener, Kurumlu Ebru   N      0538.HK      6.2    -1.8     5.60     -8.9      862        2.1       0.18         0.24   28.7    31.6     33.5        25.5   2.2      2.2       6.6      8.6   2.5    3.3
China Lodging Group Limited***                    Fong, Kenneth KC      OW      HTHT       15.9       0.6   22.00    38.3      968        1.8       3.30         3.77   13.5    14.4     29.5        25.8   2.2      2.0       7.7      8.2    -      -
Home Inns & Hotels Management Inc.***             Fong, Kenneth KC      OW      HMIN       29.1       2.1   36.00    23.7     1,319       7.8       7.07         8.71   NM      23.1     25.2        20.5   1.9      1.7       7.8      8.8    -      -
Mkt Cap Weighted Aggregates                                                                                                   3,149       12        4.0          4.9    NM      21.0     28.8        23.5   2.1      1.9       7.5      8.6   0.7    0.9
Machinery & Capital Goods
China High Speed Transmission**                   Kan, Boris            OW     0658.HK      4.3    -3.4     4.60     7.7       750        7.9       0.24         0.35   NM      46.2     14.2        9.7    0.6      0.6       4.2      5.8   0.0    0.0
China Rongsheng Heavy Industries Group Holdings
Ltd**                                             Mirchandani, Ajay     UW     1101.HK      1.4    -1.4     0.80    -42.0     1,244        3.4      0.07         0.05   -70.9   -32.1    15.2        22.4   0.5      0.5        3.3    2.2    2.0    1.3
CSR Corp Ltd.**                                   Li, Karen             OW     1766.HK      5.9     5.9     8.80     48.6    10,106       12.0      0.32         0.41    -2.8    30.0    14.7        11.3   1.6      1.4       15.3   15.3    1.4    1.8
Changsha Zoomlion Heavy Industry**                Li, Karen             UW     1157.HK      7.9       0.0   7.20     -9.1     8,933       20.0      0.90         0.87   -5.1    -3.8     6.9         7.2    1.0      0.9       16.0   13.7    3.4    3.3
Dongfang Electric Corporation Limited - A         Kan, Boris            UW    600875.SS    13.3       2.0   10.50   -21.1     4,181       24.3      1.25         1.29   -18.0    2.8     10.6        10.3   1.6      1.4       16.7   14.7    0.9    0.9
Dongfang Electric Corporation Limited - H**       Kan, Boris             N     1072.HK     12.9       1.6   12.90    -0.2     4,181       7.2       1.29         1.35   17.6     4.8     7.9         7.6    1.1      1.0       15.2   13.8    1.2    1.3
Harbin Electric Company Limited**                 Kan, Boris            OW     1133.HK      6.6       1.2    7.90    19.7     1,170       2.5       0.91         0.99    1.4     9.3     5.7         5.3    0.6      0.5        9.4    9.3    3.0    3.2
Haitian International Holdings**                  Chik, Leon            OW     1882.HK     13.3       0.0   13.00    -2.3     2,734       2.3       0.72         0.83   17.2    15.3     14.6        12.7   2.8      2.5       20.4   20.9    3.0    3.4
Johnson Electric Holdings*                        Chik, Leon            OW     0179.HK      5.2       0.6   6.10     17.5     2,394       1.6       0.05         0.06    2.3     5.9     12.5        11.8   1.4      1.3       11.6   11.5    2.1    2.3
Lonking Holdings Ltd**                            Li, Karen              N     3339.HK      1.9       7.3   3.50     83.2     1,053       7.1       0.38         0.40   -4.8     4.2     3.9         3.8    1.0      0.8       28.8   24.7    7.0    7.3
Shanghai Electric Group Company Limited**         Kan, Boris            UW     2727.HK      3.0       1.4   2.80     -5.1     7,502       6.6       0.27         0.29    7.2     4.9     8.5         8.1    0.9      0.8       11.3   10.6    3.5    3.7
SANY Heavy Equipment International Holdings
Company**                                         Deng, Chapman         N      0631.HK      3.1       5.8   5.00     61.3     1,226       2.8       0.30         0.35   19.6    19.1     8.2         6.9    1.2      1.1       16.1   16.8    2.2    2.6
Techtronic Industries                             Chik, Leon            OW     0669.HK     20.2       0.3   23.00    14.1     4,751       14.6      0.15         0.20   34.1    33.7     NM          98.8   20.9     18.0      17.2   19.9    0.2    0.2




                                                                                                                                                                                                                                                           21
Adrian Mowat                                             Asia Pacific Equity Research
(852) 2800-8599                                          31 May 2013
adrian.mowat@jpmorgan.com




Price as of                                                                                    Price          Target Price      Mkt     Avg. Daily          EPS          EPS Y/Y Growth         P/E                P/BV            ROE         Div. Yield
May 28, 2013                                       Analyst               Rec   RIC Ticker           D/D              Upside    Cap      Turnover     FY1E     FY2E       FY1E    FY2E     FY1E FY2E FY1E FY2E FY1E FY2E FY1E FY2E
Exchange rate = 6.12                                                                        (HKD)   (%)      (HKD)    (%)     (US$MM)   (US$MM)      (HKD)    (HKD)      (%)     (%)      (x)         (x)    (x)          (x)   (%)    (%)     (%)    (%)
Zhengzhou Coal Mining Machinery Group
Company**                                          Deng, Chapman         OW     0564.HK      7.6       1.3   14.10    86.3     2,175       0.9       0.99         1.16   16.1    17.6     6.0         5.1    1.1      1.0       21.8   19.9    5.0    5.9
Xinjiang Goldwind Science & Technology Co., Ltd.   Kan, Boris            N      2208.HK      6.1    -4.5     4.80    -21.8     2,815       3.7       0.14         0.21   NM      44.4     42.8        29.6   1.2      1.2       3.0      4.1   0.2    0.3
Mkt Cap Weighted Aggregates                                                                                                   55,216      116.9       0.6         0.6     0.7     8.0     11.0        18.0   3.0      2.6       14.6   14.0    2.2    2.4
Media & Entertainment
Bona Film Group Ltd.                               Wei, Dick             N       BONA        4.7    -1.5     5.50     17.5      278        0.1       0.10         0.33   NM      NM       45.5        14.3   1.4      1.3       6.0    12.1    0.0    0.0
Mkt Cap Weighted Aggregates                                                                                                     278        0.1        0.6         0.3    NM      -45.6    45.5        14.3   1.4      1.3       6.0    12.1    0.0    0.0
Metals & Mining
Maanshan Iron & Steel - A                          Kang, Daniel          UW    600808.SS     1.9       0.5   1.65    -14.9     2,320       3.1       -0.03        0.07   NM      NM       NM          26.3   0.7      0.6       -0.9     2.4   0.0    1.5
Maanshan Iron & Steel - H**                        Kang, Daniel          UW     0323.HK      1.9       2.7   1.70    -11.5     2,320       3.8       -0.03        0.07   NM      NM       NM          20.5   0.5      0.5       -0.9     2.4   0.0    2.0
Aluminum Corporation of China - H**                Kang, Daniel          N      2600.HK      3.1       1.3   3.10     0.6      8,075       7.9       -0.24        0.02   NM      NM       NM          98.3   0.8      0.8       -7.8     0.8   0.0    0.0
Aluminum Corporation of China - A                  Kang, Daniel          N     601600.SS     4.2       1.2   3.90     -6.3     8,075       12.2      -0.24        0.02   NM      NM       NM          NM     1.4      1.4       -7.8     0.8   0.0    0.0
China Hongqiao Group**                             Kang, Daniel          OW     1378.HK      4.5    -0.2     6.00     33.3     3,411        4.0      1.18         1.41   29.6    20.1     3.0         2.5    0.7      0.6       28.0   26.9    7.5    9.1
China Coal Energy - H**                            Kang, Daniel          OW     1898.HK      5.4     2.1     8.00     49.3    12,747       27.9      0.61         0.69   -9.1    13.1     7.0         6.2    0.6      0.6        9.0    9.5    4.3    4.9
China Coal Energy - A                              Kang, Daniel          OW    601898.SS     6.6       1.5   8.65     30.5    12,747       10.5      0.61         0.69   -9.1    13.1     10.9        9.7    1.0      0.9       9.0      9.5   2.7    3.1
China Shenhua Energy - H**                         Kang, Daniel          OW     1088.HK     26.4       1.2   35.00    32.8    67,677       68.9      2.37         2.51   -3.3     5.9     8.8         8.3    1.4      1.3       17.3   16.5    4.5    4.7
China Shenhua Energy - A                           Kang, Daniel          OW    601088.SS    20.8       0.8   26.50    27.2    67,677       44.1      2.37         2.51    -3.3    5.9      8.8        8.3    1.4      1.3       17.3   16.5    4.5    4.7
Baoshan Iron & Steel - A                           Kang, Daniel          OW    600019.SS     4.9       0.8    6.00    23.2    13,104       20.7      0.39         0.61   -34.2   55.8     12.5        8.0    0.7      0.7        6.0    8.9    3.6    5.6
Angang Steel - H**                                 Kang, Daniel          OW     0347.HK      4.6       1.1   6.00     31.9     4,001       7.8       0.23         0.23   NM      -0.3     15.7        15.8   0.5      0.5       3.5      3.4   3.2    3.2
Angang Steel - A                                   Kang, Daniel          OW    000898.SZ     3.4       0.6   4.30     28.4     4,001       7.3       0.23         0.23   NM      -0.3     14.7        14.7   0.5      0.5       3.5      3.4   3.4    3.4
Mongolian Mining Corporation*                      Kang, Daniel          N      0975.HK      2.1       1.0    4.50   118.4      983        1.1        0.02     0.04      NM      NM       15.2        7.3    1.2      1.0        8.1   15.1    1.6    3.4
SouthGobi Resources Ltd*                           Kang, Daniel          N      1878.HK     13.1       2.0   20.00    52.7      307        0.2       -0.14    -0.03      NM      NM       NM          NM     0.5      0.5       -4.0   -0.9    0.0    0.0
SouthGobi Resources Ltd. (SGQ CN)*****             Kang, Daniel          N      SGQ.TO       1.7       5.7   2.50     48.8      295        0.1       -0.14    -0.03      NM      NM       NM          NM     0.5      0.5       -4.0   -0.9    0.0    0.0
Yanzhou Coal Mining - H**                          Kang, Daniel          UW     1171.HK      8.2       1.4   8.00     -2.9     9,220       36.5      0.41         0.56   -67.6   37.3     15.9        11.6   0.7      0.7       4.4      5.9   1.9    2.6
Yanzhou Coal Mining - A                            Kang, Daniel          UW    600188.SS    14.8       2.7   13.90    -5.9     9,220       25.8      0.41         0.56   -67.6   37.3     36.1        26.3   1.6      1.5       4.4      5.9   0.8    1.1
Mkt Cap Weighted Aggregates                                                                                                   226,183     281.6       1.6         1.7    -4.3     9.2     9.7         12.5   1.2      1.1       12.1   12.6    3.6    4.1
Multi-Industry
China Cosco Holdings, Ltd.**                       Png, Corrine          NR     1919.HK      3.5       2.7     -       -       5,438       6.0       -0.18        0.20   NM      NM       NM          13.5   1.2      1.1       -7.7     8.4   0.0    0.0
China Merchants Holdings Int'l                     Li, Karen             UW     0144.HK     25.6       1.8   21.30   -16.8     8,217       9.4       1.47         1.73   -34.9   17.7     17.4        14.8   1.4      1.3       8.2      9.3   2.5    2.9
Kingboard Chemical                                 Chik, Leon            OW     0148.HK     17.2    -0.9     28.30    64.7     2,270       7.6       2.38         3.35   -19.8   40.7     7.2         5.1    0.5      0.4        7.2    9.4    2.9    4.7
Kingboard Laminates                                Chik, Leon             N     1888.HK      3.3     1.2      4.00    21.2     1,275       1.1       0.44         0.49    14.5    9.6     7.4         6.8    0.8      0.7       10.9   11.1    4.0    4.4
Mkt Cap Weighted Aggregates                                                                                                   17,199       24.2       1.0         1.4    -17.5   38.0     9.8         12.5   1.2      1.1       3.3      9.2   1.9    2.4
Oil & Gas
China Oilfield Services Limited**                  Handa, Akhil          N      2883.HK     16.7       1.8   15.00   -10.1    11,582       13.1      1.04         1.19   16.1    14.3     12.6        11.0   1.8      1.6       15.6   15.6    1.6    1.8
CNOOC**                                            Lee, Samuel See Wai   NR     0883.HK     14.2       1.7    0.00   -100.0   81,544      113.7      1.37         1.16   -13.0   -15.1     8.2         9.6   1.6      1.4       21.4   15.8    2.4    2.6
China Resources Gas Group Limited                  Kan, Boris             N     1193.HK     20.5       4.8   22.60    10.5     5,858       13.4      0.89         1.15    20.3    28.7    22.9        17.8   3.4      2.9       15.7   17.7    0.6    0.8
MIE Holdings Corporation**                         Handa, Akhil          OW     1555.HK      1.9    -0.5     4.00    107.3      658        1.8       0.29         0.32   78.9    12.5     5.3         4.7    1.5      1.1       32.2   27.0    0.0    0.0
Sinopec Corp - H**                                 Lee, Samuel See Wai   NR     0386.HK      8.3       1.5   0.00    -100.0   98,810       98.4      0.72         0.87   -14.2   19.5     9.0         7.6    1.1      1.0       12.7   13.8    3.3    4.0



22
Adrian Mowat                                Asia Pacific Equity Research
(852) 2800-8599                             31 May 2013
adrian.mowat@jpmorgan.com




Price as of                                                                         Price          Target Price      Mkt     Avg. Daily          EPS          EPS Y/Y Growth         P/E                P/BV             ROE         Div. Yield
May 28, 2013                          Analyst                 Rec   RIC Ticker           D/D              Upside    Cap      Turnover     FY1E     FY2E       FY1E    FY2E     FY1E FY2E FY1E FY2E FY1E FY2E FY1E FY2E
Exchange rate = 6.12                                                             (HKD)   (%)      (HKD)    (%)     (US$MM)   (US$MM)      (HKD)    (HKD)      (%)     (%)      (x)         (x)    (x)          (x)   (%)     (%)     (%)    (%)
Mkt Cap Weighted Aggregates                                                                                        198,452     240.3       1.0         1.0    -11.4    0.2     9.3         8.9    1.4      1.3       16.6    14.9    2.8    3.2
Real Estate
Agile Property Holdings Ltd**         Li, Ryan                OW     3383.HK      9.6       2.1   13.10    36.7     4,254       13.4      1.40         1.59    4.4    13.1     5.4         4.8    0.9      0.8       17.6    17.4    4.7    5.3
C C Land                              Li, Ryan                N      1224.HK      2.4       2.1   2.15    -11.5      810        0.9       0.22         0.34   10.7    52.3     11.0        7.2    0.5      0.4        4.3      6.2   2.5    2.9
China Overseas Land & Investment      Kwong, Lucia Yuen Kei   N      0688.HK     23.8       2.4   23.00    -3.2    25,001       60.9      2.29         2.64   18.5    15.2     10.4        9.0    1.9      1.6       19.8    19.5    2.1    2.5
China Resources Land                  Kwong, Lucia Yuen Kei   OW     1109.HK     24.0       3.2   23.50    -2.1    18,019       27.9      1.53         2.23   22.5    46.2     15.7        10.7   1.6      1.4       11.6    14.1    1.7    2.5
China Vanke**                         Kwong, Lucia Yuen Kei   OW    200002.SZ    16.1       0.7   18.50    14.6    22,280        4.8      1.35         1.46   18.0     8.5      9.5         8.7   1.8      1.5       21.0    19.0    1.6    1.7
Country Garden Holdings**             Li, Ryan                OW     2007.HK      4.5       3.2   4.75     4.9     10,637       12.6      0.42         0.47   11.3    11.5     8.4         7.6    1.5      1.3       19.2    18.8    4.4    4.8
Evergrande Real Estate**              Li, Ryan                OW     3333.HK      3.2       1.6   4.25     32.0     6,647       28.6      0.49         0.53   -20.6    8.1     5.2         4.8    0.8      0.7       17.6    15.6    0.0    7.2
Franshion Properties (China) Ltd.     Kwong, Lucia Yuen Kei    N     0817.HK      2.8    -0.7     2.75     -3.2     3,351       1.7       0.32         0.33    37.5   3.2      8.8         8.5    0.8      0.8        9.8      9.6   3.0    3.9
Glorious Property**                   Kwong, Lucia Yuen Kei   UW     0845.HK      1.2     3.4     1.00    -18.7     1,235       0.7       0.18         0.18   -21.8   -1.3     5.4         5.5    0.4      0.4        8.0      7.4   0.0    0.0
Guangzhou R&F Properties**            Li, Ryan                OW     2777.HK     14.2       2.6   15.20    7.0      5,894       11.8      1.74         1.95    1.9    12.1     6.4         5.7    1.2      1.1       19.9    19.7    5.7    6.4
Longfor Properties Co. Ltd.**         Li, Ryan                N      0960.HK     13.6       1.3   13.00    -4.3     9,500       12.9      1.15         1.17   -4.0     2.6     9.4         9.1    1.7      1.4       19.3    17.1    2.1    2.2
KWG Property Holding Ltd.**           Li, Ryan                OW     1813.HK      5.3       1.9   6.00     14.1     1,960       4.9       0.80         0.94   20.1    17.3     5.2         4.4    0.7      0.6       14.2    14.0    4.3    5.1
Shimao Property Holdings**            Kwong, Lucia Yuen Kei   OW     0813.HK     16.9       3.8   17.00    0.5      7,568       18.3      1.70         2.15   26.6    26.5      7.9         6.2   1.2      1.1       16.2    18.5    3.9    4.8
Shui On Land Ltd**                    Kwong, Lucia Yuen Kei    N     0272.HK      2.8       1.1    2.75    0.0      2,834        6.6      0.17         0.18   NM       7.7     13.0        12.1   0.5      0.5        3.0     3.1    2.1    2.1
Mkt Cap Weighted Aggregates                                                                                        119,990     206.0       1.4         1.6    15.1    18.6     9.8         8.3    1.5      1.3       17.3    17.0    2.5    3.3
Retailing
Baoxin Auto Group Limited**           Lai, Nick YC            OW     1293.HK      6.0    -0.5     8.50     42.4     1,966       5.0       0.30         0.52    9.4    73.7     15.6        9.0    3.0      2.4       20.7    30.4    0.0    0.0
Belle International Holdings Ltd.**   Sener, Kurumlu Ebru      N     1880.HK     12.3     4.8     11.20    -9.1    13,384       52.9      0.57         0.65   10.2    15.0     17.1        14.9   3.2      2.8       20.0    20.3    2.3    2.7
Dah Chong Hong**                      Chik, Leon              UW     1828.HK      7.1    -1.7      6.00   -15.7     1,679        2.9      0.56         0.70   -2.0    24.5     10.0         8.0   1.4      1.3       10.6    12.4    2.9    3.7
Daphne International                  Li, Shen Wei            N      0210.HK      7.1       1.1   9.30     31.9     1,498       5.2       0.61         0.75    4.7    23.0     11.6        9.4    2.0      1.8       18.6    20.0    3.1    3.8
Golden Eagle Retail Group Ltd**       Sener, Kurumlu Ebru     OW     3308.HK     12.7    -0.8     16.00    26.2     3,073       10.8      0.66         0.76    5.6    14.5     15.1        13.2   3.3      2.9       22.9    23.3    3.3    3.8
Li Ning Co Ltd**                      Li, Shen Wei            UW     2331.HK      4.4    -1.6     2.20    -50.3      707        3.1       -0.25    -0.01      NM      NM       NM          NM     1.9      1.9       -15.6   -0.6    0.0    0.0
New World Department Stores Ltd       Sener, Kurumlu Ebru     NR     0825.HK      4.2    -0.5       -       -        921        0.6        0.35     0.45      5.1     28.2     12.0        9.4    1.5      1.4        13.0   15.5    4.2    5.3
Parkson Retail Group Ltd**            Sener, Kurumlu Ebru     UW     3368.HK      3.6    -0.3     3.60     -1.1     1,318       3.0       0.29         0.31   -5.0     8.7     10.0        9.2    1.3      1.3       14.0    14.2    5.0    5.5
Ports Design**                        Li, Shen Wei            UW     0589.HK      6.4       0.5   4.10    -35.9      457        1.0       0.62         0.67   -0.1     6.7     8.1         7.6    1.4      1.3       18.1    17.8    7.3    7.9
Zhongsheng Group Holdings**           Lai, Nick YC            UW     0881.HK     10.5       5.9   7.50    -28.4     2,576       3.3       0.39         0.65   -47.1   64.2     21.0        12.8   1.7      1.5        8.6    12.5    1.6    0.8
Mkt Cap Weighted Aggregates                                                                                        27,579       88.0       0.5         0.6     8.1    23.6     15.3        12.4   2.7      2.4       17.2    19.1    2.5    2.8
Technology - Hardware
21Vianet Group Inc.***                Sullivan, James         N       VNET        9.3       0.2   11.00    17.9      540        2.6       1.03         0.53   NM      -49.1    7.1         14.0   0.1      0.1        7.1      7.0    -      -
BYD**                                 Kwock, Alvin YL         UW     1211.HK     33.4       5.9   42.00    25.7    12,248       15.7      1.42         1.78   -17.7   25.2     18.6        14.8   3.2      2.8       18.4    20.1    1.1    1.3
BYD Electronic International**        Zhang, Qin              OW     0285.HK      4.6       1.3    6.60    42.9     1,341       5.5       0.32         0.47   90.2    45.5     11.4        7.8    0.9      0.8        8.4    11.3    1.8    2.6
Digital China                         Zhang, Qin               N     0861.HK     11.1       1.7   13.00    17.3     1,561       5.7       1.27         1.40   11.5    10.1      8.7        7.9    1.6      1.4       19.6    19.4    4.0    4.4
GCL Poly Energy                       Hsu, Rick               UW     3800.HK      1.9       1.1   1.70    -11.0     3,808       32.0      -0.15    -0.02      NM      NM       NM          NM     1.5      1.5       -11.1   -1.9    0.0    0.0
Lenovo Group Limited*                 Hariharan, Gokul        OW     0992.HK      7.8    -0.3     9.00     15.5    10,476       59.3      0.05         0.08   14.0    41.8     18.9        13.3   4.4      3.5       23.8    32.5    2.6    3.0
Skyworth Digital Holdings             Chik, Leon              OW     0751.HK      5.5       7.5   9.00     64.5     1,975       15.7      0.63         0.79   40.7    25.4      8.7         6.9   1.5      1.4       18.8    20.8    3.6    4.5
SMIC*                                 Hsu, Rick               NR     0981.HK      0.7       1.4   0.00    -100.0    2,972       11.9      0.00         0.01   NM      64.5     23.0        14.0   1.2      1.1        5.0     7.5    0.0    0.0



                                                                                                                                                                                                                                                  23
Adrian Mowat                                    Asia Pacific Equity Research
(852) 2800-8599                                 31 May 2013
adrian.mowat@jpmorgan.com




Price as of                                                                           Price          Target Price       Mkt     Avg. Daily          EPS          EPS Y/Y Growth         P/E                P/BV             ROE         Div. Yield
May 28, 2013                              Analyst               Rec   RIC Ticker           D/D               Upside    Cap      Turnover     FY1E     FY2E       FY1E    FY2E     FY1E FY2E FY1E FY2E FY1E FY2E FY1E FY2E
Exchange rate = 6.12                                                               (HKD)   (%)      (HKD)     (%)     (US$MM)   (US$MM)      (HKD)    (HKD)      (%)     (%)      (x)         (x)    (x)          (x)   (%)     (%)     (%)    (%)
Spreadtrum Communications                 Zhang, Qin            N       SPRD       18.5       0.8   20.00     8.3       894       125.7      2.17         2.39   21.2    10.3     8.5         7.7    1.9      1.6       32.5    28.9    1.9    2.1
TCL Communication Technology              Hsu, Andrew Tak Jun   OW     2618.HK      4.1       0.2    5.50     33.5      602        2.7       0.28         0.52   NM      87.5     14.8        7.9    1.7      1.5       12.5    21.0    2.3    4.3
TCL Multimedia                            Hsu, Andrew Tak Jun   OW     1070.HK      6.6       6.5    7.50     13.8     1,129       4.7       0.76         0.94   8.5     23.7      8.7        7.0    1.6      1.3       23.0    24.3    4.1    4.3
VTech Holdings*                           Chik, Leon            UW     0303.HK     120.4      0.9   90.00    -25.2     3,886       6.0       0.83         0.84    3.8     1.4     18.6        18.4   6.6      6.5       36.2    36.0    5.1    5.2
ZTE Corp**                                Zhang, Qin            N      0763.HK     13.0       3.5   15.00     15.6     6,718       11.8      0.61         0.77   NM      26.7     16.8        13.3   1.5      1.3        9.0    10.5    1.5    1.9
Mkt Cap Weighted Aggregates                                                                                           48,150      299.3       0.7         0.8    24.6    22.8     15.7        12.2   2.9      2.6       16.5    20.1    2.0    2.3
Technology - Software & IT Services
AirMedia                                  Wei, Dick             N       AMCN        1.9    -0.5      3.50     86.2      115        0.1       -0.54    -0.25      NM      NM       NM          NM     1.1      1.2       -11.8   -4.6    0.0    0.0
Baidu.com                                 Wei, Dick             OW      BIDU       96.9       0.5   115.00    18.6    33,901      367.2      5.22         6.82    9.7    30.7     18.6        14.2   5.6      4.0       36.5    32.9     -      -
Dangdang                                  Wei, Dick             N       DANG        6.4       4.0    4.30    -32.3      509        6.1       -0.88    -0.67      NM      NM       NM          NM     4.3      6.9       -45.6   -53.7   0.0    0.0
Focus Media                               Wei, Dick             NR      FMCN       27.4      -        -        -       3,545       38.2      1.94         2.33   34.7    20.3     14.1        11.8   2.4      2.0       23.4    22.9    1.4    2.4
iSoftstone                                Wei, Dick             OW       ISS        4.4    -2.5     15.00    244.0      248         0.4      0.38         0.58   19.3    51.9     11.5         7.6   0.7      0.7        7.0     9.5    0.0    0.0
NetEase                                   Wei, Dick             OW      NTES       63.4       2.2   65.00     2.5      8,289       26.0      4.63         4.97    6.7     7.3     13.7        12.8   2.7      2.2       22.7    19.9    0.0    0.0
Sina Corp                                 Wei, Dick             OW      SINA       58.9       1.3   67.00     13.8     3,925      123.8      0.21         0.11   NM      -46.8    NM          NM     3.2      3.4        3.9      3.1   0.0    0.0
Shanda Games***                           Wei, Dick              N      GAME        3.6       0.3    3.70     2.8       974         9.4      0.64         0.59    -8.4   -7.8     34.6        37.6   9.4      5.0       30.7    19.3    0.0    0.0
Sohu.Com***                               Wei, Dick             OW      SOHU       66.0       2.9   56.00    -15.1     2,522       39.6      2.00         2.38   -48.5   18.9     33.0        27.8   1.9      1.8        7.4     7.7    0.0    0.0
Tencent**                                 Wei, Dick             OW     0700.HK     304.2      1.3   300.00    -1.4    72,545      180.2      7.58         9.71   10.9    28.0     31.6        24.7   8.2      6.1       30.1    28.9    0.3    0.4
Mkt Cap Weighted Aggregates                                                                                           126,573      791        6.1         7.8    13.1    27.4     25.3        20.0   6.7      5.0       29.5    27.5    0.2    0.3
Transportation
Beijing Capital International Airport**   Li, Karen             OW     0694.HK      5.5       1.7    8.00     45.7     3,063       4.7       0.33         0.41    23.4   23.1     13.0        10.5   1.2      1.1        9.2    10.7    3.1    3.8
China Shipping Container Lines**          Png, Corrine          OW     2866.HK      2.0       3.6    2.60     28.7     3,917       9.1       0.01         0.04   -80.6   NM       NM          38.9   0.7      0.7        0.4     1.8    0.0    0.0
Mkt Cap Weighted Aggregates                                                                                            6,980       13.8       0.2         0.2     5.2    34.3     5.7         26.5   0.9      0.9        4.3      5.7   1.4    1.7
Telecom Services
China United Network Communications       Liu, Lucy Yajun       N     600050.SS     3.9       1.6    7.00     81.8    13,331       50.5      0.10         0.15   38.8    57.9     39.6        25.1   1.2      1.1        1.0      1.6   0.9    1.4
China Unicom (Hong Kong) Limited**        Liu, Lucy Yajun       OW     0762.HK     11.1       0.4   15.60     40.3    33,785       41.8      0.28         0.43   58.5    52.2     31.0        20.3   1.0      1.0        3.2     4.7    1.6    2.5
China Mobile Limited**                    Liu, Lucy Yajun       UW     0941.HK     83.6       0.6   78.00     -6.7    216,446     159.4      6.22         5.67   -3.4    -8.8     10.6        11.6   1.7      1.5       16.4    13.7    4.1    3.9
China Telecom Corporation Limited**       Liu, Lucy Yajun       N      0728.HK      3.9       0.3    4.50     14.8    40,864       27.1      0.23         0.26   22.1    13.8     13.7        12.1   1.0      1.0        7.1      8.5   2.4    2.4
Mkt Cap Weighted Aggregates                                                                                           304,426     278.8       4.5         4.1    -3.0    -8.2     14.6        13.2   1.5      1.4       13.0    11.5    3.4    3.4
Utilities
Anhui Expressway**                        Deng, Chapman         OW     0995.HK      4.1    -0.5      5.80     42.5     1,033       0.8       0.45         0.38   -12.4   -15.1     7.2         8.4   0.8      0.7       11.3     9.0    5.7    4.9
Beijing Enterprises Water                 Wu, Elaine            OW     0371.HK      2.9     1.7      3.00      2.7     2,891       7.3       0.14         0.17    25.8    22.2    21.4        17.5   2.4      2.2       11.7    13.4    1.6    2.0
Cheung Kong Infrastructure                Wu, Elaine            OW     1038.HK     57.2       1.4   56.00     -2.0    18,372       13.5      4.08         4.24   20.7     4.0     14.0        13.5   2.5      2.6       18.4    19.1    3.1    3.2
China Everbright International            Wu, Elaine            OW     0257.HK      6.3    -0.2      5.30    -16.1     3,300       12.2      0.27         0.36   -10.3   35.2     23.7        17.6   2.8      2.5       12.4    14.8    0.9    1.1
China Longyuan Power Group Corp.**        Kan, Boris            OW     0916.HK      8.2       0.7    8.60     4.6      8,569       19.3      0.39         0.51   13.2    30.2     16.5        12.7   1.6      1.5       10.3    12.2    1.2    1.6
China Gas Holdings Limited                Kan, Boris             N     0384.HK      8.0       6.1    2.60    -67.3     4,688        9.6      0.26         0.28   19.5     8.8     30.6        28.1   3.2      2.9       11.0    10.7    0.0    0.0
China Resources Power Holdings            Kan, Boris            N      0836.HK     20.5       3.7   23.30     14.0    12,583       28.1      2.06         2.25   29.6     9.1     9.9         9.1    1.6      1.4       17.1    16.6    3.2    3.5
Datang International**                    Wu, Elaine            N      0991.HK      3.4       1.8    3.30     -2.3     9,137       8.7       0.30         0.34   92.9    15.1     9.0         7.8    0.9      0.8        9.8    10.7    4.5    5.1
Hollysys Automation Technologies Ltd.     Deng, Chapman         OW      HOLI       11.5    -0.1     14.60     27.1      643        13.1      1.04         1.22    3.5    17.9     11.1        9.4    1.9      1.6       16.0    16.2    0.0    0.0


24
Adrian Mowat                                           Asia Pacific Equity Research
(852) 2800-8599                                        31 May 2013
adrian.mowat@jpmorgan.com




Price as of                                                                                     Price          Target Price      Mkt       Avg. Daily          EPS          EPS Y/Y Growth         P/E                P/BV            ROE         Div. Yield
May 28, 2013                                     Analyst                 Rec    RIC Ticker           D/D              Upside     Cap       Turnover     FY1E     FY2E       FY1E    FY2E     FY1E FY2E FY1E FY2E FY1E FY2E FY1E FY2E
Exchange rate = 6.12                                                                         (HKD)   (%)      (HKD)    (%)     (US$MM)     (US$MM)      (HKD)    (HKD)      (%)     (%)      (x)         (x)    (x)          (x)   (%)    (%)     (%)    (%)
Huadian Power International - H**                Wu, Elaine               N      1071.HK      3.9       4.9   3.40    -12.7     4,618         7.4       0.18         0.31   NM      76.1     17.3        9.8    1.2      1.1       7.5    11.5    0.0    0.0
Huaneng Power Int'l - A                          Kan, Boris              UW     600011.SS     6.5       1.2   5.40    -17.3     15,020        27.9      0.45         0.58   NM      27.6     14.4        11.3   1.7      1.6       12.1   14.5    3.6    4.5
Huaneng Power Int'l - H**                        Kan, Boris              UW      0902.HK      8.3       2.8   6.70    -19.7     15,020        25.9      0.59         0.62   51.4     5.0     11.1        10.5   1.5      1.4       14.3   14.1    4.6    4.9
Jiangsu Expressway - H**                         Deng, Chapman            N      0177.HK      9.1       0.6   9.00     -1.3     5,175         4.1       0.50         0.50    7.0     1.8     14.5        14.3   1.9      1.8       13.2   13.0    5.4    5.5
Towngas China Company Limited                    Kan, Boris              OW      1083.HK      8.0    -0.6     5.95    -25.7     2,691         4.6       0.36         0.43   23.4    20.2     22.4        18.6   1.7      1.6       8.1      8.9   0.0    0.0
Shenzhen Expressway - H**                        Deng, Chapman           OW      0548.HK      3.0    -1.0     4.00     32.5     1,054         1.1       0.33         0.29   -17.2   -11.3    7.2          8.1   0.5      0.5       7.7      6.6   6.7    5.9
Shenzhen Expressway - A**                        Deng, Chapman            N     600548.SS     3.3     0.6     3.23     -1.0     1,054         0.8       0.33         0.29   -17.2   -11.3    9.8         11.1   0.7      0.7       7.7      6.6   4.9    4.3
Sichuan Expressway**                             Deng, Chapman           OW      0107.HK      2.5       0.4   3.70     49.8     1,408         1.1       0.41         0.39    7.3    -6.2     4.7         5.0    0.5      0.5       11.8   10.1    4.5    4.2
Sound Global Limited****                         Wu, Elaine               N      SOGL.SI      0.6       1.7   0.65     7.4       616          1.1       0.36         0.40    8.1    12.2     8.2         7.3    1.2      1.0       16.1   15.4    0.0    0.0
ENN Energy Holdings Limited                      Kan, Boris              OW      2688.HK     43.0     2.1     40.00    -6.9     5,991         14.8      1.88         2.30    35.5   22.2     18.0        14.7   3.5      2.9       21.2   21.8    1.4    1.7
Yuexiu Transport Infrastructure Limited**        Deng, Chapman           OW      1052.HK      4.3    -0.9      4.80    12.1      922           0.5      0.28         0.38   -16.2   35.0     12.1         8.9   0.7      0.7        5.8    7.7    5.0    6.7
Zhejiang Expressway**                            Deng, Chapman           OW      0576.HK      6.6       1.5   7.20     8.9      3,698         4.3       0.39         0.38    1.7    -2.6     13.2        13.6   1.4      1.4       12.1   11.3    5.8    5.8
Mkt Cap Weighted Aggregates                                                                                                    118,485       206.2      1.2          1.3    29.6     9.0     14.3        12.4   1.9      1.7       13.7   14.4    3.1    3.4
JPM Country Average                                                                                                            3,427,888    6,025.8     1.6          1.7     8.8     8.9     11.2        10.0   1.9      1.6       15.6   15.3    3.6    4.0
Source: Bloomberg, J.P. Morgan estimates. *Price Currency=HKD & Reporting Currency=USD **Price Currency=HKD & Reporting Currency=CNY ***Price Currency=USD & Reporting Currency=CNY ****Price Currency=SGD & Reporting Currency=CNY *****Price
Currency=SGD & Reporting Currency=CNY




                                                                                                                                                                                                                                                               25
Adrian Mowat                Asia Pacific Equity Research
(852) 2800-8599             31 May 2013
adrian.mowat@jpmorgan.com




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26
Adrian Mowat                Asia Pacific Equity Research
(852) 2800-8599             31 May 2013
adrian.mowat@jpmorgan.com




                            Appendix




                                                           Appendix




                                                                  27
                                                                                                                  Emerging Markets
                                                                                                                  Equity Research
                                                                                                                  31 May 2011




China 2020: 130 million swing                                                                                              EM 101
How demographics change the economy


 The number of graduates in China has increased by 74 million in                                                 Emerging Markets Equity Strategy
  past decade (2010 Census). The tertiary enrolment ratio is now 35%.                                             Adrian Mowat
                                                                                                                                       AC

  This combined with a 2% decline in the working age population leads to                                          (852) 2800-8599
  a 91 million fall in non-graduates in the workforce; it grew by 28                                              adrian.mowat@jpmorgan.com
  million in 2000-2010. We believe that this is the most important driver                                         J.P. Morgan Securities (Asia Pacific) Limited
  of reduce fixed asset investment. It reverses the commonly held belief                                          Ben Laidler
  that China must have growth above 8% to generate sufficient jobs.                                               (1-212) 622-5252
  Continuing the current investment-driven model will be inflationary.                                            ben.m.laidler@jpmorgan.com
                                                                                                                  J.P. Morgan Securities LLC
 China’s official GDP growth target and inflation rate for this decade
                                                                                                                  David Aserkoff, CFA
  are 7% and 4%, respectively. Considering a 10.5% GDP CAGR in                                                    (44-20) 7325-1775
  2000-2010 with just 2% inflation, this lower target appears conservative.                                       david.aserkoff@jpmorgan.com
  To achieve the 7% target China requires circa10% labor productivity. It                                         J.P. Morgan Securities Ltd.
  is investment in human capital that makes this high level of                                                    Rajiv Batra
  productivity possible, as higher-paying service sector jobs replace                                             (91-22) 6157-3568
  lower-paid construction and manufacturing jobs. The challenge is                                                rajiv.j.batra@jpmorgan.com
  creating jobs for graduates.                                                                                    J.P. Morgan India Private Limited

                                                                                                                  Faheem S Desai
 If we assume a return to the consumption/investment ratio in 2000 and
                                                                                                                  (91-22) 6157-3329
  7% GDP growth, the consumption CAGR accelerates from 8.5% to                                                    faheem.s.desai@jpmorgan.com
  8.9%. Fixed investment CAGR falls from 12.7% to 4.8% (see page                                                  J.P. Morgan India Private Limited
  37). Commodity bulls take note. The 12th Five-Year Plan aims to
                                                                                                                  Ravi Saraogi
  rebalance. But it is China’s 1979 one-child policy that is driving                                              (91-22) 6157-3305
  economic change today.                                                                                          ravi.saraogi@jpmorgan.com

                                                                                                                  J.P. Morgan India Private Limited



Figure 36: Demographics should reverse this trend                            Figure 37: China needs jobs for graduates, not in pouring
                                                                             concrete or manufacturing: Change in the non-graduate available
  800%                                                          748%         workforce 15-39 years old
  700%                          GDP
                                Government
                                                                             %oya, Millions
  600%                                                          512%
                                Profits                                         3%                                                                            600
  500%
                                Income                                          2%                                       %oya            Number
  400%                                                          343%                                                                                          500
                                                                                1%
  300%
                                                                                0%                                                                            400
  200%                                                         258%
                                                                               -1%
  100%                                                                                                                                                        300
                                                                               -2%
    0%
                                                                               -3%                                                                            200
            2000 2001 2002 2003 2004 2005 2006 2007 2008 2009                  -4%
                                                                                                                                                              100
                                                                               -5%
Source: CEIC.
Note: Household income lagging profits and GDP growth                          -6%                                                                            0
                                                                                     1990
                                                                                     1993
                                                                                     1996
                                                                                     1999
                                                                                     2002
                                                                                     2005
                                                                                     2008
                                                                                     2011
                                                                                     2014
                                                                                     2017
                                                                                     2020
                                                                                     2023
                                                                                     2026
                                                                                     2029
                                                                                     2032
                                                                                     2035
                                                                                     2038
                                                                                     2041
                                                                                     2044
                                                                                     2047




                                                                             Source: PRC NBS, Ministry of Education PRC, US Census, J.P. Morgan calculation




See page 98 for analyst certification and important disclosures, including non-US analyst disclosures.
J.P. Morgan does and seeks to do business with companies covered in its research reports. As a result, investors should be aware that the
firm may have a conflict of interest that could affect the objectivity of this report. Investors should consider this report as only a single factor in
making their investment decision.
Adrian Mowat                        Emerging Markets Equity Research
(852) 2800-8599                     31 May 2011
adrian.mowat@jpmorgan.com



EM 101 Series
EM 101 key briefing notes for
                                    Table of Contents
emerging market equity              Figure 1: Demographics should reverse this trend ..................................................28
investors.                          Figure 2: China needs jobs for graduates, not in pouring concrete or
                                    manufacturing: Change in the non-graduate available workforce 15-39 years old ...28
                                    Figure 4: Change in the non-graduate available workforce 15-39 years old.............85
                                    Figure 5: And reverse this trend.............................................................................30
For more on this subject from
J.P. Morgan’s economics team        Figure 6: Real GDP growth (2000=100) ................................................................31
please see:                         Figure 7: Contribution to China’s real GDP growth................................................31
China’s consumption uptrend         Figure 8: Growth in per capita GDP & average national wages (%)........................31
and role of labor market, 30 July   Figure 9: From consumption to investment ............................................................32
2010, Grace Ng et al
                                    Figure 10: Household income lagging profits and GDP growth ..............................32
China’s export sector copes with    Figure 11: More 19 years old in Tertiary Education - Less for construction,
rising wages, 4 March 2011,
                                    manufacturing and agriculture ...............................................................................36
Grace Ng et al (See page 40)
                                    Figure 12: Change and absolute number of 19 year old non-graduates....................36
Riding on the coattails of
China’s rising labor cost, 25
                                    Figure 13: Change in the non-graduate available workforce 15-39 years old...........36
March 2011, Sin Beng Ong et al      Figure 14: Tertiary enrollment ratio as a percentage of 19 years old .......................36
                                    Figure 15: China labor productivity growth (%).....................................................37
                                    Figure 16: China export price index (%oya, nsa)....................................................37
                                    Figure 17: China FAI breakdown...........................................................................38
                                    Figure 18: China ICOR .........................................................................................39
                                    Figure 19: China export prices and US import prices from China ...........................40
                                    Figure 20: Export price trends - China, Korea and Taiwan .....................................40
                                    Figure 21: Manufacturing wages relative to industry output ...................................40
                                    Figure 22: Share of US import market ...................................................................41
                                    Figure 23: Industrial enterprise profit margin .........................................................41
                                    Figure 24: China exports by region ........................................................................41
                                    Figure 25: Lessons from other countries - Real GDP growth (5-year centered
                                    moving average %) vs. adjusted per capita GDP (US$) ..........................................43
                                    Figure 26: Real GDP growth %oya (5-year centered moving average) over time ....44
                                    Figure 27: Relative growth and wealth of provinces in China .................................45
                                    Figure 28: Real GDP growth vs. Average CPI in the previous decades ...................46
                                    Figure 29: Intensity of cement use; per-capita consumption of cement (tonnes) vs.
                                    adjusted per-capita nominal GDP...........................................................................47
                                    Figure 30: Intensity of steel use; per-capita consumption of steel (lbs) vs.
                                    adjusted per-capita nominal GDP...........................................................................48
                                    Figure 31: Per-capita consumption of oil (barrels per day per 1000 population) vs.
                                    adjusted per-capita nominal GDP...........................................................................49
                                    Figure 32: Total energy consumption in China higher than in the US but low
                                    at a per-capita level; per-capita consumption of primary energy (tonnes of oil
                                    equivalent) vs. per adjusted capita nominal GDP....................................................50
                                    Figure 33: Mobile subscription per 100 people vs. adjusted per capita
                                    nominal GDP ........................................................................................................51
                                    Figure 34: China is already the world’s largest car market…but still low per 1000
                                    people; passenger cars per 1000 people vs. adjusted per capita nominal GDP .........52
                                    Figure 35: Share of global nominal GDP (%) – China’s share is 10% in 2010
                                    and forecast to be 17% in 2020..............................................................................53




                                                                                                                                                       29
Adrian Mowat                                            Emerging Markets Equity Research
(852) 2800-8599                                         31 May 2011
adrian.mowat@jpmorgan.com




Demographics driving change
China’s official growth target and inflation rate for this                            Figure 38: More 19-year-olds in Tertiary Education - Less for
decade are 7% and 4% respectively. Considering its                                    construction, manufacturing and agriculture
historic double-digit growth rate with just 2% inflation,                             Millions
this lower target appears conservative. But China faces
                                                                                      30.0
demographic and structural challenges that investors                                                                          Under-graduates      Non-graduates
need to consider. The catalyst for writing this paper was                             25.0
the following statement in the Nation Bureau of Statistics                            20.0
press release on the November 2010 Census:
                                                                                      15.0
“Compared with the 2000 population census, following
changes took place in the number of people with various                               10.0
educational attainments of every 100,000 people:                                       5.0
number of people with university education increased
from 3611 to 8930;…….”                                                                 0.0




                                                                                             1990
                                                                                             1993
                                                                                             1996
                                                                                             1999
                                                                                             2002
                                                                                             2005
                                                                                             2008
                                                                                             2011
                                                                                             2014
                                                                                             2017
                                                                                             2020
                                                                                             2023
                                                                                             2026
                                                                                             2029
                                                                                             2032
                                                                                             2035
                                                                                             2038
                                                                                             2041
                                                                                             2044
                                                                                             2047
China’s investment in physical infrastructure is
legendary. On page 38 we review the impact of cheap                                   Source: PRC NBS, Ministry of Education PRC, US Census, J.P. Morgan calculation
money and an increase in the capital to output ratio. We
believe investors are underestimating the investment in                               Figure 39: Change in the non-graduate available workforce 15-39
human capital. This provides China with the ability to                                years old
maintain high growth through shifting labor from                                      %oya, Millions
manufacturing, construction and agriculture to services.                                 3%                                                                            600
But it cannot continue the investment driven growth                                      2%                                         %oya          Number
                                                                                                                                                                       500
model of the 2000s. China leaders acknowledge this in                                    1%
the 12th Five Year Plan with its focus on rebalancing the                                0%                                                                            400
economy from investment to consumption plus                                             -1%
                                                                                                                                                                       300
rebalancing of income distribution from profits to                                      -2%
household income.                                                                       -3%                                                                            200
                                                                                        -4%
                                                                                                                                                                       100
Our view is optimistic. The investment in both physical                                 -5%
and critically human capital permits high productivity                                  -6%                                                                            0
                                                                                                1990
                                                                                                1993
                                                                                                1996
                                                                                                1999
                                                                                                2002
                                                                                                2005
                                                                                                2008
                                                                                                2011
                                                                                                2014
                                                                                                2017
                                                                                                2020
                                                                                                2023
                                                                                                2026
                                                                                                2029
                                                                                                2032
                                                                                                2035
                                                                                                2038
                                                                                                2041
                                                                                                2044
                                                                                                2047
that is needed to drive growth with a declining working
age population.
                                                                                      Source: PRC NBS, Ministry of Education PRC, US Census, J.P. Morgan calculation
The winners are:
21. Consumers and consumer companies                                                  Figure 40: And reverse this trend
22. Automation                                                                        % of nominal GDP
23. Service sector growth                                                                  65                                                       Fixed investment
24. The environment
                                                                                           60                                                       Private consumption
25. Countries with better demographics
                                                                                           55                                                       Total consumption
The losers are                                                                             50
1. Intensity of commodity demand
                                                                                           45
2. Low value added labor intensive industries
                                                                                           40

Table 9: Calculation of the change in the number of graduates in                           35
China 2000 to 2010 based on Census data                                                    30
                                                                                                 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Year                  Ratio             Population                 Graduates
2000                  3.61%            1,265,824,852              45,708,935
2010                  8.93%            1,339,724,852              119,637,429         Source: IMF, Datastream, J.P. Morgan calculation
Change                5.32%              73,900,000               73,928,494
Source: PRC National Bureau of Statistics; November 2010 Census




30
Adrian Mowat                         Emerging Markets Equity Research
(852) 2800-8599                      31 May 2011
adrian.mowat@jpmorgan.com




2000s: High growth with low inflation                              Figure 41: Real GDP growth (2000=100)
                                                                        500                            Real GDP
The economy: 2000 to 2010
                                                                                                       Consumption
 Real GDP CAGR of 10.5%                                                400                            Inv estment
                                                                                                       External demand
 Nominal GDP CAGR of 15%                                               300
 2010 nominal GDP = Rmb40trillion or US$5880                           200
  billion. This is 10% of global GDP.
                                                                        100
 Per capita GDP CAGR of 14.3%
 CPI CAGR of 2%; significantly lower than the CPI                            0
  CAGR 1990 to 2000 of 7%.                                                             00        01     02        03    04        05        06        07    08    09        10

 Rmb/US$ CAGR of 2% from 8.277 to 6.6. But the                    Source: J.P. Morgan economics.
  exchange rate was fixed until 21 July 2005; the
  CAGR from this point to end 2010 was 4%.                         Figure 42: Contribution to China’s real GDP growth
                                                                                  Real consumption                Real investment           Real net external demand
 Average national wage CAGR of 14.6%. There was a                      15
  sharp acceleration in 2007-08 when the average
  growth was 18%. Minimum wages are growing faster                      10
  than the national average wage. The minimum wage
  CAGR 17.8% from 2005-09. In 2010, minimum                              5
  wages were increased by a substantial 23% to
  compensate for the lack of increment during the 2009                   0
  slowdown.
 Growth was led by fixed investment while                               -5
  consumption lagged:                                                             00        01    02        03    04   05    06        07        08    09   10   11    12

       Fixed investment CAGR of 12.7%                             Source: J.P. Morgan economics.


       Domestic consumption CAGR of 8.5%                          Figure 43: Growth in per capita GDP & average national wages
                                                                   (%)
       Net external demand CAGR of 11.4%
                                                                        22                            Per capita GDP
                                                                                                      Wages
                                                                        19
There are no other countries that have achieved the same
combination of low inflation and high growth that China                 16
had in the 2000s. For the past 30 years the country has
developed with an assumption of unlimited labor, notably                13
underemployed agricultural workers.
                                                                        10

                                                                        7
                                                                                  00        01         02        03    04     05            06        07    08    09        10

                                                                   Source: CEIC, IMF.




                                                                   .




                                                                                                                                                                             31
Adrian Mowat                           Emerging Markets Equity Research
(852) 2800-8599                        31 May 2011
adrian.mowat@jpmorgan.com




Investment-led growth in the 2000s                                   Figure 44: From consumption to investment
China’s economic development is a souped-up version of               % of nominal GDP
the Asian investment led growth model. The contribution                    65                                                       Fixed investment
of fixed investment to GDP growth surpassed the
                                                                           60                                                       Private consumption
contribution from real consumption in 2003 (see Figure
42). In 2009 fixed investment contributed 8.6% of                          55                                                       Total consumption
China's 9.1% real GDP growth, helping offset the sharp                     50
contraction in external demand. In the past decade, as a                   45
percentage of nominal GDP fixed investment increased
                                                                           40
from 34% to 46%. Consumption declined from 62% to
48%; private consumption fell from 46% to 35% (see                         35
Figure 44).                                                                30
                                                                                 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Financing an investment growth model requires a wealth
                                                                     Source: J.P. Morgan economics, IMF
transfer from households to profits. The subsidy is
achieved via low wages, low return on savings and an
                                                                     Figure 45: Household income lagging profits and GDP growth
undervalued currency. The impact of this policy is clear
in Figure 45; industrial profits grew at 25% CAGR from                    800%                                                                     748%
2000-09, more than double the pace of household income                    700%                        GDP
                                                                                                      Government
growth of 11%. The 12th Five-Year Plan acknowledged                       600%                                                                     512%
                                                                                                      Profits
the inequality of growth with an aim to balance revenue                   500%
                                                                                                      Income
distribution among enterprises, individuals, central                      400%                                                                     343%
governments and local authorities.                                        300%
                                                                          200%                                                                     258%
The intensity of commodity use increased sharply.                         100%
Commodity consumption grew in the high teens in the                        0%
last decade (see Table 10). In 2010, China accounted for                          2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
over half of the world’s iron ore demand.
                                                                     Source: CEIC.
China cement consumption is remarkable (see Figure
64). China's per capita cement consumption was                       Table 10: China's dominant share of global commodity demand
1.34tonnes in 2010. Korea in 1997 did reach the same                 and CAGR 2000-10
level of per capita cement consumption that China                                                   China share of global demand (%)
achieved in 2010. But Korean per capita GDP in 1997 (in                                     Aluminum        Nickel        Copper     Iron ore
today's dollars) was four times China’s current per capita                     2000                13                          12          20
                                                                               2001                15                          15          21
GDP. In 1998 Korea had a current account crisis. Note                          2002                16                          16          23
the trend in Taiwan’s per capita cement demand. Taiwan                         2003                18           11             19          26
property prices peaked in 1994, a year after the peak in                       2004                20           13             21          30
cement demand.                                                                 2005                22           15             23          36
                                                                               2006                26           18             23          40
                                                                               2007                32           23             26          43
J.P. Morgan’s equity strategy team is less optimistic                          2008                33           23             28          47
about China commodity demand than the consensus (see                           2009                39           32             37          60
                                                                               2010                41           33             37          57
page 39). There are numerous reasons discussed below
                                                                     CAGR (2000-10)              17.5        20.5*           14.6        19.9
that require a move away from an investment-led growth
                                                                     Source: J.P. Morgan commodities research and Brook Hunt historic. * Nickel demand
model.                                                               CAGR is from 2003-10.




32
Adrian Mowat                             Emerging Markets Equity Research
(852) 2800-8599                          31 May 2011
adrian.mowat@jpmorgan.com


Demographic transition                                                 Table 11: China’s working age population
China published the results of it 2010 census in April. On             (millions)             Population               Working age            Growth in
1 November 2010 the total population was                                                                                popn % of            working age
1,339,724,852. The growth from 2000 was just 73.9                                       Working age         Total       total popn            popn (%)
                                                                            1990           724              1148            63
million, or a 0.57% CAGR. The growth rate halved                            2000           819              1264            65                    13.2
compared to the 1990s, which had a CAGR 1.07%. The                          2010           921              1340            69                    12.4
decline in the fertility rate partly explains the reduction                 2020           905              1385            65                    -1.8
from 3.44 to 3.1 people per household. The number of                        2030           830              1391            60                    -8.2
households was 401.5million. The growth in total                       Source: US Census.
population is forecast to slow to 0.3% CAGR in 2010-20.                Table 12: Urbanization rate in the last decade and current (CAGR)
                                                                       %                                    2000-2010                      2010-2020
In the 2000s the working age population increased by                   EM
12% a CAGR of 1.2%. This is the decade when China's                    China                                    3.8                           2.1
working age population will start to decline. The working              Malaysia                                 3.3                           2.2
age population comprised 69% of the total population in                India                                    2.3                           2.4
                                                                       Philippines                              2.0                           2.3
2010. It grew 12% from 2000 to 2010, a CAGR of 1.2%.                   Morocco                                  2.0                           2.1
According to the US Census, the working age population                 Turkey                                   2.0                           1.6
is expected to contract by 1.8%, or a -0.2% CAGR, this                 Egypt                                    2.0                           2.1
decade (see Table 11).                                                 South Africa                             2.0                           1.2
                                                                       Colombia                                 1.9                           1.6
                                                                       Israel                                   1.8                           1.4
The population under the age of 14 declined by 6.3% to                 Brazil                                   1.8                           1.0
16.6%. The population is aging rapidly, with 13.3% over                Peru                                     1.8                           1.5
60 years, an increase of 2.9% compared to 2000. The                    Indonesia                                1.8                           1.7
                                                                       Thailand                                 1.8                           1.8
population is ethnically homogeneous, with 91% Han                     Mexico                                   1.5                           1.1
Chinese.                                                               Chile                                    1.4                           1.1
                                                                       Argentina                                1.2                           1.0
                                                                       Korea                                    0.8                           0.5
The urban and rural split is now 50:50. The urban                      Hungary                                  0.3                           0.3
population is 665.6 million and rural 674.2 million. In                Czech Republic                           0.1                           0.3
2000 the urban population was 36%. This is low even                    Poland                                   -0.2                          0.0
compared to other emerging markets (see Table 13).                     Russia                                   -0.5                          -0.2
                                                                       DM
China’s urbanization rate was a 3.8% CAGR in the last                  Singapore                                1.9                            0.8
decade. This was the fastest rate of urbanization across               France                                   1.6                            0.9
EM and DM (see Table 12). Each year China added 21                     US                                       1.4                            1.2
million to its urban population. It is assumed that the                Australia                                1.4                            1.1
                                                                       Italy                                    0.7                            0.4
urbanization rate will slow to 2.1% during this decade.                UK                                       0.6                            0.7
The population is shifting, with an 81% increase in the                Hong Kong SAR                            0.6                            0.9
                                                                       Japan                                    0.3                            0.1
population living in a different location than their town              Germany                                  0.1                            0.0
of registration. This growth rate may be exaggerated by a              Source: United Nations, World Urbanization Prospects: The 2009 Revision Population
new methodology for counting unregistered migrant                      Database.
labor in the 2010 census. The shift is to the wealthy
Eastern region.
The peak in China’s working age population is well
known. It is the rate of urbanisation that is debatable. In
the past decade it exceeded estimates. There is no clear
relationship between per-capita GDP and the
urbanization rate, and there is a large spread of
urbanization rates across developed and emerging
economies.




                                                                                                                                                            33
Adrian Mowat                           Emerging Markets Equity Research
(852) 2800-8599                        31 May 2011
adrian.mowat@jpmorgan.com


Demographics drive rebalancing                                       Table 13: Urban population as a percentage of the total
                                                                     population
China’s official growth target and inflation rate for this
                                                                     %                                        1990              2000          2010     2020
decade is 7% and 4% respectively. This is a reasonable               EM
base case. In this section we review the assumptions that            Argentina                                   87               90            92         94
we believe investors should watch.                                   Israel                                      90               91            92         92
                                                                     Chile                                       83               86            89         91
                                                                     Brazil                                      74               81            87         90
Simple model                                                         Republic of Korea                           74               80            83         86
Theoretical potential GDP growth = the change in the                 Mexico                                      71               75            78         81
hours worked + productivity – adjustment factor. This is             Peru                                        69               73            77         80
                                                                     Colombia                                    68               72            75         78
a gross simplification of the dynamics of the world’s                Czech Republic                              75               74            74         75
second largest economy. The key demographic                          Russian Federation                          73               73            73         75
assumptions are:                                                     Malaysia                                    50               62            72         78
                                                                     Turkey                                      59               65            70         74
                                                                     Hungary                                     66               65            68         72
1. The CAGR of the working age population was 1.2%                   South Africa                                52               57            62         67
   in the last decade. The US Census forecast minus                  Poland                                      61               62            61         62
   0.2% CAGR in the working age population this                      Morocco                                     48               53            58         64
                                                                     China                                       26               36            50         55
   decade.                                                           Philippines                                 49               48            49         53
                                                                     Indonesia                                   31               42            44         48
2. In the 2000s the urbanization CAGR was 3.8%; the                  Egypt                                       43               43            43         46
   highest globally. The UN forecast urbanization                    Thailand                                    29               31            34         39
   CAGR 2.1% this decade.                                            India                                       26               28            30         34
                                                                     DM
3. The CAGR in the urban working age population is                   Hong Kong SAR                             100              100           100         100
                                                                     Singapore                                 100              100           100         100
   forecast to decelerate from 4.5% to 1.2%.
                                                                     Australia                                  85               87            89          91
In 2008, China had the highest labor productivity                    France                                     74               77            85          90
                                                                     United States of America                   75               79            82          85
globally (measured by GDP per person engaged). Labor                 United Kingdom                             78               79            80          81
productivity growth was a 10.5% CAGR in 2000-08 (as                  Germany                                    73               73            74          76
per the International Labor Organization). The range is              Italy                                      67               67            68          71
wide with the maximum at 14% and the minimum at 8%.                  Japan                                      63               65            67          69
                                                                     Source: United Nations, World Urbanization Prospects: The 2009 Revision Population
                                                                     Database. Table sorted by urban population % of total in 2010.
Urbanization, growth and productivity
The high rate of urbanization in the last decade                     Table 14: Sensitivity of potential GDP calculation to productivity
contributed to higher labor productivity as the population           using the growth in working age population
migrated from lower return agricultural jobs to higher
                                                                     Parameters                                     #1             #2           #3          #4
income manufacturing jobs. We solve for the adjustment               Working age pop growth                       -0.2           -0.2         -0.2        -0.2
factor using both the 2000s growth in working age                    Productivity growth                             6              8           10          12
population and urban working age population. In Table                Adjustment factor                             1.2            1.2          1.2         1.2
14 and Table 15 we calculate the 2010 to 2020 potential              Potential GDP                                 4.6            6.6          8.6        10.6
GDP using the growth in working age and urban working                Source: J.P. Morgan calculation

age population. The challenge for China is maintaining a
high level of productivity growth. The arguments in                  Table 15: Sensitivity of potential GDP calculation to productivity
                                                                     using the growth in urban working age population
favor of maintaining high productivity growth are:
                                                                     Parameters                                          #1            #2       #3        #4
                                                                     Urban working age pop growth                         1.2           1.2      1.2       1.2
1. Investment in human capital: In the past decade the               Productivity growth                                    6             8       10        12
   ratio of the population with a university degree                  Adjustment factor                                    4.5           4.5      4.5       4.5
   increased from 3.6% to 8.9%. That is an increase of               Potential GDP                                        2.7           4.7      6.7       8.7
   74 million graduates, more than the population of                 Source: J.P. Morgan calculation
   Thailand. A third of 19-year-olds (circa 21 million)
   are undergraduates. If China can generate service
   sector jobs, the migration from manufacturing to
   service will boost productivity.




34
Adrian Mowat                                            Emerging Markets Equity Research
(852) 2800-8599                                         31 May 2011
adrian.mowat@jpmorgan.com




2. Low cost of capital: The 12-month best lending rate                                manufacturing and construction. We believe that this is
   is 6.31%. A real rate of 2.3% assuming the new CPI                                 the most important driver of the need for China to reduce
   target of 4%. The discount to nominal GDP growth                                   its fixed asset investment. It reverses the commonly
   target is 3.7%. The low cost of capital relative to                                held belief that China must have growth above 8% to
   growth lowers the hurdle rate for productive capex.                                generate sufficient jobs.

3. Economies of scale and clustering: The large scale                                 Table 17: Key population statistics
   of manufacturing facilities in China permits the
                                                                                           Size (million)             1990        2000         2010     2020         2030
   investment in R&D for customized automation.                                       Population                      1,148       1,264        1,330    1,385        1,391
                                                                                      Working age population            724         819          921      905          830
4. Infrastructure: Huge investment in infrastructure                                  Over 60 population                  63          86         115      172          239
   increases logistic efficiency. Shorter delivery times                              Over 60 population (%)            5%          7%           9%      12%          17%
   and superior inventory management allow for                                        Urban population (%)             26%         36%          50%      62%          68%
                                                                                      Urban population                  299         455          665      851          950
   premium pricing.                                                                   Household size                     3.7         3.4          3.1      3.1          3.1
                                                                                      Urban households                    81        132          215      275          306
The non-graduate labor shortage
                                                                                      Source: NBS China, US Census, J.P. Morgan calculations
A key data point from the November 2010 census was:
                                                                                      Table 18: Annual growth key population statistics
“Compared with the 2000 population census, following
changes took place in the number of people with various                                     CAGR (%)                 2000       2010           2020     2030        2040
                                                                                      Population                      1.0%       0.5%           0.4%     0.1%       -0.2%
educational attainments of every 100,000 people:                                      Working age population          1.2%       1.2%          -0.2%    -0.9%       -0.8%
number of people with university education increased                                  Over 60 population              3.2%       2.9%           4.1%     3.3%        3.2%
from 3611 to 8930; number of people with senior                                       Urban population                4.3%       3.9%           2.5%     1.1%        0.8%
secondary education increased from 11146 to 14032; the                                Household size                 -0.7%      -1.0%           0.0%     0.0%        0.0%
                                                                                      Urban households                5.1%       5.0%           2.5%     1.1%        0.8%
number of people with junior secondary education
                                                                                      Source: NBS China, US Census, J.P. Morgan calculations
increased from 33961 to 38788; and the number of
people with a primary education decreased from 35701
                                                                                      Table 19: Number of graduates in China
to 26779”. (Source: National Bureau of Statistics
                                                                                      0000s
press release on Major Figures of the 2010 National
                                                                                                                  Graduates           New Entrants       Total Enrolment
Population Census).
                                                                                      Higher Education
                                                                                      Postgraduates                   371                   511                   1,405
An increase from 3.6% to 8.9% of the population with a                                 Doctor's Degrees                49                    62                    246
university degree means that the number of graduates in                                Master's Degrees               323                   449                   1,159
China increased by 73.9 million in the past decade. This                              Undergraduates in              5,311                 6,395                 21,447
                                                                                      Regular HEIs
figure is 116% higher than the Ministry of Education                                   Normal Courses                2,455                 3,261                 11,799
Data in CEIC. Based on the Ministry of Education                                       Short-cycle Courses           2,856                 3,134                  9,648
website the discrepancy may be partly explained by the                                Undergraduates in              1,944                 2,015                  5,414
                                                                                      Adult HEIs
1.9 million graduates in adult higher education institutes
                                                                                       Normal Courses                 865                   816                  2,257
and the 1 million web-based graduates (see Table 19,                                   Short-cycle Courses           1,078                 1,199                 3,157
http://www.moe.edu.cn/publicfiles/business/htmlfiles/mo                               Web-based                       984                  1,626                 4,173
e/s4969/201012/113484.html). Based on Ministry of                                     Undergraduates
                                                                                       Normal Courses                 406                    551                  1,573
Education press release, 180,000 students went abroad to
                                                                                       Short-cycle Courses            578                   1,074                 2,600
study. Note that new entrants in 2010 were 8.4 million.                               Total Undergraduate            8,238                 10,035                31,033
                                                                                      Source: Ministry of Education of the PRC (29 December 2010)
Table 16: Calculation of the change in the number of graduates in
China 2000 to 2010 based on Census data
Year                  Ratio             Population                 Graduates
2000                  3.61%            1,265,824,852              45,708,935
2010                  8.93%            1,339,724,852              119,637,429
Change                5.32%              73,900,000               73,928,494
Source: PRC National Bureau of Statistics; November 2010 Census


We forecast a 90 million decline in the non-graduate
working-age population. In the 2000s the non-graduate
working age population expanded by 30 million. This
swing of 130 million will add to wage inflation in

                                                                                                                                                                          35
Adrian Mowat                                             Emerging Markets Equity Research
(852) 2800-8599                                          31 May 2011
adrian.mowat@jpmorgan.com




130 million decline in manual workforce                                                Figure 47: Change and absolute number of 19-year-old non-
We use a number of data sources and assumptions to                                     graduates
calculate the change in the non-graduate workforce. As                                 %oya, Millions
noted above the November 2010 Census highlighted a 74                                         6.0%                                                                      30
million increase in graduates in China. This is higher                                        4.0%                                  %oya            Non-graduates
                                                                                                                                                                        25
than the CEIC data from the Ministry of Education.                                            2.0%
                                                                                              0.0%                                                                      20
Combining both regular and adult data 8.4 million new                                        -2.0%
                                                                                                                                                                        15
graduates entered university in 2010. The enrolment-to-                                      -4.0%
graduate ratio is 3.5 (calculated from Ministry of                                           -6.0%                                                                      10
Education website). We assume that the number of new                                         -8.0%
                                                                                                                                                                        5
entrants remains at 8.4 million through to 2049; this is                                    -10.0%
conservative. The available non-graduate workforce aged                                     -12.0%                                                                      0




                                                                                                     1990
                                                                                                     1993
                                                                                                     1996
                                                                                                     1999
                                                                                                     2002
                                                                                                     2005
                                                                                                     2008
                                                                                                     2011
                                                                                                     2014
                                                                                                     2017
                                                                                                     2020
                                                                                                     2023
                                                                                                     2026
                                                                                                     2029
                                                                                                     2032
                                                                                                     2035
                                                                                                     2038
                                                                                                     2041
                                                                                                     2044
                                                                                                     2047
15-39 is calculated excluding cumulative graduate (of
that age group) and those enrolled in university.
                                                                                       Source: PRC NBS, Ministry of Education PRC, US Census, J.P. Morgan calculation

The Chinese manufacturing sector has historically used                                 Figure 48: Change in the non-graduate available workforce 15-39
young migrant labor. The combination of a shrinking                                    years old
pool of 15-39 years old and the upgrading of their skill                               %oya, Millions
set argues for a sharp decline in the workforce willing to
                                                                                          3%                                                                            600
work in manufacturing and construction.                                                                                            %oya            Number
                                                                                          2%
                                                                                                                                                                        500
                                                                                          1%
The challenge for China is generating jobs for the
                                                                                          0%                                                                            400
eight million graduates entering the work force each
                                                                                         -1%
year. Graduate unemployment is already a source of                                                                                                                      300
                                                                                         -2%
concern. It is arguably harder for government policy to
                                                                                         -3%                                                                            200
drive service sector employment than manual and semi-                                    -4%
skilled through stimulus programs.                                                       -5%
                                                                                                                                                                        100

                                                                                         -6%                                                                            0
                                                                                                 1990
                                                                                                 1993
                                                                                                 1996
                                                                                                 1999
                                                                                                 2002
                                                                                                 2005
                                                                                                 2008
                                                                                                 2011
                                                                                                 2014
                                                                                                 2017
                                                                                                 2020
                                                                                                 2023
                                                                                                 2026
                                                                                                 2029
                                                                                                 2032
                                                                                                 2035
                                                                                                 2038
                                                                                                 2041
                                                                                                 2044
                                                                                                 2047
Figure 46: More 19 years old in Tertiary Education - Less for                          Source: PRC NBS, Ministry of Education PRC, US Census, J.P. Morgan calculation
construction, manufacturing and agriculture
Millions
30.0
                                      Under-graduates        Non-graduates             Figure 49: Tertiary enrolment ratio as a percentage of 19-year-
25.0                                                                                   olds
                                                                                        80%
20.0
                                                                                        70%
15.0                                                                                    60%
10.0                                                                                    50%
                                                                                        40%
 5.0
                                                                                        30%
 0.0                                                                                    20%
       1990
       1993
       1996
       1999
       2002
       2005
       2008
       2011
       2014
       2017
       2020
       2023
       2026
       2029
       2032
       2035
       2038
       2041
       2044
       2047




                                                                                        10%

Source: PRC NBS, Ministry of Education PRC, US Census, J.P. Morgan calculation
                                                                                            0%
                                                                                                 1990
                                                                                                 1993
                                                                                                 1996
                                                                                                 1999
                                                                                                 2002
                                                                                                 2005
                                                                                                 2008
                                                                                                 2011
                                                                                                 2014
                                                                                                 2017
                                                                                                 2020
                                                                                                 2023
                                                                                                 2026
                                                                                                 2029
                                                                                                 2032
                                                                                                 2035
                                                                                                 2038
                                                                                                 2041
                                                                                                 2044
                                                                                                 2047




                                                                                       Source: PRC NBS, Ministry of Education PRC, US Census, J.P. Morgan calculation




36
Adrian Mowat                                           Emerging Markets Equity Research
(852) 2800-8599                                        31 May 2011
adrian.mowat@jpmorgan.com




Net external demand a drag on growth?                                                Table 20: China's export share of world trade; selected
FT Confidential (7 April 2011) forecast 20-30% wage                                  commodities
inflation for the 166 million migrant workers. In the same                           % share                       1990         2001    2003    2005    2008       2009
                                                                                     Textiles                        4.8         14.4    20.9    25.9    25.8       28.3
report Hong Kong Footwear Makers Association in                                      Clothing                        8.9         18.9    22.4    26.9    33.0       34.0
Dongguan reported a 5% drop in orders post a margin                                  Iron and steel                  1.2          2.4     2.6     6.1    12.0        7.3
protecting 15% increase in prices. Textile and footwear                              Chemicals                       1.3          2.2     2.4     3.2     4.7        4.3
orders are shifting to Bangladesh, India and Vietnam.                                Machinery & transport           0.9          3.8     6.4     9.2    12.6       14.0
                                                                                     equip.
Minimum wages in India and Vietnam are US$96 and                                     Office & telecom equip.         1.1          6.2    12.3   17.7     24.3       26.2
US$62 per month compares to China's lowest minimum                                     Telecom equip.                 na          8.8    14.6   20.4     26.9       29.4
wage in the Western provinces of US$130 (RMB850).                                    Source: World Trade Organization
The minimum wage in Shenzhen, Guangdong is US$200
(Rmb1320).                                                                           Changing composition of growth
                                                                                     Below we explore the potential magnitude of
Note that China already has a significant share in high                              deceleration in fixed investment growth if real GDP
value added exports including electronics and machinery.                             growth slows to a base case of 7% and the drivers of
It is reasonable to assume that China’s trade surplus                                growth shift from fixed investment to consumption.
narrows as it loses market share in low-value-added
industry. This is potentially a win-win situation with                               Assumptions:
China replacing low-value jobs with high-value service                                    Real GDP CAGR (2010-20): 7%
jobs, while less developed countries with rapidly growing
working age populations win market share.
                                                                                                 Consumption, fixed investment and net external
                                                                                                  demand as a share of GDP return to 2000 levels
                                                                                                  (see Table 21).
Figure 50: China labor productivity growth (%)
   15.0                                                                              Results:
   14.0                                                                                   Fixed investment CAGR decelerates from
   13.0                                                                                       12.7% to 4.7% (2000-10).
   12.0
   11.0                                                                                          Consumption CAGR increases from 8.5% to
   10.0                                                                                           8.9% (2000-10). Private consumption CAGR
    9.0
                                                                                                  increases from 7.5% to 10%.
    8.0
    7.0
    6.0
                                                                                                 Net exports CAGR decelerates from 11% to 6%
             2000    2001     2002     2003   2004   2005   2006   2007   2008
                                                                                                  (2000-10)

Source: International Labor Organization                                             Net external demand contributed an average 0.7% to real
                                                                                     GDP growth in the last decade. In this decade if Chinese
Figure 51: China export price index (%oya, nsa)                                      wage growth exceeds other EMs then net external
   15                                                                                demand may be negative.
   10                                                                                Table 21: Potential consumption and investment CAGR (2010-20)
    5                                                                                %                                  Real GDP        Consn    Fixed Inv      Ext Dd
                                                                                     Share of GDP in 2000                                56         38            5
    0                                                                                Share of GDP in 2010                                47         47            5
                                                                                     Assumed share in 2020                               56         38            5
   -5                                                                                CAGR (00-10)                          10.5          8.5       12.7          11.4
                                                                                     CAGR forecast (10-20)                  7            8.9        4.7          6.1
  -10
                                                                                     Source: J.P. Morgan economics, strategy.
  -15
        96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11

Source: J.P. Morgan economics.




                                                                                                                                                                   37
Adrian Mowat                            Emerging Markets Equity Research
(852) 2800-8599                         31 May 2011
adrian.mowat@jpmorgan.com




Cheap money and high ICOR                                             Table 22: Real GDP growth, ICOR and average CPI during high
The Incremental Capital Output Ratio is domestic                      growth periods
investments divided by the change in real GDP. China’s                              High growth            Avg Real GDP               Average      Average Annual
ICOR has been rising in the last three years. It has                                   period                growth %                  ICOR            CPI %
                                                                      China*         1979-2010                  9.9                     4.0              6.02
averaged 4.0 in the high growth period since 1979. This
                                                                      Taiwan         1965-1990                  8.8                     3.3              6.36
is higher than the ICOR in Korea, Taiwan and Japan                    Korea          1965-1990                  8.9                     2.0             11.62
during their respective high growth periods (See Table                Japan**        1956-1970                  9.9                     2.6              9.12
22).                                                                  India          1991-2010                  6.9                     4.0              6.35
                                                                      Source: J.P. Morgan economics, Bloomberg
Twice EM fixed investment to GDP ratio
                                                                      Figure 52: China FAI breakdown
China fixed investment to GDP ratio is twice the EM
                                                                           70%
average (see Table 23). Excess savings help fund this
                                                                           60%
investment via the banking. The rapid rise in profits
                                                                           50%
relative to GDP (Figure 45) provided the cash for
                                                                           40%
reinvestment. As household income to GDP rises there
will be a corresponding decline in profits to GDP.                         30%

                                                                           20%

The low return on savings is a drag on consumption.                        10%

Individuals save to meet future liabilities. The largest                   0%
                                                                                 2004      2005         2006        2007      2008        2009    2010   2011
liability is their pension. Today bank deposit rates are
more than 10% lower than nominal wage growth. The                                                 Priv ate and JV   State Ow ned     Collective
result is that individuals are forced to save larger and
                                                                      Source: J.P. Morgan economics
larger portion of their income in order to have sufficient
capital to retire. It may be counterintuitive, but China
                                                                      Table 23: Contribution to real GDP: China the outlier
needs higher interest rates to boost consumption.
                                                                       Countries                        Consumption                Fixed Investment      Net trade
                                                                       Argentina                            78%                           23%              -1%
Its investment in human capital permits China to break
                                                                       Brazil                               82%                           21%              -3%
away from its investment-led growth model. The risk is                 Chile                                84%                           28%             -11%
that the ministries and industries which thrive with                   China                                48%                           47%               5%
investments are unwilling to reduce their share of GDP.                Colombia                             81%                           24%              -5%
                                                                       Czech Republic                       71%                           27%               2%
Potential risks of this are poor allocation of capital and
                                                                       Hungary                              72%                           13%              15%
inflation.                                                             India                                73%                           33%              -6%
                                                                       Indonesia                            66%                           24%               9%
                                                                       Malaysia                             66%                           23%              11%
                                                                       Mexico                               81%                           22%              -3%
                                                                       Peru                                 75%                           25%               0%
                                                                       Philippines                          86%                           21%              -6%
                                                                       Poland                               79%                           23%              -2%
                                                                       Russia                               77%                           22%               1%
                                                                       South Africa                         84%                           22%              -6%
                                                                       South Korea                          67%                           27%               6%
                                                                       Taiwan                               66%                           19%              15%
                                                                       Thailand                             60%                           22%              19%
                                                                       Turkey                               81%                           20%              -1%
                                                                      Source: J.P. Morgan economics:
                                                                      Note: In Figure 44: From consumption to investment nominal rather real GDP is used to
                                                                      calculate the ratio.




38
Adrian Mowat                                         Emerging Markets Equity Research
(852) 2800-8599                                      31 May 2011
adrian.mowat@jpmorgan.com




Impact on commodity demand                                                           Table 24: How slower investment could reduce commodity
If fixed asset investment real growth slows from 12.7%                               demand – base case and 4.8% growth
to 4.7% in 2010s then China’s demand for commodities                                                                      Aluminium          Nickel       Copper       Iron ore
will slow. In Table 24 we assume 4.7% growth in                                      2000                                         13                          12             20
                                                                                     2010                                         41             33           37             57
China’s commodity demand. The difference in global
                                                                                     2015e                                        49             41           42             57
demand, between the J.P. Morgan’s base case and the                                  CAGR (2000-10)                             17.5           20.5         14.6           19.9
rebalance scenario in 2015, ranges from -12%                                         China CAGR (2010-15)                       10.8           10.4          6.2            5.8
(aluminium) to -3% (iron ore).                                                       base case
                                                                                     Total CAGR (2010-15) base                      7.0          5.6           4.0           5.8
                                                                                     case
Figure 53: China ICOR                                                                Base case 2015 total volume                58209          1979        23359          2636
   8                                                                                 Rebalance scenario volume                  51360          1791        22735          2567
                                                                                     Reduction                                   -12%           -9%          -3%           -3%
                                                                                     Source: J.P. Morgan estimates, J.P. Morgan EM equity strategy team calculations
   6


   4


   2


   0
       1979   1982   1985    1988   1991   1994   1997   2000   2003   2006   2009

Source: J.P. Morgan economics.




                                                                                                                                                                        39
Adrian Mowat                           Emerging Markets Equity Research
(852) 2800-8599                        31 May 2011
adrian.mowat@jpmorgan.com



China’s export sector copes with rising wages
Grace Ng (852) 2800-7002. March 4, 2011

 Tradable goods inflation has been modest so far,                   Figure 54: China export prices and US import prices from China
  but rising wages have begun to affect production                          %oya, both scales                               US import prices from
  costs.                                                                    16                                              China, USD terms (RHS)   6.0
                                                                            12
     Rising export prices in 2007-08 largely reflected                                  China export prices, USD                                    4.0
                                                                                8                (LHS)
     stronger CNY; this time domestic inflation plays a
                                                                                                                                                     2.0
     major role.                                                                4
                                                                                0
 Export sector manages to move up value-added                                                                                                       0.0
    chain amid rising costs, with profit margins on the                     -4
                                                                                                     China export prices,                            -2.0
    rise.                                                                   -8
                                                                                                        Yuan (LHS)
As part of the growing global attention being paid to                      -12                                                                       -4.0
China’s inflation, there is increasing concern that                             Jan 05           Jul 06            Feb 08        Sep 09        Apr 11
domestic inflation is being transmitted abroad through               Source: J.P. Morgan economics
rising export prices. The latest US data showed that
consumer goods import prices have begun to turn up on                Figure 55: Export price trends - China, Korea and Taiwan
the back of rising prices in China. The broader worry is                   %oya, USD terms
that overheating risks in the EM world will place                         20
significant upward pressure on DM consumer goods                                         China
prices. Alternatively, for China’s trade sector, the worry                10
is that, faced with upward pressure on domestic                            0
production costs, which has become a more dominant
concern than the gradual appreciation of the CNY/USD                      -10                             Taiwan
exchange rate, Chinese exporters may begin to lose                                                                                    Korea
                                                                          -20
export market share in the global economy.
China’s inflation: domestic vs. trade sector                              -30

For China’s inflation, we have highlighted that, in                                 06              07               08              09              11
addition to near-term pressure from rising food prices,              Source: J.P. Morgan economics
the recent upward trend in nonfood inflation has been                Figure 56: Manufacturing wages relative to industry output
notable as well: the nonfood CPI rose 2.6%oya in
                                                                           108
January, the fastest rise in 13 years. Within the nonfood
CPI, however, it is the domestic service sector, in                        106
particular the housing component, that has been rising
                                                                           104
the fastest, with the housing CPI up 6.8%oya in January.
Meanwhile, our estimate for the major consumer goods                       102
CPI component, which reflects the pricing trend in the
                                                                           100
tradables sector and is more relevant to China’s export
prices, rose a modest 0.5%oya in January, gradually                         98
emerging from the prevalent deflationary trend seen in                      96
recent years. Along with that, China’s export price index
                                                                                    05Q1     06Q1         06Q1      07Q1      08Q1     09Q1     10Q1
in yuan terms (that is, before reflecting the currency
effect) rose 4.7%oya 3mma by January.                                Source: J.P. Morgan economics

While the price increase in the tradable goods sector has
been modest compared to overall domestic service prices,             This ratio should reflect the trend in labor cost per unit of
reflecting persistent, entrenched excess capacity in a               secondary industry output (dominated by manufacturing).
number of manufacturing industries over the years, the               Interestingly, while this measure was relatively stable
general costs of production in China’s manufacturing                 during 2005-08 (except during the financial crisis period,
sector, including wages, have been rising. We                        when it fell somewhat), the index started to pick up
constructed a measure of wage cost pressure by dividing              rather notably since early 2009. This trend to some extent
total manufacturing sector wage payments by secondary                reflects the gradual rise in overall labor cost in the
industry GDP output (in nominal terms).                              manufacturing sector during the past two years.



40
Adrian Mowat                            Emerging Markets Equity Research
(852) 2800-8599                         31 May 2011
adrian.mowat@jpmorgan.com

Regarding the implications for China’s export prices,                 western parts of the country, with migration speeding up
broadly speaking, the recent pace of gain in China’s                  considerably over the past two years. As the Chinese
export prices has been generally in line with that in other           government is set to speed up the urbanization process
major exporters in EM Asia such as Taiwan and Korea,                  and infrastructure spending in inland regions under the
as improving global demand allows Asian exporters to                  12th five-year plan, the improvement in the
lift prices at a gradual pace.As such, the pace of gain in            transportation network should further encourage
US$ export prices in over-year-ago terms is approaching               manufacturers to move inland.
the recent peak seen during 2H07-1H08. Meanwhile, this
time the rise in China’s export prices has been largely               Figure 57: Share of US import market
driven by the gradual rise in domestic prices, while in                        % share, 12-month moving average
2007-08 the notable appreciation in the CNY/USD                                20
exchange rate played an important role in the rise in                          18
China’s US$ export prices (CNY/USD appreciated by                              16              EM Asia (ex-China)                China
about 10% between mid-2007 and mid-2008). This                                 14
suggests that, in addition to the gradual, moderate rise in                                                                                        Mexico
                                                                               12
China’s tradable goods prices, as the pace of CNY
appreciation picks up further (we expect CNY/USD to                            10
rise about 5% this year), along with expected solid global                     8                                      Japan
demand, there could be more upward pressure on China’s                         6
export prices (in US$ terms).                                                       98         00           02         04         06        08         10          12

                                                                      Source: J.P. Morgan economics
Exporters adapting to rising wages
The encouraging news is that despite growing concerns                 Figure 58: Industrial enterprise profit margin
over rising production costs (hence the pressure to raise                  % of sales revenue, 3mma
export prices), China’s share of the US (and global)                       7                                                      Overall industrial enterprises
market, which had expanded significantly over the past
decade, remained at an elevated level through 2010. In                     6
addition, profit margins for China’s industrial enterprises,               5
which suffered notably during the global financial crisis,
have rebounded swiftly during the past two years.                          4
Indeed, profit margins for the export-related industrial                   3
enterprises in particular have advanced notably,                                                 Export-related industrial enterprises
significantly exceeding the average pre-crisis level. The                  2
fact that China’s export sector is holding up well, despite                     03        04         05          06         07        08     09       10         11

growing cost concerns, has come on the back of steady                 Source: J.P. Morgan economics
industrial upgrading and moving up the value-added
chain. Indeed, while the share of China’s exports of                  Figure 59: China exports by region
lower end consumer goods (such as textiles and clothing)                    % share of total exports, 12mma, both scales
in the global market seems to be gradually peaking,                        92.5                                                                                  10.5
China’s share of the global market in many higher value-                                     Coastal region (LHS)
                                                                           92.0                                                                                  10.0
added industries, such as machinery and high-tech
sectors, has continued to expand in recent years.                          91.5                                                                                  9.5
                                                                           91.0                                                                                  9.0
Another way Chinese exporters have attempted to
                                                                           90.5                                                                                  8.5
manage production costs has been to move inland, where
costs of labor and land are generally lower than in the                    90.0                                                                                  8.0
                                                                                                         Western and central region (RHS)
coastal area. Indeed, a growing number of large-scale                      89.5                                                                                  7.5
US, European, and Asian manufacturers have moved part                                00             02            04             06          08             11
of their coastal production lines to the central and
                                                                      Source: J.P. Morgan economics




                                                                                                                                                                        41
Adrian Mowat                                             Emerging Markets Equity Research
(852) 2800-8599                                          31 May 2011
adrian.mowat@jpmorgan.com




Table 25: Summary of key population data
Size (million)                                                  1990            2000        2010     2020     2030     2040
Population                                                      1,148           1,264       1,330    1,385    1,391    1,359
Working age population                                           724             819         921      905      830      766
Over 60 population                                                63              86         115      172      239      327
Over 60 population (%)                                           5%              7%          9%      12%      17%      24%
Urban population                                                26%             36%         50%      62%      68%      76%
Urban population                                                 299             455         665      851      950     1,029
Household size                                                   3.7             3.4         3.1      3.1      3.1      3.1
Urban households                                                  81             132         215      275      306      332

Change (millions)                                               1990             2000        2010    2020     2030     2040
Population                                                                        115          67      54       7       -33
Working age population                                                             96         102     -16      -74      -64
Over 60 population                                                                 23          29      57       67       88
Urbanisation rate                                                                            14%     12%       7%       8%
Urban population                                                                  156         210     186       98       80
Household size                                                                   -0.26       -0.34   0.00     0.00     0.00
Urban households                                                                   52          82      60       32       26

CAGR (%)                                                        1990             2000        2010     2020     2030     2040
Population                                                                       1.0%        0.5%     0.4%     0.1%    -0.2%
Working age population                                                           1.2%        1.2%    -0.2%    -0.9%    -0.8%
Over 60 population                                                               3.2%        2.9%     4.1%     3.3%     3.2%
Urban population                                                                 4.3%        3.9%     2.5%     1.1%     0.8%
Household size                                                                  -0.7%       -1.0%     0.0%     0.0%     0.0%
Urban households                                                                 5.1%        5.0%     2.5%     1.1%     0.8%

Annual change (millions)                                        1990             2000        2010    2020     2030     2040
Population                                                                       11.5         6.7     5.4      0.7     -3.3
Working age population                                                            9.6        10.2    -1.6     -7.4     -6.4
Over 60 population                                                                2.3         2.9     5.7      6.7      8.8
Urban population                                                                 15.6        21.0    18.6      9.8      8.0
Urban households                                                                  5.2         8.2     6.0      3.2      2.6

Education                                                       1990             2000        2010      2020     2030     2040
Total population                                                1,148           1,264        1,330    1,385    1,391    1,359
Total working age population                                     724              819         921       905      830      766
Graduate ratio                                                  3.0%             3.6%        8.9%     14.0%    19.3%    25.3%
Graduates                                                        34.5            45.6        118.8    193.8    268.8    343.8
Non-graduates working age                                        689              774         802       711      562      422
Change graduates                                                                   11          73        75       75       75
Change non-grad' working age                                                       84          28       -91     -149     -139
Change graduates (%)                                                            32.4%       160.3%    63.1%    38.7%    27.9%
Change non-grad' working age (%)                                                12.2%        3.7%    -11.4%   -21.0%   -24.8%
Source: China NBS, US Census, J.P. Morgan Calculations




42
   Adrian Mowat                                               Emerging Markets Equity Research
   (852) 2800-8599                                            31 May 2011
   adrian.mowat@jpmorgan.com


Methodology –
  1. We adjust per capita GDP to today’s US$. We do this by inflating the historical per capita GDP by current deflator and converting to US$ using current
       exchange rate
     2.       The centered moving average is calculated as the average of current year, previous two years and next two years real GDP growth


Figure 60: Lessons from other countries - Real GDP growth (5-year centered moving average %) vs. adjusted per capita GDP (US$)
  Real GDP grow th 5-y ear centered moving average %                                                              China (1978-2010)       US (1948-2010)            Japan (1956-2010)
   16
                                                                                                                  Taiw an (1960-2010)     South Korea (1960-2010)   Hong Kong (1963-2010)

   14                                                                                                             Singapore (1960-2010)   Poly . (Curve fit)


   12


   10


     8


     6


     4


     2


     0


    -2
          0                                       10000                                20000                        30000                 40000                     50000

                                                                                                 Adjusted GDP per capita US$

Source: J.P. Morgan economics. Note The fitted curve excludes Singapore data points.


                                                                                                                                                                                   43
   Adrian Mowat                                 Emerging Markets Equity Research
   (852) 2800-8599                              31 May 2011
   adrian.mowat@jpmorgan.com




Figure 61: Real GDP growth %oya (five-year centered moving average) over time
  Real GDP growth 5-y ear centered moving average %
   16
                                                                                                    US                   Japan                 Hong Kong            Singapore

                                                                                                    China                South Korea           Taiw an
   14



   12



   10



     8



     6



     4



     2



     0



    -2
          52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10
Source: J.P. Morgan economics




   44
   Adrian Mowat                                       Emerging Markets Equity Research
   (852) 2800-8599                                    31 May 2011
   adrian.mowat@jpmorgan.com




Figure 62: Relative growth and wealth of provinces in China
                                                                                                                                                 2010
                                                                                                                                                 GDP
                                                                                                                             Province          Growth
                                                                                                                             Tianjin            17.4%
                                                                                                                             Chongqing          17.1%
                                                                                                              Heilongjiang   Hainan             15.8%
                                                                                                                             Qinghai            15.3%
                                                                                                                             Sichuan            15.1%
                                                                                                              Jilin
                                                                                                                             Inner M ongolia    14.9%
                                                                                 Inner Mongolia
                                                                                               Liaoning                      Hubei              14.8%
                                                                                            Beijing                          Hunan              14.5%
                                 Xinjiang
                                                                                                 Tianjin                     Anhui              14.5%
                                                                                         Hebei                               Shaanxi            14.5%
                                                                      Ningxia Shanxi Shandong                                Zhejiang           11.8%
                                                                                                                             Gansu              11.7%
                                                  Qinghai
                                                                 Gansu       Henan                  Jiangsu                  Xinjiang           10.6%
                                                                      Shaanxi
                                                                                                                             Beijing            10.2%
                                                                                                               Shanghai
                           Tibet                                                                  Anhui                      Shanghai            9.9%
                                                                                  Hubei
                                                              Sichuan                                      Zhejiang
                                                                        Chongqing
                                                                                            Jiangxi
                                                                                 Hunan
   GDP per capital (RMB)
                                                                      Guizhou                      Fujian
         60,000 – 80,000

         40,000 – 60,000                                    Yunnan        Guangxi Guangdong
         20,000 – 40,000

         0 – 20,000
                                                                               Hainan

Source: CEIC, J.P. Morgan’s Hands of China Team




                                                                                                                                                        45
   Adrian Mowat                                      Emerging Markets Equity Research
   (852) 2800-8599                                   31 May 2011
   adrian.mowat@jpmorgan.com




Figure 63: Real GDP growth vs. Average CPI in the previous decades
  Real GDP grow th %                                                                    China (1991 - 2001)
                                           China (2001 - 2010)
   12




   10




     8

                                                                                                                                 China (1981 - 1990)



     6




     4


                                                                                                                   China       US              Japan

                                                                                                                   Taiw an     South Korea     Hong Kong
     2
                                                                                                                   Singapore



     0
         -1                    1                3                5               7                 9          11   13          15                17        19
                                                                                           Av erage CPI %


Source: J.P. Morgan economics, Bloomberg




   46
   Adrian Mowat                                                 Emerging Markets Equity Research
   (852) 2800-8599                                              31 May 2011
   adrian.mowat@jpmorgan.com




Figure 64: Intensity of cement use; per-capita consumption of cement (tonnes) vs. adjusted per-capita nominal GDP
                                                                                                                                                            Russia (1991-2009E)
   Cement consumption per capita (tonnes)
                                                                                          1997: per capita cement consumption peaked in Korea               Brazil (1985-2009E)
  1.4
                                                                                                                                                            India (1985-2009E)
                                         China 2010 E
                                                                                                                                                            China (1985-2010E)
                                                                                                 1993: per capita cement consumption peaked in Taiwan
                                                                                                                                                            US (1930-2008)

  1.2                                    China 2009                                                                                                         UK (1985-2009E)
                                                                                                                                                            Germany (1985-2009E)
                                                                                                                                                            Japan (1985-2009E)
                                                                                                                                                            Taiwan (1985-2009)
  1.0                                                                                                                                                       South Korea (1985-2009E)
                                                                                                                                                            Mexico (1985-2009E)
                                                                                                   S. Korea 2009E

  0.8
                                                                                                                                                                             Japan 2009E



  0.6

                                                                                                                                                                                   Germany 2009E
                                        Russia 2009E                                                    Taiwan 2009
                     Mexico 2009E
  0.4




  0.2
                                                                    Brazil 2009E
                                                                                                                                                                                                   US 2008
                                                                                                                                                 UK 2009E
                  India 2009E
  0.0
        0                         6000                        12000                        18000                       24000                 30000             36000                   42000           48000
                                                                                                                            GDP per capita (USD)

Source: US Geological Survey and J.P. Morgan estimates. Note: The GDP per capita is restated for today’s dollars by adjusting the deflator series.




                                                                                                                                                                                                               47
   Adrian Mowat                                                  Emerging Markets Equity Research
   (852) 2800-8599                                               31 May 2011
   adrian.mowat@jpmorgan.com




Figure 65: Intensity of steel use; per-capita consumption of steel (lbs) vs. adjusted per-capita nominal GDP
  Per capita consumption of steel (lbs)
                                                                                                                                                            South Korea (1970 - 2009E)
   3,000                                       1993: per capita steel consumption peaked in Taiwan
                                                                                                                                                            United States (1950 - 2009E)

                                                                                                                                                            Taiwan (1977 - 2009E)
                                                                                           2008: per capita steel consumption peaked in Korea
                                                                                                                                                            Japan (1956 - 2009E)
   2,500
                                                                                                                                                            Germany (1968 - 2009E)

                                                                                                                                                            China (1983 - 2009E)

   2,000                                                                                                      S. Korea 2009E                                India (1978 - 2009E)




   1,500                                                                                            Taiwan 2009E                                            Japan 2009E




   1,000

                                                    China 2009E
                                                                                                                                       Germany 2009E
        500
                                                                                                                                                       U.S. 2009E


                                    India 2009E
           0
                0                 5,000                10,000                 15,000                20,000                 25,000   30,000   35,000      40,000      45,000         50,000

                                                                                                       GDP per capita (US$)
Source: CRU and J.P. Morgan estimates. Note: The GDP per capita is restated for today’s dollars by adjusting the deflator series.




   48
   Adrian Mowat                                           Emerging Markets Equity Research
   (852) 2800-8599                                        31 May 2011
   adrian.mowat@jpmorgan.com




Figure 66: Per-capita consumption of oil (barrels per day per 1000 population) vs. adjusted per-capita nominal GDP

        Barrels per day per 1000 population
  80
                      Russia (1991-2009)
                      Brazil (1982-2009)
                      India (1965-2009)
                      China (1978-2009)
                      US (1965-2009)
                      UK (1965-2009)
                      Germany (1968-2009)
  60                  Japan (1965-2009)                                    S. Korea 2009
                      Taiwan (1965-2009)
                      South Korea (1965-2009)
                      South Africa (1965-2009)                                                                                                                         US 2009
                                                                                                                                                     Japan 2009

                                                                                           Taiwan 2009

  40



                     Russia 2009




  20
                                                                                                                                   UK 2009


                                                                                                                                                        Germany 2009

                                                             Brazil 2009
                      China 2009                South Africa 2009
    0
         0                       6000                     12000                  18000              24000                 30000              36000         42000                 48000

                                                                                                            GDP per capita (USD)

Source: BP Statistical Review of World Energy June 2010




                                                                                                                                                                                         49
   Adrian Mowat                                                Emerging Markets Equity Research
   (852) 2800-8599                                             31 May 2011
   adrian.mowat@jpmorgan.com




Figure 67: Total energy consumption in China higher than in the US but low at a per-capita level; per-capita consumption of primary energy (tonnes of oil equivalent) vs. per adjusted capita
nominal GDP
      energy consumed per capita (tonnes of oil equivalent)

  9            Brazil (1982-2009)
               India (1965-2009)
               China (1978-2009)
               South Africa (1965-2009)
  8            US (1965-2009)
               UK (1965-2009)
               Germany (1968-2009)
               Japan (1965-2009)                                                                                                                                                                     US 2009
  7
               Taiwan (1965-2009)
               South Korea (1965-2009)                                 S. Korea 2009
               Russia (1991-2009)
  6
                                          Russia 2009
                                                              Taiwan 2009

  5
                                                                                                                                                                                                 Japan 2009


  4

                       South Africa 2009

  3
                                                                                                                                                                                                 Germany 2009

  2                                                                                                                                                                      UK 2009



  1                                                               Brazil 2009


                                                 China 2009
                    India 2009
  0
       0                         6000                         12000                        18000                        24000                         30000                        36000                        42000                         48000
                                                                                                                                GDP per capita (USD)

Source: BP Statistical Review of World Energy June 2010. Note: Primary energy comprises commercially traded fuels only. Excluded, therefore, are fuels such as wood, peat and animal waste. Also excluded are wind, geothermal and solar power generation.




   50
   Adrian Mowat                                                  Emerging Markets Equity Research
   (852) 2800-8599                                               31 May 2011
   adrian.mowat@jpmorgan.com




Figure 68: Mobile subscription per 100 people vs. adjusted per capita nominal GDP
        Mobile subscription per 100 people                                                                                                                           US (1989 - 2009)
        180                                                                                                                                                          UK (1989 - 2009)
                    Russia 2009                                                                                                                                      Brazil (1992 - 2009)
                                                                                                                                                                     India (1995 - 2009)
                                                                                                                                                                     China (1992 - 2009)
        160                                                                                                                                                          South Korea (1989 - 2009)
                                                                                                                                                                     Taiwan (1989 - 2009)
                                                                                  Taiwan 2009                                                                        Russia (1993 - 2009)

        140
                                                                                                                                                           UK 2009

        120
                                                                                                             South Korea 2009

        100
                                                                                                                                                         US 2009

          80
                    India 2009
                                                     Brazil 2009
          60



          40                                                    China 2009



          20



            0
                0                   5,000                 10,000                 15,000             20,000       25,000         30,000       35,000      40,000          45,000           50,000
                                                                                                                                  GDP per capita (USD)
Source: Bloomberg. Note: Subscriber data is not adjusted for individuals using multiple SIM cards




                                                                                                                                                                                                   51
   Adrian Mowat                                                Emerging Markets Equity Research
   (852) 2800-8599                                             31 May 2011
   adrian.mowat@jpmorgan.com




Figure 69: China is already the world’s largest car market…but still low per 1000 people; passenger cars per 1000 people vs. adjusted per capita nominal GDP
        Passenger cars per 1000 population                                                                                                                                                              US 2007
  900             US (1930-2007)
                  Germany (1995-2006)
                  Italy (1995-2006)
  800             UK (1995-2006)
                  Japan (1970-2008)
                  South Korea (1970-2008)
                  India (2001-2008)
  700             China (1991-2008)



                                                                                                                                                                                Italy 2006
  600
                                                                                                                                                                                                       Germany 2006


  500




  400                                                                                                                                                                                        UK 2006

                                                                                                     Korea 2008

  300




               India 2008 (8)
                                   China 2014 E                                                                                                                                                              Japan 2008
  200



                  China 2008
  100




    0
         0                                         10000                                         20000                                         30000                                         40000                        50000
                                                                                                                                                 GDP per capita (USD)

Source: J.P. Morgan estimates, Eurostat, US Department of Energy. Note: China 2014 forecast from J.P. Morgan China Autos team. GDP per capita data is adjusted for inflation.




   52
   Adrian Mowat                                               Emerging Markets Equity Research
   (852) 2800-8599                                            31 May 2011
   adrian.mowat@jpmorgan.com




Figure 70: Share of global nominal GDP (%) – China’s share is 10% in 2010 and forecast to be 17% in 2020

   100%
                                                                                       ROW
    90%


    80%                                                                                                                                                                                 Other EM
                                   Japan
    70%


    60%

                                                                  Developed Europe
    50%


    40%


    30%
                                                                                          US (2000: 31%, 2010: 24%; 2020: 19%)
                                                                                                                                                                                                                              India
    20%
                                                                                                                                                                            Brazil                                           Russia
    10%
                                                                                                                                                                  China (2000:4%, 2010: 10%; 2020F: 17%)
      0%
           2000        2001         2002        2003        2004         2005        2006        2007         2008        2009         2010        2011        2012         2013        2014        2015         2016        2017        2018        2019   2020

Source: J.P. Morgan economics, IMF. Note: Regions follow MSCI country definitions. The projections assume nominal GDP growth at potential real GDP growth and central banks inflation target. To compute FX for periods beyond 2011, we assume the
normalization of REER over the forecasted period.




                                                                                                                                                                                                                                                      53
                                                                                                            Emerging Markets Equity
                                                                                                            Research
                                                                                                            23 February 2012




EM equities as China slows
Managing the downside risk if China continues to slow


 Hard landing is an emotive term in China. Despite frequent use there is                                   Emerging Markets Equity Strategy
  no commonly accepted definition. In this report we consider the                                           Adrian Mowat
                                                                                                                              AC

  possibility of a decline in Chinese steel and cement in 2012 relative to                                  (852) 2800-8599
  2011. This is a measurable outcome and avoids the debate on the                                           adrian.mowat@jpmorgan.com
  accuracy of FAI and GDP data.                                                                             J.P. Morgan Securities (Asia Pacific) Limited

                                                                                                            Ben Laidler
 Residential construction accounts for a quarter of steel demand.                                          (1-212) 622-5252
  Seasonally adjusted housing starts declined by 42% in December.                                           ben.m.laidler@jpmorgan.com
  Residential construction starts exceeded sales by 50% in 2011. Either                                     J.P. Morgan Securities LLC
  sales need to rise or starts fall. The latter is happening. Cement and
                                                                                                            David Aserkoff, CFA
  steel production are 7% and 20%, respectively, below their 2011 peak.                                     (44-20) 7325-1775
  The lesson from property market corrections in other countries is                                         david.aserkoff@jpmorgan.com
  sobering (see page 63). China is unique in that policy makers attempt to                                  J.P. Morgan Securities Ltd.
  control prices. It is open to debate whether households will return to the                                Rajiv Batra
  property market when policy changes. This report will be successful if                                    (91-22) 6157-3568
  investors consider the wide range of potential outcomes.                                                  rajiv.j.batra@jpmorgan.com

                                                                                                            J.P. Morgan India Private Limited
 How realistic is a forecast of a decline in steel and cement production? It
                                                                                                            Sanaya Tavaria
  is reasonable, in our view. Assuming an optimistic 9% growth in non-
                                                                                                            (1-212) 622-5469
  residential steel and cement demand, a 30% decline in residential                                         sanaya.x.tavaria@jpmorgan.com
  construction starts would result in a decline in steel and cement                                         J.P. Morgan Securities LLC
  production. Please see page 62 for detailed calculations.
                                                                                                            Prateek Parekh
 Is a weak Chinese economy consistent with a bullish view on EM? The                                       (91-22) 6157-3277
                                                                                                            prateek.parekh@jpmorgan.com
  first-order effects on economic growth (China is 30% of EM GDP and
                                                                                                            J.P. Morgan India Private Limited
  40% of 2012 global GDP growth) and EM EPS are negative. MSCI EM
  materials’ 34% revenue and 48% EPS is from Iron ore and Steel (see                                        Derivatives Strategy
  page 66). EM equities and industrial metals are correlated; the R2 is                                     Tony SK Lee
                                                                                                                             AC


  0.82. But the second-order impact of lower commodity prices is                                            (852) 2800-8857
                                                                                                            tony.sk.lee@jpmorgan.com
  positive for the majority of economies and companies as it boosts
                                                                                                            J.P. Morgan Securities (Asia Pacific) Limited
  real incomes and margins.

 Timing this call is difficult. Data is distorted by Chinese New Year and
  markets are very sensitive to government policy. The extreme levels of
  the 2008 GFC are used as stress points for testing the hard-landing
  hedges. Based on our stress point assumptions, CNY and TWD puts
  have the highest bang for the buck. Across different asset classes, FX
  puts are in general much more cost effective than sovereign CDS
  spreads, equity puts and commodity puts (see page 67).

 The risks to our view include a rapid increase in new loans (possibly
  following sharp reductions in RRRs) and underestimating the willingness
  and ability of households to buy property.

See page 98 for analyst certification and important disclosures, including non-US analyst disclosures.
J.P. Morgan does and seeks to do business with companies covered in its research reports. As a result, investors should be aware that the
firm may have a conflict of interest that could affect the objectivity of this report. Investors should consider this report as only a single factor in
making their investment decision.

                                                                                                                    www.morganmarkets.com
Adrian Mowat                                                 Emerging Markets Equity Research
(852) 2800-8599                                              23 February 2012
adrian.mowat@jpmorgan.com




                                                             Table of Contents
                                                             Has a hard landing started? ..................................................56
                                                             A first-order negative ............................................................................................57
                                                             Second-order benefits............................................................................................58
                                                             What is priced in? .................................................................................................59
                                                             Construction activity…the data so far for starts, steel and cement...........................60
                                                             Residential starts and declining steel and cement
                                                             production...............................................................................62
                                                             The US housing market .........................................................63
                                                             EM equities exposure to commodities .................................65
                                                             Managing Chinese growth risk using derivatives ...............67
                                                             Risks of common option strategies......................................72
                                                             MSCI EM Materials valuation summary ................................73
                                                             Appendix .................................................................................75
                                                             China property data: Insights.................................................................................79
                                                             Seasonality............................................................................................................80

Figure 71: Cement consumption per capita: China may follow the path of Korea, Taiwan and Spain
                                                                                                                                                                Russia (1991-2010)
   Cement consumption per capita (tonnes)
                                                                                                                                                                Brazil (1985-2010)
 1.7
                                                                                                                                                                India (1985-2010)

                                                                                                                                                                China (1985-2010)
                                                      1997: per capita cement consumption peaked in Korea
                                    China 2012E                                                                                                                 US (1930-2010)
 1.5
                                                                                                                                                                UK (1985-2010)
                                                                              1993: per capita cement consumption peaked in Taiwan
                                    China 2011                                                                                                                  Germany (1985-2010)

                                                                                                                                                                Japan (1985-2010)
 1.3
                                                                                                                                                                Taiwan (1985-2010)

                                                                                                                                                                South Korea (1985-2010)

 1.1                                                                                                                                                            Mexico (1985-2010)

                                                                                               S. Korea 2010                                                    Spain (1985-2010)
                                                                                                                       Peak for Spain in 2006
                                                                                                                                                                Indonesia (1985-2010)

 0.9                                                                                                             Spain 2010
                                                                                                                                                                Hong Kong (1990 -2010)
                                                                                                                                                        Japan 2009


 0.7


                                Russia 2010                                                                                                                   Germany 2010
 0.5                                                                                Taiwan 2010
                 Mexico 2010

 0.3



 0.1
                       Indonesia 2010                 Brazil 2010
                                                                                                                                                                                          US 2010
                India 2010                                                                                            UK 2010
-0.1
       0                     6000                 12000                 18000                   24000                   30000                   36000             42000                       48000

                                                                                                        GDP per capita (USD)

Source: J.P. Morgan calculations




                                                                                                                                                                                                    55
Adrian Mowat                          Emerging Markets Equity Research
(852) 2800-8599                       23 February 2012
adrian.mowat@jpmorgan.com



Has a hard landing started?
“Hard landing” is an emotive term in China. Despite                 Figure 72: Area under construction trending down
frequent use there is no commonly accepted definition.               320                 Construction activit y
In this report we consider the possibility of a decline
                                                                                         Steel-residential production, seasonally
in Chinese steel and cement production in 2012                       270                 adjusted, 3mmva
relative to 2011. This is a measurable outcome and                                       Cement Residential construction,
avoids the debate on the accuracy of FAI and GDP data.               220                 seasonally adjusted, 3mmva
Consider this as a period of consolidation. On page 62 we
explain why a decline in steel and cement production is              170
reasonable.
                                                                     120
Cement production is 7% below its seasonally adjusted
peak. The annualized rate of steel production peaked at                  70
740M tonnes; it is now 610M tonnes. Seasonally                            Jan-05     Jan-06      Jan-07       Jan-08       Jan-09      Jan-10      Jan-11
adjusted housing starts declined by 42% in                          Source: Bloomberg. Note: Numbers are rebased to 100 as of 2005
December. Housing starts are now equivalent to the
average level of sales in 2H11. The burden of proof                 Figure 3: Spanish steel demand, cement demand and housing
should be on those that forecast a recovery. Despite                construction starts
numerous recent examples of property market corrections             200               Spain (Construction Starts)              Spain (Steel Demand)
many are confident that the economic impact on China                                  Spain (cement Demand)
will be modest. The short history of China’s property
                                                                    150
market means that both bulls and bears are speculating.
This report will be successful if investors consider the
wide range of potential outcomes.                                   100


In this report we compare recent corrections in China’s               50
property market with previous property corrections in the
US and Spain. Construction starts in Spain peaked in
                                                                         0
2006. By 2010, construction starts, steel demand and                         1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
cement demand had declined 88%, 56% and 45%,
                                                                    Source: Bloomberg, Note: Annual data rebased to 100 as of 1999. Numbers
respectively, from their 2006 peak.
                                                                    Figure 73: China property prices
Property prices in China are high relative to income. In
                                                                     350
China’s housing market: Wide regional differences in
manageable overall price adjustment, Zhu et al, 4
                                                                     300
November 2011, our China economists calculate an
average house price to income ratio of 10.6x in 2010.
                                                                     250
In many major cities the ratio exceeds 15x (see Table
44). To avoid further inflating prices the government                200
policy is to control prices. The policy is working, with
both price and sales volume declining in 2H11. Chinese               150
households are now in control of the market. Falling
prices and volumes plus ongoing anti-speculative                     100
measures are likely to discourage buyers. Will this                    May-04         Aug-05        Nov-06        Feb-08       May-09        Aug-10         Nov-11
change if government policy changes? There is no                    Source: Centaline leading Index. Note: The index is the average of property prices of
guarantee that it will. Note the government has been                Shanghai, Beijing, Guangzhou, Shenzen and Tianjin.
unable to revive the A-share market since the 2007
bubble.




56
Adrian Mowat                           Emerging Markets Equity Research
(852) 2800-8599                        23 February 2012
adrian.mowat@jpmorgan.com


Is China different? Yes, in that its property bubble is a            overconfidence and inward-looking communist party
function of savings looking for return rather than the               under-reacting to economic data.
debt-driven markets of developed countries. But the
source of capital driving the market does not change the             Figure 74: China’s credit-to-GDP ratio
likely outcome. The evidence from Asian housing
                                                                      180%                           Credit/GDP ratio         94-08 trend
bubbles is that savings-driven property markets, where
loan-to-value ratios are low, generate large bubbles and              160%
subsequent busts. Japan, Korea and Taiwan suffered
housing bubbles in the late 1980s/early ‘90s. In Hong                 140%
Kong property prices fell 70% from 1997 to 2003. All
these bubbles occurred after periods of strong economic               120%
growth. The low real return on cash was a key                         100%
justification for high prices.
                                                                          80%
Typically commentators underestimate the impact of the
property market on an economy. In China, primary                          60%
market transactions dominate, thus their economic impact                        94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11
is higher than in developed economies. A strong                      Source: PBoC, total social financing ex equity
property market converts household savings into
economic activity and local government revenue. The                  Figure 75: Credit to GDP and GDP per capita
second-order effects include investment in heavy
industry capacity and infrastructure spending (partly
financed by land sales).

Can the economy slow down in a leadership transition
year? At the March 2013 NPC meeting Li Keqiang is
expected to formally replace Wen Jiabao as State Council
premier. Xi Jinping will replace Hu Juntao PRC
President. A popular theory is that with the transition
from the fourth to fifth generation of leaders, policy will
ensure steady economic growth. But stable growth is
always the objective. It is difficult to think of a
government globally that does not strive for this goal. An
                                                                     Source: IMF. 1 - for China includes ‘disintermediated’ credit
alternative analysis is that the main goal during the
protracted leadership change process is to present an
image of unified party agreeing smooth transition. This is           A first-order negative
challenging with seven of the nine members of the                    A decline in steel and cement demand/production implies
standing committee and some 70% of key senior                        a significant economic slowdown. China is 30% of EM
positions changing.                                                  GDP and at current forecasts is 40% of 2012 global
                                                                     growth. Risk assets, particularly in EM, may suffer.
China is unique in that its economic track record is
strong. As was the case with Japan and the Asian Tigers              China dominates global commodity demand (see Table
in 1990s this may lead to overconfidence. Property                   26). Confirmation of the slowdown should be a catalyst
market corrections have a large economic impact that                 for a correction in commodity prices. Again this is a risk
usually requires a response greater than “fine tuning”.              for EM equities. The correlation between EM equities
The PBoC’s M2 growth target for 2012 is 14%, similar to              and commodities is 0.82.
2011 13.6%oya. A larger monetary stimulus is possible
through reductions in reserve ratios. A modest fiscal                Table 26: China’s share of global commodity demand
stimulus is planned with the deficit increasing from                               Aluminum          Nickel       Copper         Iron ore      Coal    Oil
Rmb500billion to Rmb1trillion. Total tax revenue ex                  2015E            48               41           42              52          32     11
property sales was 19% of GDP in 2011. With credit-to-               2010             40               33           37              53          34     10
GDP ratios elevated, policymakers maybe reluctant to                 2005             22               15           23              36           6     8
expand the fiscal stimulus. Tax revenue grew at 26% in               2000             13                            12              20          1*     7
2011, but the pace of growth slowed in 4Q11. If activity             Source: J.P. Morgan. Note: Coal includes thermal + coking coal. *Data for 2001.

remains weak, tax revenue growth may slow further.
China may run the risk of a combination of


                                                                                                                                                        57
Adrian Mowat                                 Emerging Markets Equity Research
(852) 2800-8599                              23 February 2012
adrian.mowat@jpmorgan.com


Table 27: Correlation of MSCI EM and S&P GSCI Industrial Metals            Second-order benefits
                             Correlation            R-squared
                                                                            Manufacturing margin boost as input prices fall
Daily over 2m                   0.64                   0.41
1m over 3yrs                    0.82                   0.67                 QE without inflation...QE2 was synchronized with
1m over 5 yrs                   0.71                   0.51
QoQ over 10 yrs                 0.68                   0.46                  rising commodity demand as Chinese construction
Source: MSCI, Datastream.
                                                                             activity accelerated and DM growth expanded. The
                                                                             initial fundamental increase in commodity prices may
Figure 76: Correlation of MSCI EM with S&P GSCI Industrial                   have been amplified by those fearing the debasement
Metals- Weekly returns over three years rolling                              of paper money.
 0.8
 0.7
                                                                            Boost to real household income.
 0.6                                                                        Reinforce deflationary trend increasing monetary
 0.5
                                                                             policy flexibility.
 0.4
 0.3                                                                        Reduced current account deficits in Turkey and India.
 0.2
 0.1                                                                       The intensity of commodity use has increased sharply.
   0                                                                       Commodity consumption grew in the high teens in the
-0.1                                                                       last decade. In 2010, China accounted for over half of the
-0.2                                                                       world’s iron ore demand.
   Feb-95 Feb-97 Feb-99 Feb-01 Feb-03 Feb-05 Feb-07 Feb-09 Feb-11

Source: Datastream, MSCI.                                                  Figure 77: CPI minus PPI – China, India and Brazil

AUD and BRL terms of trade                                                   15                          India               China                  Brazil
The Australian dollar and Brazilian Real would face the                      10
combination of weaker terms of trade and lower interest
rate differentials. These current account deficit countries                     5
are beneficiaries of significant investment flows. A
                                                                                0
reversal in these flows tends to lead to sharp corrections.
                                                                                -5
Direct impact on MSCI EM EPS
                                                                            -10
The direct impact on EPS is potentially via commodity
companies plus property and building material stocks in                     -15
China. To calculate the impact on EM we calculate the                                 05       06        07        08        09           10         11
contribution by commodity of revenue and earnings for
                                                                           Source: J.P. Morgan economics.
MSCI materials sector.
                                                                           Figure 78: CPI minus PPI – US and EMU
Steel and industrial metals contributed 10% of MSCI EM
                                                                                 20
2011 EPS. Just iron ore and copper are 6% and 1% of                                                                     US                          EMU
MSCI EPS respectively. Current analysts’ forecasts are                           15
for a 12% and 23% decline in iron ore and copper EPS in
                                                                                 10
2012. Chinese cement and homebuilders contribute 1.8%
of MSCI EM EPS                                                                       5

                                                                                     0
Please see page 65 for a detailed calculation of the
source of revenue and profits by commodities of MSCI                                 -5
EM materials.
                                                                                -10

                                                                                -15
                                                                                          05        06        07        08           09        10            11
                                                                           Source: J.P. Morgan economics.




58
Adrian Mowat                                              Emerging Markets Equity Research
(852) 2800-8599                                           23 February 2012
adrian.mowat@jpmorgan.com


Figure 79: US real incomes compressed by inflation                                         Figure 80: Approaching mid-range valuations - China property
   %ch, 3-mo annualized                                                                    developers’ discount to NAV time series (ex Vanke and COLI)
  10
                                                   Compensation                             60%

   5                                                                                        40%

   0                                                                                        20%               +2 Std dev

                                                 PCE prices                                  0%              +1 Std dev
   -5
                                                                                           -20%
 -10
                                                                                           -40%
 -15                                                                                                         -1 Std dev Long Term Avg: -
   Jan 09        Jul 09       Dec 09        Jun 10       Dec 10       Jun 11      Dec 11   -60%

Source: J.P. Morgan economics, November 2011.
                                                                                                             -2 Std dev
                                                                                           -80%




                                                                                                   May 03




                                                                                                                                         Feb 07


                                                                                                                                                       May 08




                                                                                                                                                                                        Feb 12
                                                                                                            Aug 04


                                                                                                                          Nov 05




                                                                                                                                                                   Aug 09


                                                                                                                                                                               Nov 10
What is priced in?                                                                                                                 -
                                                                                           Source: Bloomberg, J.P. Morgan estimates
Chinese property developers are not pricing in a
correction. The discount to NAV of property developers                                     Figure 81: MSCI EM materials and China materials relative to
is near the long-term average.                                                             MSCI EM
                                                                                           120                        MSCI EM Materials                         MSCI China Materials
Chinese steel and industrial metals are also vulnerable.
Steel companies are at 10-year average valuations. In                                      110
contrast, iron ore companies trade at a meaningful
                                                                                           100
discount to average. Notably Vale is one standard
deviation below its long-term average valuation.                                             90

Table 28: MSCI EM valuation by commodity                                                     80
                                                  Valuation Score
Commodity                                                                                    70
                                           Average                     Median
Aluminum                                     0.7                        (0.1)
                                                                                             60
Commodity Chemicals                          0.6                         0.5
                                                                                              Feb 09                          Feb 10                            Feb 11                      Feb 12
Construction Materials                       0.1                         0.1
Diversified Chemicals                       (0.1)                       (0.0)              Source: MSCI, Datastream, 21 February 2012. Note: Index rebased to 100 as of 20
Diversified Metals & Mining                  0.1                        (0.0)              February 2009
Fertilizers & Agricultural Che              (0.5)                       (0.8)
Forest Products                             (0.5)                       (0.5)              Figure 82: Iron Ore and Copper prices
Gold                                        (0.9)                       (0.9)
Industrial Gases                            (0.1)                       (0.1)                300                                                  Iron Ore              Copper
Paper Packaging                              1.1                         1.1
Paper Products                              (0.6)                       (0.7)                250
Precious Metals & Minerals                   0.1                         0.1
Specialty Chemicals                         (0.2)                        0.0                 200
Steel                                        0.2                         0.1
Iron Ore                                    (0.5)                       (0.7)                150
Source: MSCI, Datastream, 20 February 2012. Note: Valuation score is average of
standard deviations from 10 year mean of 12 month forward PE and trailing PB.                100

Please see page 73 for valuation summary for MSCI EM                                          50
Material constituents.                                                                         0
                                                                                               Jan 07                Jan 08            Jan 09             Jan 10            Jan 11       Jan 12
                                                                                           Source: Bloomberg, 21 February 2012. Note: Prices rebased to 100 as of 01 January
                                                                                           2007.




                                                                                                                                                                                            59
Adrian Mowat                                     Emerging Markets Equity Research
(852) 2800-8599                                  23 February 2012
adrian.mowat@jpmorgan.com




Construction activity…the data so far for starts, steel and cement
This section includes actual and seasonally adjusted                           Figure 84: China seasonally adjusted construction starts and
residential construction starts and sales. Please see                          sales
page 80 for the seasonality calculation. On the                                         150           sqm mn
assumption that sales lag starts, construction starts for                                                      Residential Construction Starts, 3mmva       Residential Sales, 3mmva

                                                                                        130
December 2011 are plotted as December 2012.
                                                                                        110
In 2011 starts were 1,460M square meters versus sales of
                                                                                                 90
970M square meters. From June the range of seasonally
adjusted sales was 70 to 90M square meters. If                                                   70
construction starts are 80M square meters per month
in 2012, full year starts will be 35% below 2011 starts.                                         50
This is a sobering figure. In a normal inventory-
                                                                                                 30
correction production needs to drop below sales. Faced                                            Jan-06        Jun-07               Nov-08             Mar-10         Aug-11          Dec-12
with excess inventory/work in progress it is unreasonable
                                                                               Source: CEIC, December 2011. Note: Chart shows 3mmva, seasonally adjusted data
to forecast that developers will accelerate starts in 1H12.
                                                                               Figure 85: China, actual construction starts and sales
For construction starts to be flat in 2012 then the monthly
                                                                                        170           sqm mn
seasonally adjusted rate would need to increase by 75%                                                                      Residential Sales, 3mmva

from the December activity.                                                             150                                 Residential Construction Starts, 3mmva

                                                                                        130
CY11 steel production was 678M or 56.5M tonnes per
                                                                                        110
month. Residential construction was 25% of China’s
steel demand in 2010. Seasonally adjusted, steel                                                 90
production in December was 51million tonnes; 17%                                                 70
below the May peak of 60 million tonnes. Steel
production in January declined to 50million tonnes in                                            50
January and inventories increased. For 2012 steel                                                30
production to equal 2011production, the monthly rate                                              Jan-06        Jun-07               Nov-08             Mar-10         Aug-11          Dec-12
needs to increase by 14% to 57M tonnes per month.                              Source: CEIC, December 2011. Note: The charts shows actual 3mmva numbers

Figure 83: China 2010 steel demand end user share                              Figure 86: China’s steel production
   Others, 5% Transport,                                                                         65
                 11%
                                                                                Million Tonnes




   Home                                       Construction - Residential                                          Steel Production (seasonally adjusted, 3mmva)
 appliances,                                                                                     60
     3%                  Construction -       Construction - Non Residential                                      Steel production (actual, 3mmva)
                          Residential,                                                           55
                             24%              Infrastructure
                                              Machinery                                          50
       Machinery,
         20%                 Construction -   Home appliances
                                 Non                                                             45
                              Residential,    Transport
                                 29%                                                             40
                                              Others
 Infrastructure,
                                                                                                 35
       8%
                                                                                                  Mar-08       Oct-08           Jun-09           Feb-10     Sep-10          May-11      Jan-12
Source: J.P. Morgan, metals and mining team                                    Source: Bloomberg, CISA. Note: Since February 2009, the numbers are obtained from
                                                                               CISA




60
Adrian Mowat                            Emerging Markets Equity Research
(852) 2800-8599                         23 February 2012
adrian.mowat@jpmorgan.com




Cement demand in Spain in 2010 declined 56% from                      Figure 87: China’s cement production
its 2006 peak. In United States, demand declined 45%                  200                             Cement production (seasonally adjusted 3mmva)
from its peak. In China seasonally adjusted cement
                                                                      180                             Cement production (actual, 3mmva)
production was 170 million tonnes for December, 7%
below its October peak. See Table 43 for China cement                 160
production data.                                                      140

The growth rate for cement production is still in positive            120
territory. High developers’ inventory and work in                     100
progress is likely to lead to lower construction starts and
                                                                       80
activity. This would be evident in a decline in cement




                                                                                                           Dec-08




                                                                                                                                               Dec-09




                                                                                                                                                                                   Dec-10




                                                                                                                                                                                                                       Dec-11
                                                                                        Jun-08




                                                                                                                             Jun-09




                                                                                                                                                                 Jun-10




                                                                                                                                                                                                     Jun-11
                                                                               Mar-08




                                                                                                                    Mar-09




                                                                                                                                                        Mar-10




                                                                                                                                                                                            Mar-11
                                                                                                  Sep-08




                                                                                                                                      Sep-09




                                                                                                                                                                          Sep-10




                                                                                                                                                                                                              Sep-11
demand.
                                                                      Source: Bloomberg, December 2011.
China’s per-capita cement consumption was 1.52 tonnes
in 2011. The previous record for per-capita cement                    Figure 88: China seasonally adjusted cement production growth
demand was Korea in 1997 at 1.34 tonnes. Korean per
                                                                                                      Cement production data, 3mmva seasonally adjusted (%oya)
capita GDP in 1997 (in today's dollars) was four times                                                Cement production data,3mmva actual (%oya)
China today. Note the trend in Taiwan’s per-capita                     30
cement demand. Taiwan property prices peaked in 1994,
a year after the peak in cement demand (see Figure 71).                20
Taiwan is a reasonable analogy for China; high
household savings, current account controls, limited                   10
savings products and equivalent building standards. Note
that per-capita cement demand today in Taiwan is 65%                       0
below its 1993 peak.
                                                                      -10
                                                                        Mar-08                   Oct-08              Jun-09                Jan-10                Sep-10                 Apr-11                Dec-11
                                                                      Source: Bloomberg, December 2011.



                                                                      Figure 89: China seasonally adjusted Steel production growth
                                                                                                           Steel production data, 3mmva seasonally adjusted (%oya)
                                                                       40                                  Steel production data, 3mmva actual (%oya)

                                                                       30

                                                                       20

                                                                       10

                                                                           0

                                                                      -10

                                                                      -20
                                                                         Mar-08 Sep-08 Mar-09 Sep-09 Mar-10 Sep-10 Mar-11 Sep-11
                                                                      Source: Bloomberg, CISA. Note: Since February 2009, the numbers are obtained from
                                                                      CISA.




                                                                                                                                                                                                                         61
Adrian Mowat                           Emerging Markets Equity Research
(852) 2800-8599                        23 February 2012
adrian.mowat@jpmorgan.com



Residential starts and declining steel and cement production
Assumptions                                                          Is a 30% decline in construction starts reasonable?
 Cement production equals demand.                                   A 30% decline in construction starts is sobering but
                                                                     reasonable, in our view.
 Steel demand = production minus net exports. Net
  exports in 2011 were 3% of production.
                                                                      Our assumption of 9% steel and cement demand
 Residential sales in 2012 equal 2011 sales.                          growth excluding residential construction is
                                                                       optimistic, in our view.
 Steel and cement demand excluding residential
  construction and construction machinery (non-                       This level of construction starts is 25% above that of
  residential construction, transportation, machinery,                 December 2011.
  others) continues to grow at same rate at 2011 pace
                                                                      A 30% decline in construction starts would still result
  (9%oya). This is an optimistic assumption.
                                                                       55% excess supply by end 2012.
 To estimate residential construction activity or
                                                                      The sequencing is oversupply, price correction and
  area under construction we use the average of the                    then inventory correction. In the US a modest price
  last 12 months’ construction starts (the majority of
                                                                       decline resulted in a 25% annualized decline in starts
  cement and steel is used in the first 12 months of
                                                                       (see page 62).
  construction). Steel and cement production should
  increase at the same rate as increase in construction              Table 29: Starts vs. sales
  activity. But in 2011 residential construction activity            Year                       Starts (‘000 sqm)           Sales (‘000 sqm)
  increased by 22%oya yet steel and cement demand                    2004                            773,887                    338,199
  with 10%oya increase in steel and cement demand for                2005                            882,318                    497,945
  housing. There are three possible explanations for the             2006                            896,778                    543,921
                                                                     2007                           1,016,294                   691,038
  discrepancy in growth rates: (1) slowdown in                       2008                            798,891                    558,865
  infrastructure demand (note railway FAI decline                    2009                            924,635                    861,850
  23%); (2) local government meeting social housing                  2010                           1,294,679                   930,516
  starts targets but not following through with                      2011                           1,460,346                   970,303
                                                                     2012(E)                        1,020,000                   970,303
  construction; and (3) a slower pace of construction by
                                                                     Source: CEIC
  property developers due to weak demand and strained
  working capital.                                                   Table 30: China steel demand
 Demand for steel and cement used for residential                                                       2011       2012 Growth      2012 Steel
  construction declines at the same rate as decline in                                                                  rate          Demand
  construction starts. This is again an optimistic                   Construction - Residential           163          -30%             115
                                                                     Construction - Non Residential       197            9%             215
  scenario as developers are likely to slow construction             Infrastructure                        53            9%              58
  activity due to weak demand and shortage of working                Machinery                            136            9%             148
  capital. The steel and cement production data indicate             Home appliances                       19            9%              21
  that construction activity reduced in 2H 2011.                     Transport                             75            9%              82
                                                                     Others                                34            9%              37
 Steel demand ex housing=2011 steel demand*2012                     Total                                678            0%             676
  growth rate.                                                       Source: CISA, million tonnes

 2012 Total steel demand=2011 total steel demand.                   Table 31: China cement demand
Calculations                                                                                             2011       2012 Growth    2012 Cement
                                                                                                                        rate         Demand
 2012 residential construction steel demand=2012                    Commodity Housing                    474          -30%             330
   total steel demand minus steel demand ex housing.                 Commercial building                  144            9%             157
                                                                     Infrastructure                       891            9%             971
 2012 construction starts=2011 construction                         Other Cement Consumption             550            9%             600
  start*decline in steel production for residential                  Total                               2058            0%            2058
  construction.                                                      Source: CISA, million tonnes

Results
A 30% decline in construction starts would result in flat
steel and cement production in 2012.



62
Adrian Mowat                                                  Emerging Markets Equity Research
(852) 2800-8599                                               23 February 2012
adrian.mowat@jpmorgan.com

The US housing market
In this section, we review the sequence of the US
housing market correction and its impact on commodity
consumption. We accept there are many differences                                                         Figure 90: US housing market timeline
between the US and Chinese housing markets. One                                                                                                                      US Single Home Housing
                                                                                                                                                                     Sales (3mmva, SAAR, 160
important difference is that property prices relative to                                                                                                             LHS)
                                                                                                           120
income were lower in the US at their peak than they are                                                                                                              US Single Home Housing
in China. Figure 90 depicts the movements in housing                                                                                                                 Construction Starts
                                                                                                           100                                                       (3mmva, SAAR, LHS)
property market. The property market is analyzed by                                                                                                                  S&P 500, Shiller Index, 140
looking at phases of price movements. S &P 500, 20 city                                                      80                                                      (Seasonally adjusted,
                                                                                                                                                                     3mmva, RHS)
composite Shiller price index is used. Sales are primary
single family home sales. Starts are new construction                                                        60                                                                                  120
starts.
                                                                                                             40
Phase 1: Property price increases, starts and sales
                                                                                                             20                                                                                  100
consolidate (November 2002-April 2006)                                                                            03       04     05       06      07        08     09         10   11
Property prices increased 13% CAGR from end 2002 to                                                       Source: U.S. National Census bureau. Note: The starts, sales and prices are based to 100
mid 2006. The increase in starts and sales during the                                                     as of January 2003
same period were however only 1% and 3% respectively.
The peak in construction starts and sales occurred six and                                                Figure 91: US starts, sales and prices during the price
nine months respectively before property prices peaked.                                                   consolidation phase
                                                                                                            120                                      Sales            Starts             Price
Phase 2: Property price consolidates, construction
starts and sales decline (May 2006- July 2007)                                                              110
The seasonally adjusted construction starts and sales                                                       100
declined 25% and 21% CAGR during the period.
                                                                                                             90
Property prices decline 4% CAGR.
                                                                                                             80
Phase 3: Property prices decline, construction starts
                                                                                                             70
and sales decline rapidly (Aug 2007-May 2009)
The definition of property prices falling is consecutive                                                     60
months of decline in prices by more than 1% MoM. This                                                        50
period witnessed a deceleration in construction starts and                                                        Jul 05                Jan 06             Jul 06               Jan 07             Jul 07
sales by 40% and 33% CAGR respectively.                                                                   Source: US National census bureau. Note: Sales, Starts and prices are rebased to 100 as
                                                                                                          of July 2005.
The US economy is yet to recover from its May 09 lows.
New construction starts and sales are near their May 09
lows, at around 25% of their peak values.

Table 32: US housing economy: Key events
Event                                                             Date             Actual Values                                                                  Rebased Values
                                                                      Sales            Starts                                   Price              Sales              Starts              Price
Phase 1: Property price increases, starts and sales consolidate (November 2002-April 2006)
Sales (Peak)                                         Jul 05            1389            2054                                     191                 100                  100              100
Starts (Peak)                                        Jan 06            1174            2273                                     204                  85                  111              106
Price (Peak)                                         Apr 06            1123            1821                                     207                  81                   89              108
Phase 2 Property price consolidates, construction starts and sales decline (May 2006- July 2007):
One year after sales peaks                           Jul 06            965             1737                                     205                  69                  85               107
One year after, starts peaks                         Jan 07            891             1409                                     204                  64                  69               106
One year after price peaks                           Apr 07            887             1490                                     203                  64                  73               106
Price, Starts coming down                            Jul 07            778             1354                                     197                  56                  66               103
Phase 3: Property prices decline, construction starts and sales decline rapidly (Aug 2007-May 2009)
One year after price starts coming down              Jul 08            477              923                                     165                  34                  45                86
Sales, Starts Bottom                                 Apr 09            337              478                                     142                  24                  23                74
Price Bottoms                                        May 09            376              540                                     141                  27                  26                74
Current                                              Dec 11            307              689                                     138                  22                  34                72
Source: US National census bureau. Units:Vloume (‘000/unit). Note: Sales, refers to primary single family sales and starts refers to new construction starts.




                                                                                                                                                                                                  63
Adrian Mowat                           Emerging Markets Equity Research
(852) 2800-8599                        23 February 2012
adrian.mowat@jpmorgan.com




Impact of housing on steel and cement demand                         Figure 92: US steel and cement demand relation to construction
The direct impact of a decline in housing starts on US               starts
                                                                                                                                                              140
steel demand should be limited. But steel and cement
                                                                     120
production declined 57% and 37% annualized                                                                                                                    130
respectively from their peak by 2009. The 1.5-year lag
                                                                     100
between the peak in starts, and steel and cement                                                                                                              120
production peak is likely a function of the indirect impact
                                                                       80
of stress in the financial system (see Figure 92).                                                                                                            110

                                                                       60                                                                                     100
Did analysts forecast a US property bubble? No!                                           US Construction Starts
                                                                                          (3mmva, SAAR)
The actual FY07 EPS was 22% lower than analysts’                       40                 US Steel production (3mmva,                                         90
December estimates. This was the quarter when property                                    SA)
prices were declining. Even post the 4Q07 miss, analysts               20                 US Cement production                                                80
remained sanguine with a forecast of unchanged EPS in                          03   04       05       06       07      08       09       10       11
FY08. Actual FY08 EPS declined 30%. In January 2009,                 Source: Bloomberg. Note: All indices are rebased to 100 as of January 2003
analysts forecast a 40% decline FY09 EPS. The final
number was 20% below this forecast.                                  Figure 93: US homebuilders EPS estimates
                                                                     150                 2005           2006           2007            2008            2009
Lessons to be learnt from US housing bubble
                                                                     130
 Increasing property prices and receding demand
                                                                     110
   (sales) are the first signs of a property bubble.
                                                                       90
 Even during the period of price consolidation, sales
  and new construction starts decline. Decline in                      70
  construction starts was 25% annualized during the                    50
  price consolidation phase.
                                                                       30
 The National Association of Homebuilders’ Market                     10
  survey, equivalent of PMI, led the peak in sales by                          T-12 T-11 T-10 T-9 T-8 T-7 T-6 T-5 T-4 T-3 T-2 T-1                      T
  three months. This was too late to prevent a
  significant build of inventory.                                    Source: IBES, MSCI, Datastream

 Economic activity in US property market was                        Figure 94: NAHB market index vs. home sales
  significant. The peak-to-trough ratio of housing sales
  and starts in US was 4.5x and 4.8x respectively. The                                                         US Home Sales (3mmva, SAAR, LHS)
                                                                     130                                                                                       80
  current sales and starts are 78% and 70%,                                                                    NAHB Index (RHS)
                                                                                                                                                               70
  respectively, below their 2005-2006 peak.                          110
                                                                                                                                                               60
                                                                          90
                                                                                                                                                               50
                                                                          70                                                                                   40
                                                                                                                                                               30
                                                                          50
                                                                                                                                                               20
                                                                          30
                                                                                                                                                               10
                                                                          10                                                                                  0
                                                                               03   04       05       06       07      08       09       10       11
                                                                     Source: Note: NAHB market index is pushed 3 months ahead




64
Adrian Mowat                                        Emerging Markets Equity Research
(852) 2800-8599                                     23 February 2012
adrian.mowat@jpmorgan.com




EM equities exposure to commodities
Calculation:
Revenue contribution = (Revenue of each constituent of
MSCI EM materials sector * Free float Market Cap of                               Figure 95: MSCI EM sector weight
each constituent)/ Total MSCI EM Materials Free Float                              Utilities, 4                                                 Energy
Market Cap                                                                                        Telecom, 8           Energy, 14               Materials

Earnings contribution = (Net profit of each constituent                                                                                         Industrials
of MSCI EM materials sector)/ Total net profit of MSCI                                 Information
                                                                                                                                                 Consumer
EM Materials.                                                                          Technology,
                                                                                                                                                 Discretionary
                                                                                            13                                      Materials, 14Consumer
Table 33: Weight in MSCI EM materials and MSCI EM based on                                                                                       Staples
                                                                                                                                                 Healthcare
revenue and earnings contribution
                                                                                                                              Industrials, 7    Financials
                            MSCI EM Materials       MSCI EM Weight based
                             weight based on                 on                          Financials,                                            Information
                           Revenue    Earnings      Revenue     Earnings                     24                                                 Technology
                           contribut Contribut      contribu   Contributi                                                                       Telecom
                             ion         ion          tion         on
                                                                                                                              Consumer
Iron Ore                     15.8       34.8           2.2         5.5
                                                                                                                   Consumer Discretionary,      Utilities
Commodity Chemicals          16.2       13.7           2.2         2.2
                                                                                           Healthcare, 1           Staples, 8     8
Steel (manufacturer)         13.2       11.0           1.8         1.8
Gold, Silver                 11.0        7.9           1.5         1.3            Source: MSCI, Datastream
Construction Materials       10.1        4.6           1.4         0.7
Chemicals, Fertilizers,
Agriculture, Logistics           9.3        6.1        1.3         1.0
Copper                           6.0        9.0        0.8         1.4
Platinum                         3.7        2.4        0.5         0.4            Figure 96: MSCI EM earnings contribution
Nickel                           3.6        2.5        0.5         0.4                                                                          Energy
                                                                                   Information                                  Utilities, 3
Steel (Integrated)               3.4        2.2        0.5         0.4
                                                                                   Technology, Telecom,
Paper and Forest                                                                                                                                Materials
Products                         3.1        1.2        0.4         0.2
                                                                                        9          7
Zinc, Molybdenum,                                                                                                           Energy, 23          Industrials
Lead                             2.0        1.8       0.3         0.3
Aluminum                         1.4        1.0       0.2         0.2                                                                           Consumer
Power                            0.7        1.0       0.1         0.2                                                                           Discretionary
Coal                             0.5        0.7       0.1         0.1                                                                           Consumer
Total Material                   100        100       13.8        16.0                                                                          Staples
                                                                                                                                                Healthcare
Source: IBES, Datastream, Bloomberg
                                                                                       Financials,                          Materials, 15       Financials
Table 34: MSCI EM GICS weight based on revenue and earnings                                27
contribution                                                                                                                                    Information
                                                                                                                                                Technology
                                  MSCI EM weight        MSCI EM weight                                                                          Telecom
                                 based on Revenue      based on Earnings                                        Consumer
                                                          contribution                                                                          Utilities
                                                                                                    Consumer Discretionary,
Energy                                 14                      23                      Healthcare, 1 Staples, 4    7        Industrials, 6
Materials                              14                      15
Industrials                             7                       6                 Source: MSCI, IBES, Datastream
Consumer Discr.                         8                       7
Consumer Staples                        8                       4
Healthcare                              1                       1
Financials                             24                      27
Information Technology                 13                       9
Telecom                                 8                       7
Utilities                               4                       3
Source: MSCI, IBES, Datastream




                                                                                                                                                              65
Adrian Mowat                                                             Emerging Markets Equity Research
(852) 2800-8599                                                          23 February 2012
adrian.mowat@jpmorgan.com




Figure 97: MSCI EM materials breakdown by revenue
                            Iron Ore                                                             Commodity Chemicals                                                      Steel (mazufacturer)
                            Gold, Silver                                                         Construction Materials                                                   Chemicals, Fertilizers, Agriculture,Logistics
                            Copper                                                               Platinum                                                                 Nickel
                            Steel (Integrated)                                                   Paper azd Forest Products                                                Zinc, Molybdenum, Lead
                                                                          Chemicals, Fertilizers,
                                                                         Agriculture,Logistics, 9.3


                             Construction Materials,
                                     10.1
                                                                                                                                                                                         Paper azd Forest Products,
                                                                                Copper, 6.0                                                                                                         3.1

           Gold, Silver, 11.0

                                                                                                                                                                                                               Zinc, Molybdenum,
                                                                                                                                                                                                                    Lead, 2.0
                                                                                                                                                               Steel (Integrated), 3.4
                                                                                              Other, 18.5                                                                                                                Aluminium, 1.4
      Steel (mazufacturer), 13.2
                                                                                                                                                                                                                             Power, 0.7

                                                                                                                                                                    Nickel, 3.6


                                                                                                                                                                                                         Platinum, 3.7             Coal, 0.5
                 Commodity Chemicals, 16.2

                                                                       Iron Ore, 15.8




Source: IBES, Datastream, Bloomberg.


Figure 98: MSCI EM Materials breakdown by earnings


                        Iron Ore                                              Commodity Chemicals                                  Steel (mazufacturer)                                   Gold, Silver
                        Construction Materials                                                                     gistics
                                                                              Chemicals, Fertilizers, Agriculture,Lo               Copper                                                 Platinum
                        Nickel                                                Steel (Integrated)                                   Paper azd Forest Products                              Zinc, Molybdenum, Lead
                        Aluminium                                             Power                                                Coal

                                                                                                                    gistics, 6.1
                                                                               Chemicals, Fertilizers, Agriculture,Lo
                                                      Construction
                                                      Materials, 4.6
                                  Gold, Silver, 7.9




                                                                                                                                                                                               Zinc, Molybdenum, Lead, 1.8
                                                                                        Copper, 9.0                                                                         Paper azd Forest
                                                                                                                                                                             Products, 1.2
          Steel (mazufacturer), 11.0
                                                                                                                                                                                                                       Aluminium, 1.0



                                                                                                                                                                                                                                   Power, 1.0
                                                                                                                                                               Steel (Integrated), 2.2
                                                                                                 Other, 12.9
      Commodity Chemicals, 13.7
                                                                                                                                                                                                                                    Coal, 0.7




                                                                                                                                                                            Nickel, 2.5                            Platinum, 2.4



                                          Iron Ore, 34.8




Source: IBES, Datastream, Bloomberg.




66
Adrian Mowat                            Emerging Markets Equity Research
(852) 2800-8599                         23 February 2012
adrian.mowat@jpmorgan.com




Managing Chinese growth risk using derivatives
Tony SK LeeAC, tony.sk.lee@jpmorgan.c.com

A significant slowdown is not our base case, but the risk             we can see that CNY has tightened the most year-to-date,
is increasing. It is prudent for investors to hedge and               followed by ASX 200 and KRW, all of which have
mange the risk. The challenge is finding value among the              fallen by more than 25%. The laggards in the recent drop
various hedges available across the universe of China-                in protection costs include A50 ETF Tracker, Nikkei
sensitive assets and evaluating the risk/reward of these              225 and copper.
hedges during the stress scenarios.
                                                                      Protection costs versus historical levels: Based on the
Cross-asset correlations increased in the last five years. A          percentiles since 2008, Nikkei 225 is the cheapest across
key driver of cross-asset correlation is high                         all the China-sensitive assets, despite the fact that it was a
macroeconomic volatility. When prices move together,                  laggard in the recent decline of the costs of protection,
investors can hedge one asset with tradable instruments               perhaps indicating that its volatility might have found a
from another asset class, preferably when there is a                  floor. Within the equity space, the volatility of ASX 200
fundamental linkage between the assets. This cross-asset              also remains relatively subdued and hence may provide
hedging can be optimal if the proxy hedge is more liquid,             cheap protection as a proxy hedge against the risk to
costs less, or provides better entry points as compared to            Chinese growth. Within the commodity and FX asset
a direct hedge. While investors should consider tracking              classes, the volatility for CNY, TWD and crude oil
risk that can come from correlation breakdown, or asset               appears relatively cheap based on this measure while the
trending, the cross-asset tracking risk may benefit                   sovereign CDS spreads for China and Australia as
investors by avoiding the negative impact of ‘crowded                 well as SGD have yet to normalize and are trading at the
hedge’ unwinds.                                                       opposite end of the spectrum.

Recent trends in protection costs: After the recent risk-             Protection cost changes across major asset classes: In
on period, volatility and credit spreads have fallen                  terms of average relative change by asset class over the
sharply across all risky asset classes, driving down the              last three months, FX volatility is the leader during the
cost of protection. To identify a cost-effective hedge                recent decline of protection costs, followed by equity
against the risk of significant slowdown in Chinese                   volatility while commodity volatility and CDS spreads
growth in the current moderating volatility environment,              have lagged. Over the last 12 months, FX is the only
we first screen across the recent performance and                     asset class whose volatility has fallen while CDS spreads
volatility/spread changes in various China-sensitive                  are still more than 40% higher.
assets across equities, credit, FX and commodities (see
Table 35). 3M ATM implied volatility and 5Y CDS                       Beta to risk-off events: Looking at the past three crises
spreads are used in this analysis to identify any                     in 4Q08, 2Q10 and 3Q11, we can gauge the beta of the
dislocations, leaders and laggards in the costs of                    costs of protection for each asset class to significant risk-
protection.                                                           off events by measuring the average relative changes of
                                                                      volatility and CDS spreads based on the levels at the start
Price performance: During the risk-on rally year-to-                  of the quarter during which the crises occurred, to the
date, H-shares, Hang Seng, Taiwan TAIEX, A50 ETF                      peak levels observed in the quarter. During the crisis in
Tracker and copper were the best performers with gains                4Q08, CDS spreads had the highest beta, followed by
of more than 10%, while all the China-sensitive assets we             equity volatility while all asset classes had similar levels
monitor (except for crude oil) also have positive                     of beta during the crisis in 3Q11. As CDS spreads have
performances.                                                         lagged in the recent decline of protection costs and
                                                                      remain relatively elevated, the other asset classes might
Notable movers in protection costs: Looking at the                    have the potential to display a higher beta to significant
relative change in volatility and CDS spread data for a               risk-off events in the near future.
rough indication of the change in the costs of protection,




                                                                                                                                 67
Adrian Mowat                                                                         Emerging Markets Equity Research
(852) 2800-8599                                                                      23 February 2012
adrian.mowat@jpmorgan.com




                                          Table 35: Price performance and volatility / CDS spread movements for China-sensitive assets as of February 10, 2012
                                                                              Price Performance                                                                                                 3M ATM Implied Volatility / 5Y CDS Spread
                                                                                                        Current Vol /                                                                             Absolute Change      Relative Percentage Change %tile
                                    Name                        Type        YTD       3M       12M       CDS Level                                                                             YTD      3M      12M      YTD       3M      12M   since 08
                                    A50 ETF Tracker             Equity      10.6%      2.9%     -8.8%            26.6                                                                            -1.8      -9.0    5.2       -6%    -25%     24%     29%
                                    ASX 200                     Equity        4.7%     0.0%   -13.6%             17.0                                                                            -6.6      -6.3    3.4      -28%    -27%     25%     17%
                                    Hang Seng                   Equity      12.7%      9.6%     -8.5%            21.8                                                                            -3.8    -10.7     3.0      -15%    -33%     16%     28%
                                    H-shares                    Equity      14.8%     10.7%     -5.1%            27.5                                                                            -3.7    -10.2     5.4      -12%    -27%     24%     31%
                                    KOSPI 200                   Equity        9.7%    10.7%     -1.3%            21.3                                                                            -4.7      -9.2    2.6      -18%    -30%     14%     35%
                                    Nikkei 225                  Equity        5.8%     5.3%   -15.6%             18.2                                                                            -1.5      -6.0    1.5       -7%    -25%      9%       5%
                                    Taiwan TAIEX                Equity      11.2%      7.6%   -11.0%             19.4                                                                            -5.9      -7.0    3.7      -23%    -26%     23%     28%
                                    AUD                         FX            4.1%     5.1%      6.3%            12.9                                                                            -2.9      -5.3    0.2      -18%    -29%      2%     28%
                                    CNY                         FX            0.1%     0.9%      4.6%             2.1                                                                            -0.9      -1.5   -1.0      -30%    -42%    -32%     17%
                                    KRW                         FX            3.1%     0.6%     -0.7%            11.1                                                                            -4.0      -5.7   -2.1      -27%    -34%    -16%     22%
                                    NZD                         FX            6.1%     6.5%      8.1%            13.1                                                                            -2.6      -5.1    0.1      -17%    -28%      0%     18%
                                    SGD                         FX            3.0%     2.5%      1.5%             8.2                                                                            -1.1      -4.0    1.2      -12%    -33%     17%     70%
                                    TWD                         FX            2.4%     2.1%     -2.2%             5.7                                                                            -1.2      -2.9   -0.7      -18%    -34%    -11%     13%
                                    Copper                      Commodity   11.5%     13.5%   -15.0%             32.9                                                                            -3.6      -7.3    6.7      -10%    -18%     25%     34%
                                    Crude Oil                   Commodity    -0.2%     0.9%    13.8%             30.3                                                                            -5.9    -10.6     2.9      -16%    -26%     11%     15%
                                    Australia 5Y CDS            Credit                                           68.0                                                                           -14.3      -4.7   14.1      -17%     -7%     26%     74%
                                    China 5Y CDS                Credit                                          126.0                                                                           -22.0    -22.0    50.0      -15%    -15%     66%     78%
       Source: J.P. Morgan Equity Derivatives Strategy


Figure 99: YTD relative % change of volatility / CDS                                                            Figure 100: Percentile of volatility / CDS since 2008
                                           0%                                                                                                                    90%

                                                                                                                                                                 80%
                                          -5%
YTD Relative Change of Volatility / CDS




                                                                                                                Percentile of Volatility / CDS since 2008




                                                                                                                                                                 70%
                                          -10%
                                                                                                                                                                 60%

                                          -15%                                                                                                                   50%


                                          -20%                                                                                                                   40%

                                                                                                                                                                 30%
                                          -25%
                                                                                                                                                                 20%

                                          -30%
                                                                                                                                                                 10%

                                          -35%                                                                                                                                 0%




Source: J.P. Morgan Equity Derivatives Strategy                                                                 Source: J.P. Morgan Equity Derivatives Strategy


Figure 101: Average relative change of volatility / CDS by asset class                                          Figure 102: Average relative change of vol / CDS to peak during past
                                          50%                                                                   crises
                                                 3M
                                                                                                                                                                                        400%
                                          40%    12M                                                                                                                                              4Q08
                                                                                                                                                                                                  2Q10
                                                                                                                         Relative Change of Volatility / CDS from Start of Quarter to




                                                                                                                                                                                        350%
                                          30%                                                                                                                                                     3Q11
Relative Change of Volatility / CDS




                                          20%                                                                                                                                           300%


                                          10%                                                                                                                                           250%
                                                                                                                                                    Peak




                                           0%                                                                                                                                           200%


                                          -10%
                                                                                                                                                                                        150%

                                          -20%
                                                                                                                                                                                        100%

                                          -30%
                                                                                                                                                                                        50%
                                          -40%
                                                       Equity         FX          Commodity         Credit
                                                                                                                                                                                         0%
Source: J.P. Morgan Equity Derivatives Strategy                                                                                                                                                      Equity         FX          Commodity       Credit
                                                                                                                Source: J.P. Morgan Equity Derivatives Strategy




68
Adrian Mowat                                                           Emerging Markets Equity Research
(852) 2800-8599                                                        23 February 2012
adrian.mowat@jpmorgan.com




                            Table 36: Hedging costs and potential return on premium/CDS across China-sensitive assets as of February 10, 2012
                                                           Current       Lows      Abs Dist to    Rel Dist to    3M 95% Put 6M 95% Put      Max Return on     Max Return to
                            Name               Type         Level     Since 2008* Lows Since 08* Lows Since 08* Prem / CDS** Prem / CDS** 95% Puts / CDS*** Cost Ratio (6M)***
                            A50 ETF Tracker    Equity           11.44         6.87         -4.57         -39.9%         3.28%        5.47%             34.9%              6.4X
                            ASX 200            Equity         4245.33      3145.50      -1099.83         -25.9%         2.03%        3.57%             20.9%              5.9X
                            Hang Seng          Equity        20783.86     11015.84      -9768.02         -47.0%         2.74%        5.05%             42.0%              8.3X
                            H-shares           Equity        11405.22      4990.08      -6415.14         -56.2%         3.62%        6.56%            51.2%               7.8X
                            KOSPI 200          Equity          261.17       123.27       -137.90         -52.8%         2.25%        3.92%             47.8%             12.2X
                            Nikkei 225         Equity         8947.17      7054.98      -1892.19         -21.1%         2.13%        3.99%             16.1%              4.0X
                            Taiwan TAIEX       Equity         7862.27      4089.93      -3772.34         -48.0%         2.18%        5.27%             43.0%              8.2X
                            AUD                FX              1.0677       0.6117         -0.46         -42.7%         1.28%        2.70%             39.7%             14.7X
                            CNY                FX                6.29         7.31          1.01          16.1%         0.05%        0.17%              9.6%             56.2X
                            KRW                FX             1124.50      1570.75        446.25          39.7%         1.11%        1.19%             24.8%             20.9X
                            NZD                FX                0.83         0.49         -0.33         -40.4%         1.06%        2.64%             37.2%             14.1X
                            SGD                FX                1.26         1.56          0.30          23.6%         0.45%        1.02%             15.1%             14.7X
                            TWD                FX               29.58        35.17          5.58          18.9%         0.20%        0.22%             11.7%             53.0X
                            Copper             Commodity      8460.75      2809.50      -5651.25         -66.8%         4.91%        7.74%            61.8%               8.0X
                            Crude Oil          Commodity        98.67        33.87        -64.80         -65.7%         3.77%        5.93%            60.7%              10.2X
                            Australia 5Y CDS   Credit           68.00       180.06        112.06        164.8%            17.0         34.0             5.6%             16.4X
                            China 5Y CDS       Credit          126.00       265.00        139.00        110.3%            31.5         63.0             6.6%             10.5X
               Source: J.P. Morgan Equity Derivatives Strategy
               *Highs are used for CDS ** FX puts are puts on Asian currencies/calls on USD with notional and premium in USD; 3M and 6M hedging costs for CDS; 95% strikes relative to current spot
               *** Return on premium / CDS if markets revert back to lows since 2008; CDS returns are estimated by spread change and DV01.


Identifying the best hedges: Using the extreme levels                                                                                                                95% put / CDS structure across all the China-sensitive
during the global financial crisis or the lows since 2008                                                                                                            hedges (see Figure 105). Interestingly, they are also the
as stress points, we can determine which hedges could                                                                                                                hedges with the lowest costs across all the assets (see
provide us with the most “bang for the buck” in a                                                                                                                    Figure 103). If China were to enter a scenario of
scenario of a significant slowdown in Chinese growth                                                                                                                 significant slowdown, the demand for China investments
(see Table 36). We prefer using this metric to the metric                                                                                                            as well as its currency would be severely impacted.
of absolute low premium to identify which China-                                                                                                                     Given the close ties between China and Taiwan, TWD
sensitive hedge is the most cost effective.                                                                                                                          would be impacted as well. However, despite the low
                                                                                                                                                                     premium outlay and the high potential payouts against
Hedges with the most bang for the buck: Based on our                                                                                                                 our stress points, investors must beware of the possibility
stress point assumptions, CNY and TWD puts have the                                                                                                                  of government intervention during times of crisis.
most attractive maximum return-to-cost ratios for the 6M

Figure 103: 6M hedging costs based on 95% put premium / CDS                                               Figure 104: Max return on 95% puts / CDS based on lows since 2008
                            9%                                                                                                                                      70%
                                                                                                            Max Return on 95% Puts / CDS Based on Lows Since 2008




                            8%
                                                                                                                                                                    60%

                            7%
 6M 95% Put Premium / CDS




                                                                                                                                                                    50%
                            6%

                            5%                                                                                                                                      40%


                            4%                                                                                                                                      30%

                            3%
                                                                                                                                                                    20%
                            2%

                                                                                                                                                                    10%
                            1%

                            0%                                                                                                                                      0%




Source: J.P. Morgan Equity Derivatives Strategy                                                           Source: J.P. Morgan Equity Derivatives Strategy




                                                                                                                                                                                                                              69
Adrian Mowat                                                    Emerging Markets Equity Research
(852) 2800-8599                                                 23 February 2012
adrian.mowat@jpmorgan.com




Figure 105: Max return-to-cost ratio (6M) based on lows since 2008                       Figure 106: Max return-to-cost ratio vs cost normalized against H-
                                                          60X                            shares
 Max Return to Cost Ratio (6M) Based on Lows Since 2008




                                                                                                                                           8.0X
                                                                                                                                                      CNY
                                                          50X
                                                                                                                                           7.0X        TWD




                                                                                           Max Return to Cost Ratio (6M) versus H-shares
                                                          40X
                                                                                                                                           6.0X


                                                          30X                                                                              5.0X


                                                          20X                                                                              4.0X


                                                                                                                                           3.0X
                                                          10X                                                                                                     KRW
                                                                                                                                                  AU 5Y
                                                                                                                                                  CDS                         AUD
                                                                                                                                                                                        KOSPI 200
                                                                                                                                           2.0X               SGD                                                 Crude
                                                          0X                                                                                                            NZD                              Taiwan   Oil
                                                                                                                                                                                                         TAIEX
                                                                                                                                                      CH 5Y CDS                             Hang Seng
                                                                                                                                           1.0X                               ASX 200                                     H-shares     Copper
                                                                                                                                                                                                           A50 ETF
                                                                                                                                                                                            Nikkei 225     Tracker
                                                                                                                                           0.0X
                                                                                                                                               0.0X           0.2X       0.4X        0.6X        0.8X         1.0X                   1.2X       1.4X
Source: J.P. Morgan Equity Derivatives Strategy                                                                                                                           6M 95% Put Premium / CDS versusH-shares

                                                                                         Source: J.P. Morgan Equity Derivatives Strategy




In the FX space, puts on the other China related                                                                                             Indeed, when we normalize the maximum return-to-cost
currencies (i.e., AUD, KRW, NZD and SGD) have less                                                                                           ratios and hedging costs against those of H-shares for the
attractive maximum return-to-cost ratios than CNY and                                                                                        6M 95% put / CDS structure across all the China-
TWD puts, despite having much higher returns at the                                                                                          sensitive assets (see Figure 106), we find that only the
stress points. This is mainly due to their much richer                                                                                       puts on copper, A50 ETF tracker and Nikkei 225 are less
option premium. Nevertheless, based on this metric,                                                                                          attractive than H-shares puts. The rest all have better
FX puts are in general much more attractive than                                                                                             risk/reward profiles with lower costs outlay and higher
sovereign CDS spreads, equity puts and commodity                                                                                             maximum return-to-cost ratios.
puts.
                                                                                                                                             Despite the less favorable risk/reward profiles, the puts
In the equity space, KOSPI 200 puts are the most cost                                                                                        on the equity markets with direct exposure to China, in
effective hedges based on our preferred metric. On the                                                                                       particular H-shares, still offer a lot of value since they
other hand, the puts on the equity markets with direct                                                                                       provide a direct hedge to the risk in Chinese growth. On
exposure to China (A50 Tracker ETF, Hang Seng and H-                                                                                         the other hand, the proxy hedges can expose investors to
shares) are not as attractive as the sharp rise in their                                                                                     tracking risks, which are not captured in our analysis.
implied volatility last year has yet to completely                                                                                           The main premise of proxy hedging is that the correlation
dissipate.                                                                                                                                   between the two assets will remain stable. The expected
                                                                                                                                             benefits of cross-asset hedging (either coming from
In the commodity space, crude oil puts are more cost                                                                                         the cheapness of protection, or expected reversion of
effective than copper puts, primarily due to the lower put                                                                                   price divergence) should be compared to the potential
option premium for crude oil.                                                                                                                tracking risks.

In the credit space, the elevated levels of the China and                                                                                    Exotic hedges with hybrid options: Investors who
Australia sovereign CDS spreads appear to have priced                                                                                        prefer to use H-shares puts for hedging against the risk to
in some risks to Chinese growth, making them relatively                                                                                      Chinese growth but would like to reduce the option
less attractive compared to some of the FX puts.                                                                                             premium can consider hybrid derivatives, which have a
However, based on our stress point assumptions, their                                                                                        payoff that is conditional on the price of more than one
risk/reward profiles are more superior to the equity and                                                                                     asset class. One advantage of using hybrid derivatives is
commodity puts.                                                                                                                              that investors can significantly cheapen the cost of a
                                                                                                                                             hedge by buying protection against a particular cross-
High option premium lowers the attractiveness of H-                                                                                          asset scenario.
shares puts: While having one of the highest returns
based on our stress point assumptions (see Figure 104),                                                                                      An example is buying a put option on H-shares with a
due to the rich option premium, H-shares puts currently                                                                                      payoff conditional on the gold price rising above a
do not screen well as the most "bang for the buck" hedge.                                                                                    certain level. If an investor believes that a market crash in

70
Adrian Mowat                           Emerging Markets Equity Research
(852) 2800-8599                        23 February 2012
adrian.mowat@jpmorgan.com


China will coincide with a run of investors into the
relative security of gold, buying this hybrid option could
be significantly cheaper than buying a plain put on H-
shares. Currently, the indicative option premium of a H-
shares 6M 90% put option contingent on gold higher than
its current level at expiry is 3.31%, which represents a
discount of 33% versus the H-shares 6M 90% vanilla put
premium of 5.0%.

Another example is buying a put option on H-shares with
a payoff conditional on CNY depreciating below a
certain level, based on the view that a market crash in
China will coincide with investment outflow and
depreciation in its currency. Currently, the indicative
option premium of a H-shares 6M 90% put option
contingent on CNY deprecating from its current level at
expiry is 3.71%, which represents a discount of 26%
versus the H-shares 6M 90% vanilla put premium of
5.0%.




                                                                          71
Adrian Mowat                             Emerging Markets Equity Research
(852) 2800-8599                          23 February 2012
adrian.mowat@jpmorgan.com




Risks of common option strategies
Risks to Strategies: Not all option strategies are suitable            underlying asset’s price is above the strike price of the
for investors; certain strategies may expose investors to              put option.
significant potential losses. We have summarized the
risks of selected derivative strategies. For additional risk           Straddle or Strangle. The seller of a straddle or strangle
information, please call your sales representative for a               is exposed to increases in the underlying asset’s price
copy of “Characteristics and Risks of Standardized                     above the call strike and declines in the underlying
Options.” We advise investors to consult their tax                     asset’s price below the put strike. Since exposure on the
advisors and legal counsel about the tax implications of               upside is theoretically unlimited, investors who also own
these strategies. Please also refer to option risk disclosure          the underlying asset would have limited losses should the
documents.                                                             underlying asset rally. Covered writers are exposed to
                                                                       declines in the underlying asset position as well as any
Put Sale. Investors who sell put options will own the                  additional exposure should the underlying asset decline
underlying asset if the asset’s price falls below the strike           below the strike price of the put option. Having sold a
price of the put option. Investors, therefore, will be                 covered call option, the investor gives up all appreciation
exposed to any decline in the underlying asset’s price                 in the underlying asset above the strike price of the call
below the strike potentially to zero, and they will not                option.
participate in any price appreciation in the underlying
asset if the option expires unexercised.                               Put Spread. The buyer of a put spread risks losing 100%
                                                                       of the premium paid. The buyer of higher-ratio put
Call Sale. Investors who sell uncovered call options have              spread has unlimited downside below the lower strike
exposure on the upside that is theoretically unlimited.                (down to zero), dependent on the number of lower-struck
                                                                       puts sold. The maximum gain is limited to the spread
Call Overwrite or Buywrite. Investors who sell call                    between the two put strikes, when the underlying is at the
options against a long position in the underlying asset                lower strike. Investors who own the underlying asset will
give up any appreciation in the underlying asset’s price               have downside protection between the higher-strike put
above the strike price of the call option, and they remain             and the lower-strike put. However, should the underlying
exposed to the downside of the underlying asset in the                 asset’s price fall below the strike price of the lower-strike
return for the receipt of the option premium.                          put, investors regain exposure to the underlying asset,
                                                                       and this exposure is multiplied by the number of puts
Booster. In a sell-off, the maximum realized downside                  sold.
potential of a double-up booster is the net premium paid.
In a rally, option losses are potentially unlimited as the             Call Spread. The buyer risks losing 100% of the
investor is net short a call. When overlaid onto a long                premium paid. The gain is limited to the spread between
position in the underlying asset, upside losses are capped             the two strike prices. The seller of a call spread risks
(as for a covered call), but downside losses are not.                  losing an amount equal to the spread between the two
                                                                       call strikes less the net premium received. By selling a
Collar. Locks in the amount that can be realized at                    covered call spread, the investor remains exposed to the
maturity to a range defined by the put and call strike. If             downside of the underlying asset and gives up the spread
the collar is not costless, investors risk losing 100% of              between the two call strikes should the underlying asset
the premium paid. Since investors are selling a call                   rally
option, they give up any price appreciation in the
underlying asset above the strike price of the call option.            Butterfly Spread. A butterfly spread consists of two
                                                                       spreads established simultaneously – one a bull spread
Call Purchase. Options are a decaying asset, and                       and the other a bear spread. The resulting position is
investors risk losing 100% of the premium paid if the                  neutral, that is, the investor will profit if the underlying is
underlying asset’s price is below the strike price of the              stable. Butterfly spreads are established at a net debit.
call option.                                                           The maximum profit will occur at the middle strike price;
                                                                       the maximum loss is the net debit.
Put Purchase. Options are a decaying asset, and
investors risk losing 100% of the premium paid if the




72
Adrian Mowat                                Emerging Markets Equity Research
(852) 2800-8599                             23 February 2012
adrian.mowat@jpmorgan.com



MSCI EM Materials valuation summary
Table 37: MSCI EM Materials stocks valuations
      Name           Country       Ticker         JPM            Sub Industry              Mkt Cap    Price     Forward PE       Trailing PB     Valuation
                                                 Rating             Name                   (US$ Bn)   (LC)     Curr-    # of    Curr-     # of    Score
                                                                                                                ent      SD      ent      SD
Uralkali             Russia     URKA RM           NR      Fertilizers & Agricultural Che     11.2      240      NM       NM      2.6     (1.6)        (1.6)
Suzano Papel Pna     Brazil     SUZB5 BZ           N      Paper Products                     0.9         8      NM       NM      0.4     (1.4)        (1.4)
Huabao Intl.Hdg.     China      336 HK            OW      Specialty Chemicals                1.4         6      9.3     (1.5)    3.1     (1.3)        (1.4)
Zijin Mining Group   China      2899 HK           NR      Gold                               2.7         4      8.2     (1.5)    2.6     (1.2)        (1.4)
Ojsc Novolipetsk     Russia     NLMK LI           UW      Steel                              1.7        25      9.2     (0.3)    1.5     (2.3)        (1.3)
Bbmg 'H'             China      2009 HK            N      Construction Materials             1.0         7      5.6     (1.2)    1.4     (1.1)        (1.2)
Vale Pna             Brazil     VALE5 BZ          OW      Iron Ore                           81.7       42      6.1     (0.9)    1.5     (1.4)        (1.2)
Anglogold Ashanti    SA         ANG SJ            UW      Gold                               16.4      329      7.9     (1.7)    4.0     (0.5)        (1.1)
Cemex 'Cpo'          Mexico     CEMEXCPO MM       NR      Construction Materials             8.7        11      NM       NM      0.6     (1.1)        (1.1)
Cia.Minas            Peru       BVN US             N      Gold                               7.8        41     10.5     (0.9)    3.4     (1.2)        (1.1)
United Phosph        India      UNTP IN           NR      Fertilizers & Agricultural Che     0.7       161      9.1     (0.9)    2.0     (1.0)        (1.0)
Sinofert Holdings    China      297 HK            NR      Fertilizers & Agricultural Che     0.6         2     10.7     (1.0)    1.0     (0.9)        (1.0)
Koza Altin           Turkey     KOZAL TI           N      Gold                               0.9        33      7.8     (0.9)    7.1     (1.0)        (0.9)
Gold Fields          SA         GFI SJ             N      Gold                               11.6      123      7.0     (1.4)    2.1     (0.5)        (0.9)
Fibria On            Brazil     FIBR3 BZ           N      Paper Products                     2.0        17      NM       NM      0.5     (0.9)        (0.9)
Hanwha               Korea      000880 KS         NR      Commodity Chemicals                1.5      37600     4.8     (0.7)    0.5     (1.1)        (0.9)
Csg Holding 'B'      China      200012 CH         NR      Construction Materials             0.6         7      6.0     (1.1)    1.6     (0.7)        (0.9)
Bradespar Pn         Brazil     BRAP4 BZ          OW      Iron Ore                           4.7        35      5.8     (0.7)    1.4     (1.0)        (0.9)
China Nat.Bldg.      China      3323 HK           OW      Construction Materials             4.1        11      6.2     (1.0)    2.2     (0.7)        (0.8)
Shougang Fushan      China      639 HK            NR      Diversified Metals & Mining        1.2         3      7.7     (0.8)    0.9     (0.8)        (0.8)
Mechel Oao           Russia     MTL US            OW      Iron Ore                           1.6        11      5.8     (0.6)    0.9     (0.9)        (0.8)
China Blue           China      3983 HK           OW      Fertilizers & Agricultural Che     1.4         6      9.9     (1.1)    2.1     (0.4)        (0.7)
Oci                  Korea      010060 KS         UW      Diversified Chemicals              4.0      286500    8.7     (0.2)    2.0     (1.3)        (0.7)
Feng Hsin Iron &     Taiwan     2015 TT           NR      Steel                              0.8        51     11.4     (1.0)    1.9     (0.4)        (0.7)
Nine Dragons         China      2689 HK           UW      Paper Products                     1.3         6     10.4     (0.6)    1.2     (0.8)        (0.7)
Sesa Goa             India      SESA IN           NR      Iron Ore                           1.7       245      6.5     (0.3)    1.7     (1.1)        (0.7)
Sinopec 'H'          China      338 HK            NR      Commodity Chemicals                0.9         3      8.7     (0.7)    0.9     (0.6)        (0.7)
Anhui Conch          China      914 HK            OW      Construction Materials             4.4        28      9.8     (1.0)    2.8     (0.3)        (0.7)
Lee & Man Paper      China      2314 HK            N      Paper Products                     0.8         4     10.4     (0.3)    1.3     (1.0)        (0.7)
Cemargos             Colombia   CEMARGOS CB        N      Construction Materials             1.8      10860    33.2     (0.8)    1.1     (0.4)        (0.6)
Sappi                SA         SAP SJ            NR      Paper Products                     1.8        26      9.9     (0.5)    1.2     (0.6)        (0.6)
China Molyb          China      3993 HK           NR      Diversified Metals & Mining        0.7         4     14.1     (0.3)    1.6     (0.8)        (0.5)
China Shanshui       China      691 HK            NR      Construction Materials             1.6         8      6.2     (0.9)    2.4     (0.2)        (0.5)
Harmony Gold         SA         HAR SJ            OW      Gold                               4.9        98     10.4     (1.0)    1.4     (0.0)        (0.5)
Hindalco             India      HNDL IN           OW      Aluminum                           3.4       151      8.9     (0.0)    1.0     (1.0)        (0.5)
Duratex On           Brazil     DTEX3 BZ          OW      Forest Products                    1.4        10     12.6      0.4     1.5     (1.4)        (0.5)
Indorama             Thailand   IVL TB             N      Commodity Chemicals                2.0        42     12.5     (0.3)    3.3     (0.7)        (0.5)
China Resources.     China      1313 HK           NR      Construction Materials             1.7         7      8.2     (1.2)    2.7      0.3         (0.5)
Fosun                China      656 HK            NR      Steel                              1.0         5      9.6     (0.2)    0.8     (0.7)        (0.5)
Kghm                 Poland     KGH PW            UW      Diversified Metals & Mining        6.2       139      6.3     (0.4)    1.4     (0.5)        (0.4)
Petronas.            Malaysia   PCHEM MK          OW      Commodity Chemicals                5.5         7     12.8     (0.7)    2.8     (0.1)        (0.4)
Jiangxi Copper 'H'   China      358 HK            NR      Diversified Metals & Mining        3.8        21      8.3     (0.4)    1.5     (0.4)        (0.4)
Impala Platinum      SA         IMP SJ            UW      Precious Metals & Minerals         10.8      164     14.4      0.5     2.2     (1.2)        (0.4)
Jindal Steel         India      JSP IN            NR      Steel                              4.9       642     13.3     (0.3)    4.3     (0.4)        (0.3)
Sterlite             India      STLT IN           OW      Diversified Metals & Mining        3.6       133      7.4     (0.5)    1.1     (0.2)        (0.3)
Afn.Rainbow Mrls.    SA         ARI SJ            NR      Diversified Metals & Mining        2.6       188      8.2     (0.8)    1.9      0.2         (0.3)
Posco                Korea      005490 KS         OW      Steel                              24.0     413000    9.4      0.6     0.8     (1.2)        (0.3)
Eternal Chemical     Taiwan     1717 TT           NR      Commodity Chemicals                0.6        26      NA       NA      1.5     (0.2)        (0.2)
Zhaojin Mining       China      1818 HK           NR      Gold                               1.7        15     14.4     (1.1)    6.3      0.7         (0.2)
Kp Chemical          Korea      064420 KS         NR      Commodity Chemicals                0.8      18550     6.5     (0.4)    1.4      0.0         (0.2)
Tata Steel           India      TATA IN           OW      Steel                              3.0       478      8.8      0.7     1.3     (1.0)        (0.1)
Southern Copper      Peru       SCCO US           OW      Diversified Metals & Mining        5.5        32     12.8      0.2     6.7     (0.5)        (0.1)
Yingde Gases         China      2168 HK           NR      Industrial Gases                   1.0         9     10.7     (0.4)    2.7      0.2         (0.1)
Tung Ho Stl.Enter.   Taiwan     2006 TT           NR      Steel                              0.8        31     11.0     (0.2)    1.5      0.0         (0.1)
Mmc Norilsk          Russia     GMKN RM           UW      Diversified Metals & Mining        9.2       5763     8.4      0.0     2.2     (0.1)        (0.1)
Taiwan Cement        Taiwan     1101 TT            N      Construction Materials             4.3        38     12.5     (0.6)    1.4      0.5         (0.1)
China Zhongwang      China      1333 HK           NR      Aluminum                           0.7         3     10.1      0.7     1.0     (0.8)        (0.1)
Severstal            Russia     CHMF RM            N      Steel                              3.0       440      7.1     (0.5)    1.9      0.5         (0.0)
Mfrisco              Mexico     MFRISCOA MM       NR      Diversified Metals & Mining        3.0        59     22.0     (0.5)   16.4      0.4         (0.0)




                                                                                                                                                 73
Adrian Mowat                                                Emerging Markets Equity Research
(852) 2800-8599                                             23 February 2012
adrian.mowat@jpmorgan.com




       Name                Country               Ticker              JPM                 Sub Industry                 Mkt Cap          Price          Forward PE           Trailing PB           Valuation
                                                                    Rating                  Name                      (US$ Bn)         (LC)          Curr-    # of        Curr-     # of            Score
                                                                                                                                                      ent      SD          ent      SD
Aneka Tambang            Indonesia        ANTM IJ                      N         Diversified Metals & Mining             0.7           1920          10.4      0.3         1.8     (0.3)            0.0
Northam Platinum         SA               NHM SJ                       N         Precious Metals & Minerals              1.0            32           16.9      0.7         1.1     (0.7)            0.0
Dongyue Group            China            189 HK                      NR         Specialty Chemicals                     0.9             8            4.9     (0.7)        3.3      0.8             0.0
Taiwan Fertilizer        Taiwan           1722 TT                     OW         Fertilizers & Agricultural Che          2.0            81           20.7     (0.5)        1.6      0.6             0.1
Eregli Demir Celik       Turkey           EREGL TI                    NR         Steel                                   1.2             4            8.7     (0.2)        1.2      0.3             0.1
Cap                      Chile            CAP CI                      NR         Steel                                   3.3          21296          10.3     (0.2)        3.6      0.4             0.1
Hyosung                  Korea            004800 KS                   NR         Commodity Chemicals                     1.4          69000           6.8     (0.0)        0.8      0.2             0.1
Dongkuk Steel Mill       Korea            001230 KS                   NR         Steel                                   0.8          24750           8.4      1.1         0.5     (0.9)            0.1
Vale Indonesia           Indonesia        INCO IJ                      N         Diversified Metals & Mining             1.0           3550          10.6      0.2         2.1     (0.1)            0.1
Braskem Pna              Brazil           BRKM5 BZ                     N         Commodity Chemicals                     1.4            16           11.7      0.2         1.2     (0.0)            0.1
Jsw Steel                India            JSTL IN                      N         Steel                                   1.5           855           10.5      1.1         1.2     (1.0)            0.1
Kumba Iron Ore           SA               KIO SJ                      NR         Iron Ore                                5.7           540            9.2     (0.4)       10.5      0.6             0.1
Asia Cement              Taiwan           1102 TT                     OW         Construction Materials                  2.4            37           11.9     (0.2)        1.4      0.5             0.1
Ultratech Cement         India            UTCEM IN                     N         Construction Materials                  2.1           1476          17.8      0.6         3.8     (0.3)            0.1
Sider.Nacional On        Brazil           CSNA3 BZ                    NR         Steel                                   7.4            18            9.9      0.3         3.1     (0.1)            0.1
Anglo American           SA               AMS SJ                      OW         Precious Metals & Minerals              4.9           569           26.2      1.7         2.7     (1.2)            0.2
Hanwha Chemical          Korea            009830 KS                   UW         Commodity Chemicals                     2.3          30700           6.9      0.1         1.0      0.4             0.3
Hyundai Hysco            Korea            010520 KS                   NR         Steel                                   1.2          40600           9.6     (0.4)        2.0      1.1             0.3
Hyundai Steel            Korea            004020 KS                   NR         Steel                                   5.5          112000          8.5      0.5         1.0      0.2             0.3
Exxaro Resources         SA               EXX SJ                      NR         Diversified Metals & Mining             3.3           199            6.6      0.1         3.6      0.6             0.4
Mmx Miner On             Brazil           MMXM3 BZ                    OW         Iron Ore                                1.3             9           26.4      1.4         1.9     (0.7)            0.4
Minmetals                China            1208 HK                     NR         Diversified Metals & Mining             0.9             4            5.6     (0.2)        2.1      1.1             0.4
Synthos                  Poland           SNS PW                      NR         Commodity Chemicals                     1.0             5            8.6     (0.7)        2.5      1.6             0.5
Formosa Chems.&          Taiwan           1326 TT                      N         Commodity Chemicals                     8.7            91           13.3      0.7         2.0      0.3             0.5
Mexchem                  Mexico           MEXCHEM* MM                 NR         Commodity Chemicals                     2.7            48           15.6      1.0         3.7      0.0             0.5
Gerdau Pn                Brazil           GGBR4 BZ                     N         Steel                                   8.9            18           12.1      2.1         1.2     (1.1)            0.5
Inverargos               Colombia         INVARGOS CB                 NR         Construction Materials                  2.8          17000          42.2      1.6         1.1     (0.5)            0.6
Formosa Plastics         Taiwan           1301 TT                     UW         Commodity Chemicals                     12.4           92           14.4      0.7         2.3      0.5             0.6
Cmpc                     Chile            CMPC CI                     NR         Paper Products                          4.9           2140          18.8      1.2         1.2      0.0             0.6
Ict.Tunggal              Indonesia        INTP IJ                     OW         Construction Materials                  2.9          17500          14.9      0.2         4.4      1.0             0.6
Pe&Oles                  Mexico           PE&OLES* MM                 NR         Precious Metals & Minerals              7.1           643           14.6     (0.3)        6.6      1.6             0.6
Gmexico 'B'              Mexico           GMEXICOB MM                  N         Diversified Metals & Mining             12.4           41           10.4      0.5         2.9      0.8             0.7
Kumho Petro              Korea            011780 KS                   NR         Commodity Chemicals                     1.6          174000          7.3      0.4         3.0      1.0             0.7
Metalurgica              Brazil           GOAU4 BZ                    OW         Steel                                   3.6            22           10.5      2.1         1.0     (0.7)            0.7
Cheil Industries         Korea            001300 KS                   OW         Diversified Chemicals                   4.1          98000          14.0      1.1         1.5      0.3             0.7
Arcelormittal Sa.        SA               ACL SJ                       N         Steel                                   1.5            64           14.2      2.0         1.2     (0.5)            0.8
Volcabc1                 Peru             VOLCABC1 PE                 NR         Diversified Metals & Mining             2.1             4            9.3      1.2         3.2      0.3             0.8
Lcy Chemical             Taiwan           1704 TT                     NR         Commodity Chemicals                     0.8            55           13.8      1.6         2.1      0.2             0.9
Tsrc                     Taiwan           2103 TT                     OW         Commodity Chemicals                     1.3            77            9.8      0.4         3.9      1.4             0.9
Asian Paints             India            APNT IN                     NR         Specialty Chemicals                     1.8           3054          25.6      1.2        13.4      0.6             0.9
Semen Gresik             Indonesia        SMGR IJ                      N         Construction Materials                  3.7          11200          14.2      0.8         5.0      1.1             0.9
Nan Ya Plastics          Taiwan           1303 TT                      N         Commodity Chemicals                     11.4           71           16.3      1.3         2.1      0.6             1.0
Sqm 'B'                  Chile            SQM/B CI                    NR         Fertilizers & Agricultural Che          5.8          29044          23.5      0.6         8.1      1.4             1.0
Klabin Sa Pn             Brazil           KLBN4 BZ                    NR         Paper Packaging                         2.3             9           19.4      2.2         1.6     (0.1)            1.1
China Steel              Taiwan           2002 TT                      N         Steel                                   11.6           30           20.8      2.4         1.7     (0.2)            1.1
Lafarge Malayan          Malaysia         LMC MK                      NR         Construction Materials                  1.0             7           16.8      0.7         2.0      1.6             1.1
Lg Chem                  Korea            051910 KS                   OW         Commodity Chemicals                     17.4         421000         11.2      1.4         3.4      1.1             1.2
Honam Petro              Korea            011170 KS                   UW         Commodity Chemicals                     4.9          380500          9.1      0.7         2.2      1.8             1.3
Acc                      India            ACC IN                      UW         Construction Materials                  1.5           1366          19.6      2.2         4.1      0.4             1.3
Ambuja Cements           India            ACEM IN                     UW         Construction Materials                  2.2           173           18.1      1.6         3.6      1.0             1.3
Siam Cement Fb           Thailand         SCC/F TB                    OW         Construction Materials                  4.1           418           14.6      1.8         3.6      0.8             1.3
Ptt Global               Thailand         PTTGC TB                     N         Commodity Chemicals                     4.0            74            9.5      2.3         1.9      0.4             1.4
Korea Zinc               Korea            010130 KS                   NR         Diversified Metals & Mining             3.2          419000          9.4      1.5         2.2      1.3             1.4
Pretoria Port.Cmt.       SA               PPC SJ                      OW         Construction Materials                  2.1            31           15.3      1.7        18.9      1.1             1.4
Angang Steel 'H'         China            347 HK                       N         Steel                                   0.9             6           31.5      4.1         0.7     (1.1)            1.5
Usiminas Pna             Brazil           USIM5 BZ                    UW         Steel                                   5.0            12           24.7      4.5         0.7     (1.2)            1.7
Jsw                      Poland           JSW PW                       N         Diversified Metals & Mining             1.4           108            9.3      3.8         1.7      0.0             1.9
Aluminum Corp.Of         China            2600 HK                      N         Aluminum                                2.1             4           61.5      6.6         0.9     (1.2)            2.7
China Petrochem          Taiwan           1314 TT                     NR         Commodity Chemicals                     2.3            38            9.9      9.5         2.0      1.9             5.7
Source: MSCI, IBES, Bloomberg. Note: (1) Valuation score is average of standard deviations from 10 year mean of 12 month forward PE and trailing PB. Table sorted by valuation score. ; (2) At
the time of publishing this note, 23 February 2012, NR meant Not Covered by J.P. Morgan. The designation NR subsequently means restricted due to legal or business reasons




74
Adrian Mowat                                                  Emerging Markets Equity Research
(852) 2800-8599                                               23 February 2012
adrian.mowat@jpmorgan.com


Appendix
Table 38: Weight of MSCI EM Materials constituents based on revenue
                                                                         MSCI EM Weight (Based on Revenue Mix)                                    MSCI EM Weight (Based on 2011
                                                                                                                                                          Revenue Mix)
Name                         BBG Ticker                Constituent1               Constituent2             Constituent3        Constituent4     Constitu Constitu Constitu Constit
                                                                                                                                                 ent1     ent2     ent3     uent4
Acc                            ACC IN           Construction Materials                                                                            0.3
Afn.Rainbow Mrls.              ARI SJ           Iron Ore                             Platinum                    Nickel                           0.3      0.1      0.1
Alumin. Corp.                 2600 HK           Aluminium                                                                                         0.4
Ambuja Cements                ACEM IN           Construction Mat.                                                                                 0.4
Aneka Tambang                 ANTM IJ           Nickel                             Gold, Silver                                                   0.1      0.1
Angang Steel 'H'               347 HK           Steel (mazufacturer)                                                                              0.2
Anglo AmerPlat                AMS SJ            Platinum                                                                                          0.9
Anglogold Ashanti             ANG SJ            Gold, Silver                                                                                      3.4
Anhui Conch                    914 HK           Construction Mat.                                                                                 0.8
Arcelormittal Sa.              ACL SJ           Steel (Integrated)                      coal                                                      0.3      0.0
Asia Cement                   1102 TT           Construction Mat.                                                                                 0.5
Asian Paints                  APNT IN              Che.Fer, Agri,Logi                                                                             0.4
Bbmg 'H'                      2009 HK           Construction Materials                                                                            0.2
Bradespar Pn                 BRAP4 BZ           Iron Ore                              Copper                     Nickel      Che.Fer, Agri,Logi   0.7      0.0      0.1      0.1
Braskem Pna                  BRKM5 BZ           Commodity Chemicals                                                                               0.3
Cia.Minas                     BVN US            Gold, Silver                                                                                      1.5
Cap                            CAP CI           Iron Ore                           Steel (Integ.)                                                 0.3      0.3
Cemargos                  CEMARGOS CB           Construction Materials                                                                            0.3
Cemex 'Cpo'               CEMEXCPO MM           Construction Materials                                                                            1.7
Cheil Industries             001300 KS             Che.Fer, Agri,Logi                                                                             0.8
China Blue '                  3983 HK              Che.Fer, Agri,Logi                                                                             0.3
China Molyb                   3993 HK           Zinc, Molyb, Lead                                                                                 0.1
China Nat.Bldg.               3323 HK           Construction Materials                                                                            0.7
China Petrochem.              1314 TT           Commodity Chemicals                                                                               0.4
China Resources               1313 HK           Construction Materials                                                                            0.3
China Shanshui                 691 HK           Construction Materials                                                                            0.3
China Steel                   2002 TT           Steel (mazufacturer)                                                                              2.2
China Zhongwang               1333 HK           Aluminium                                                                                         0.1
Cmpc                          CMPC CI           Paper, Forest Prod                                                                                1.0
Csg Holding 'B'              200012 CH          Construction Materials                                                                            0.1
Sider.Nacional On            CSNA3 BZ           Iron Ore                           Steel (Integ.)       Che.Fer, Agri,Logi                        0.3      1.0      0.2
Dongkuk Steel Mill           001230 KS          Steel (mazufacturer)                                                                              0.2
Dongyue Group                  189 HK              Che.Fer, Agri,Logi                                                                             0.2
Duratex On                   DTEX3 BZ           Paper, Forest Prod                                                                                0.3
Eregli Demir Celik           EREGL TI           Steel (mazufacturer)                                                                              0.2
Eternal Chemical              1717 TT           Commodity Chemicals                                                                               0.1
Exxaro Resources               EXX SJ           Power                          Zinc, Molyb, Lead                                                  0.4      0.2
Feng Hsin I&S                 2015 TT           Steel (mazufacturer)                                                                              0.1
Formosa Chems.                1326 TT           Commodity Chemicals                                                                               1.6
Formosa Plastics              1301 TT           Commodity Chemicals                                                                               2.3
Fosun Internat.                656 HK           Steel (Integrated)                   Iron Ore           Che.Fer, Agri,Logi                        0.1      0.0      0.1
Metalurgica Ger.             GOAU4 BZ           Steel (mazufacturer)                                                                              0.7
Gerdau Pn                    GGBR4 BZ           Steel (mazufacturer)                                                                              1.7
Gold Fields                    GFI SJ           Gold, Silver                                                                                      2.4
Gmexico 'B'               GMEXICOB MM           Copper                          Che.Fer, Agri,Logi      Zinc, Molyb, Lead                         1.7      0.5      0.2
Hanwha Chemical              009830 KS          Commodity Chemicals                                                                               0.4
Hanwha                       000880 KS          Commodity Chemicals                                                                               0.3
Harmony Gold.                 HAR SJ            Gold, Silver                                                                                      1.0
Hindalco Indust.              HNDL IN           Aluminium                                                                                         0.7
Honam Petrochem              011170 KS          Commodity Chemicals                                                                               1.0
Huabao Intl.Hdg.               336 HK              Che.Fer, Agri,Logi                                                                             0.3
Hyosung                      004800 KS          Commodity Chemicals                                                                               0.3
Hyundai Hysco                010520 KS          Steel (mazufacturer)                                                                              0.2
Hyundai Steel                004020 KS          Steel (mazufacturer)                                                                              1.1
Impala Platinum                IMP SJ           Platinum                                                                                          2.1
Ict.Tunggal                    INTP IJ          Construction Materials                                                                            0.5
Indorama                       IVL TB           Commodity Chemicals                                                                               0.3
Pe&Oles                    PE&OLES* MM          Gold, Silver                       Gold, Silver                  Copper      Zinc, Molyb, Lead    0.3      0.7      0.1      0.2
Vale Indonesia                INCO IJ           Nickel                                                                                            0.2
Inverargos                 INVARGOS CB          Construction Materials                                                                            0.5
Jsw                           JSW PW            Coal                                                                                              0.3
Jiangxi Copper 'H'             358 HK           Copper                             Gold, Silver                                                   0.7      0.1
Source: MSCI, Bloomberg. Note: Che, Fer, Agri, Logi represents Chemicals, Fertilizers, agriculture, logistics.


                                                                                                                                                                               75
Adrian Mowat                                                  Emerging Markets Equity Research
(852) 2800-8599                                               23 February 2012
adrian.mowat@jpmorgan.com



Table 39: Weight of MSCI EM Materials constituents based on revenue
                                                                                  MSCI EM Constituent name                                     MSCI EM Weight (Based on 2011
                                                                                                                                                       revenue Mix)
Name                        BBG Ticker               Constituent1                Constituent2             Constituent3      Constituent4     Constitu Constitu Constitu Constit
                                                                                                                                              ent1     ent2     ent3     uent4
Jindal Steel                  JSP IN           Steel (Integrated)                    Power                                                     0.6      0.3
Jsw Steel                    JSTL IN           Steel (manufacturer)                                                                            0.3
Kghm                         KGH PW            Copper                          Che.Fer, Agri,Logi                                              1.0      0.2
Klabin Sa Pn                KLBN4 BZ           Paper,Forest Products                                                                           0.4
Kumho Petro                011780 KS           Commodity Chemicals                                                                             0.3
Korea Zinc                 010130 KS           Copper                             Gold, Silver          Zinc, Molyb, Lead                      0.1      0.2      0.3
Koza Altin                  KOZAL TI           Gold, Silver                                                                                    0.2
Kp Chemical                064420 KS           Commodity Chemicals                                                                             0.2
Kumba Iron Ore                KIO SJ           Iron Ore                                                                                        1.1
Lafarge Malayan              LMC MK            Construction Materials                                                                          0.2
Lee & Man Paper              2314 HK           Paper,Forest Products                                                                           0.2
Lcy Chemical                 1704 TT           Commodity Chemicals                                                                             0.2
Lg Chem                    051910 KS           Commodity Chemicals                                                                             3.4
Lg Chem 1Pf                051910 KS           Commodity Chemicals                                                                             0.2
Mechel Oao                  MTLR RM            Iron Ore                        Steel (Integrated)             Power                            0.2      0.1      0.0
Mexchem                   MEXCHEM*MM           Commodity Chemicals                                                                             0.5
Mfrisco                   MFRISCOAMM           Gold, Silver                         Copper              Zinc, Molyb, Lead                      0.3      0.1      0.2
Minmetals Res.               1208 HK           Copper                          Zinc, Molyb, Lead            aluminium                          0.0      0.0      0.1
Mmx Miner On Nm            MMXM3 BZ            Iron Ore                                                                                        0.2
Nan Ya Plastics              1303 TT           Commodity Chemicals                                                                             2.0
Nine Dragons                 2689 HK           Paper,Forest Products                                                                           0.3
Mmc Norilsk                GMKN RM             Nickel                                Copper                  Platinum                          0.9      0.4      0.4
Northam Platinum             NHM SJ            Platinum                                                                                        0.2
Ojsc Novolipetsk            NLMK RM            Steel (Integrated)                   Iron Ore                                                   0.3      0.0
Oci                        010060 KS           Che.Fer, Agri,Logi                                                                              0.8
Petronas Chem.             PCHEM MK            Commodity Chemicals                                                                             1.1
Posco                      005490 KS           Steel (mazufacturer)                                                                            4.7
Pretoria Port.Cmt.           PPC SJ            Construction Materials                                                                          0.4
Ptt Global Chem            PTTGC TB            Commodity Chemicals                                                                             0.8
Sappi                        SAP SJ            Paper,Forest Products                                                                           0.3
Semen Gresik                 SMGR IJ           Construction Materials                                                                          0.7
Sesa Goa                     SESA IN           Iron Ore                                                                                        0.3
Severstal                   CHMF RM            Iron Ore                        Steel (Integrated)                                              0.1      0.4
Shougang Fushan               639 HK           Coal                                                                                            0.2
Siam Cement Fb               SCC TB            Construction Materials                                                                          0.8
Sinofert Holdings             297 HK           Che.Fer, Agri,Logi                                                                              0.1
Sinopec Shai.                 338 HK           Commodity Chemicals                                                                             0.2
Sqm 'B'                     SQM/B CI           Che.Fer, Agri,Logi                                                                              1.1
Southern Copper             SCCO US            Copper                                                                                          1.1
Sterlite Inds.(India)        STLT IN           Copper                          Zinc, Molyb, Lead            aluminium                          0.3      0.3      0.1
Suzano Papel Pna            SUZB5 BZ           Paper,Forest Products                                                                           0.2
Synthos                      SNS PW            Commodity Chemicals                                                                             0.2
Taiwan Cement                1101 TT           Construction Materials                                                                          0.8
Taiwan Fertilizer            1722 TT           Che.Fer, Agri,Logi                                                                              0.4
Tata Steel                   TATA IN           Steel (Integrated)            Steel (manufacturer)                                              0.2      0.4
Tsrc                         2103 TT           Commodity Chemicals                                                                             0.3
Tung Ho Stl.Enter.           2006 TT           Steel (mazufacturer)                                                                            0.1
Ultratech Cement           UTCEM IN            Construction Materials                                                                          0.4
United Phosph.               UNTP IN           Che.Fer, Agri,Logi                                                                              0.1
Uralkali                    URKA RM            Che.Fer, Agri,Logi                                                                              2.0
Usiminas On                 USIM3 BZ           Steel (mazufacturer)                                                                            0.3
Usiminas Pna                USIM3 BZ           Steel (mazufacturer)                                                                            0.6
Vale On                     VALE3 BZ           Iron Ore                             Copper                    Nickel      Che.Fer, Agri,Logi   4.9      0.1      0.9      0.7
Vale Pna                    VALE3 BZ           Iron Ore                             Copper                    Nickel      Che.Fer, Agri,Logi   7.2      0.2      1.3      1.0
Volcabc1                  VOLCABC1PE           Copper                          Zinc, Molyb, Lead                                               0.0      0.4
Fibria On                   FIBR3 BZ           Paper,Forest Products                                                                           0.4
Yingde Gases                 2168 HK           Paper,Forest Products                                                                           0.2
Zhaojin Mining               1818 HK           Gold, Silver                                                                                    0.3
Zijin Mining Group           2899 HK           Gold, Silver                                                                                    0.6
Source: MSCI, Bloomberg. Note: Che, Fer, Agri, Logi represents Chemicals, Fertilizers, agriculture, logistics.




76
Adrian Mowat                                                  Emerging Markets Equity Research
(852) 2800-8599                                               23 February 2012
adrian.mowat@jpmorgan.com



Table 40: Weight of MSCI EM Materials constituents based on earnings contribution
                                                                          MSCI EM Weight (Based on Revenue Mix)                                   MSCI EM Weight (Based on 2011
                                                                                                                                                          Revenue Mix)
Name                          BBG Ticker               Constituent1               Constituent2             Constituent3        Constituent4     Constitu Constitu Constitu Constit
                                                                                                                                                 ent1     ent2     ent3     uent4
Acc                             ACC IN            Construction Materials                                                                          0.1      0.0      0.0      0.0
Afn.Rainbow Mrls.               ARI SJ            Iron Ore                           Platinum                    Nickel                           0.4      0.1      0.0      0.0
Alumin. Corp.                  2600 HK            Aluminium                                                                                       0.2      0.0      0.0      0.0
Ambuja Cements                 ACEM IN            Construction Mat.                                                                               0.2      0.0      0.0      0.0
Aneka Tambang                  ANTM IJ            Nickel                            Gold, Silver                                                  0.1      0.0      0.0      0.0
Angang Steel 'H'                347 HK            Steel (mazufacturer)                                                                            0.0      0.0      0.0      0.0
Anglo AmerPlat                 AMS SJ             Platinum                                                                                        0.3      0.0      0.0      0.0
Anglogold Ashanti              ANG SJ             Gold, Silver                                                                                    2.7      0.0      0.0      0.0
Anhui Conch                     914 HK            Construction Mat.                                                                               0.9      0.0      0.0      0.0
Arcelormittal Sa.               ACL SJ            Steel (Integrated)                    coal                                                      0.0      0.0      0.0      0.0
Asia Cement                    1102 TT            Construction Mat.                                                                               0.4      0.0      0.0      0.0
Asian Paints                   APNT IN               Che.Fer, Agri,Logi                                                                           0.1      0.0      0.0      0.0
Bbmg 'H'                       2009 HK            Construction Materials                                                                          0.3      0.0      0.0      0.0
Bradespar Pn                  BRAP4 BZ            Iron Ore                            Copper                     Nickel      Che.Fer, Agri,Logi   1.5      0.0      0.1      0.1
Braskem Pna                   BRKM5 BZ            Commodity Chemicals                                                                             0.2      0.0      0.0      0.0
Cia.Minas                      BVN US             Gold, Silver                                                                                    1.3      0.0      0.0      0.0
Cap                             CAP CI            Iron Ore                         Steel (Integ.)                                                 0.5      0.0      0.0      0.0
Cemargos                   CEMARGOS CB            Construction Materials                                                                          0.1      0.0      0.0      0.0
Cemex 'Cpo'                CEMEXCPO MM            Construction Materials                                                                          -2.0     0.0      0.0      0.0
Cheil Industries              001300 KS              Che.Fer, Agri,Logi                                                                           0.5      0.0      0.0      0.0
China Blue '                   3983 HK               Che.Fer, Agri,Logi                                                                           0.2      0.0      0.0      0.0
China Molyb                    3993 HK            Zinc, Molyb, Lead                                                                               0.1      0.0      0.0      0.0
China Nat.Bldg.                3323 HK            Construction Materials                                                                          1.3      0.0      0.0      0.0
China Petrochem.               1314 TT            Commodity Chemicals                                                                             0.0      0.0      0.0      0.0
China Resources                1313 HK            Construction Materials                                                                          0.3      0.0      0.0      0.0
China Shanshui                  691 HK            Construction Materials                                                                          0.5      0.0      0.0      0.0
China Steel                    2002 TT            Steel (mazufacturer)                                                                            1.1      0.0      0.0      0.0
China Zhongwang                1333 HK            Aluminium                                                                                       0.1      0.0      0.0      0.0
Cmpc                           CMPC CI            Paper, Forest Prod                                                                              0.5      0.0      0.0      0.0
Csg Holding 'B'               200012 CH           Construction Materials                                                                          0.2      0.0      0.0      0.0
Sider.Nacional On             CSNA3 BZ            Iron Ore                         Steel (Integ.)       Che.Fer, Agri,Logi                        1.0      0.6      0.1      0.0
Dongkuk Steel Mill            001230 KS           Steel (mazufacturer)                                                                            0.3      0.0      0.0      0.0
Dongyue Group                   189 HK               Che.Fer, Agri,Logi                                                                           0.3      0.0      0.0      0.0
Duratex On                    DTEX3 BZ            Paper, Forest Prod                                                                              0.2      0.0      0.0      0.0
Eregli Demir Celik            EREGL TI            Steel (mazufacturer)                                                                            0.3      0.0      0.0      0.0
Eternal Chemical               1717 TT            Commodity Chemicals                                                                             0.1      0.0      0.0      0.0
Exxaro Resources                EXX SJ            Power                        Zinc, Molyb, Lead                                                  0.7      0.0      0.0      0.0
Feng Hsin I&S                  2015 TT            Steel (mazufacturer)                                                                            0.2      0.0      0.0      0.0
Formosa Chems.                 1326 TT            Commodity Chemicals                                                                             1.5      0.0      0.0      0.0
Formosa Plastics               1301 TT            Commodity Chemicals                                                                             2.0      0.0      0.0      0.0
Fosun Internat.                 656 HK            Steel (Integrated)                  Iron Ore          Che.Fer, Agri,Logi                        0.0      0.1      0.1      0.0
Metalurgica Ger.              GOAU4 BZ            Steel (mazufacturer)                                                                            0.6      0.0      0.0      0.0
Gerdau Pn                     GGBR4 BZ            Steel (mazufacturer)                                                                            1.1      0.0      0.0      0.0
Gold Fields                     GFI SJ            Gold, Silver                                                                                    1.9      0.0      0.0      0.0
Gmexico 'B'                GMEXICOB MM            Copper                        Che.Fer, Agri,Logi      Zinc, Molyb, Lead                         1.6      0.5      0.2      0.0
Hanwha Chemical               009830 KS           Commodity Chemicals                                                                             0.5      0.0      0.0      0.0
Hanwha                        000880 KS           Commodity Chemicals                                                                             0.5      0.0      0.0      0.0
Harmony Gold.                  HAR SJ             Gold, Silver                                                                                    0.3      0.0      0.0      0.0
Hindalco Indust.               HNDL IN            Aluminium                                                                                       0.7      0.0      0.0      0.0
Honam Petrochem               011170 KS           Commodity Chemicals                                                                             0.9      0.0      0.0      0.0
Huabao Intl.Hdg.                336 HK               Che.Fer, Agri,Logi                                                                           0.3      0.0      0.0      0.0
Hyosung                       004800 KS           Commodity Chemicals                                                                             0.2      0.0      0.0      0.0
Hyundai Hysco                 010520 KS           Steel (mazufacturer)                                                                            0.2      0.0      0.0      0.0
Hyundai Steel                 004020 KS           Steel (mazufacturer)                                                                            1.1      0.0      0.0      0.0
Impala Platinum                 IMP SJ            Platinum                                                                                        1.4      0.0      0.0      0.0
Ict.Tunggal                     INTP IJ           Construction Materials                                                                          0.3      0.0      0.0      0.0
Indorama                        IVL TB            Commodity Chemicals                                                                             0.3      0.0      0.0      0.0
Pe&Oles                     PE&OLES* MM           Gold, Silver                      Gold, Silver                 Copper      Zinc, Molyb, Lead    0.2      0.4      0.1      0.1
Vale Indonesia                 INCO IJ            Nickel                                                                                          0.2      0.0      0.0      0.0
Inverargos                  INVARGOS CB           Construction Materials                                                                          0.2      0.0      0.0      0.0
Jsw                            JSW PW             Coal                                                                                            0.4      0.0      0.0      0.0
Jiangxi Copper 'H'              358 HK            Copper                            Gold, Silver                                                  0.8      0.1      0.0      0.0
Source: MSCI, Bloomberg. Note: Che, Fer, Agri, Logi represents Chemicals, Fertilizers, agriculture, logistics.




                                                                                                                                                                               77
Adrian Mowat                                                  Emerging Markets Equity Research
(852) 2800-8599                                               23 February 2012
adrian.mowat@jpmorgan.com




Table 41: Weight of MSCI EM Materials constituents based on earnings contribution
                                                                                  MSCI EM Constituent name                                     MSCI EM Weight (Based on 2011
                                                                                                                                                       revenue Mix)
Name                        BBG Ticker               Constituent1                Constituent2             Constituent3      Constituent4     Constitu Constitu Constitu Constit
                                                                                                                                              ent1     ent2     ent3     uent4
Jindal Steel                  JSP IN           Steel (Integrated)                    Power                                                     0.3      0.3      0.0      0.0
Jsw Steel                    JSTL IN           Steel (manufacturer)                                                                            0.2      0.0      0.0      0.0
Kghm                         KGH PW            Copper                          Che.Fer, Agri,Logi                                              3.8      0.1      0.0      0.0
Klabin Sa Pn                KLBN4 BZ           Paper,Forest Products                                                                           0.1      0.0      0.0      0.0
Kumho Petro                011780 KS           Commodity Chemicals                                                                             0.3      0.0      0.0      0.0
Korea Zinc                 010130 KS           Copper                             Gold, Silver          Zinc, Molyb, Lead                      0.1      0.2      0.3      0.0
Koza Altin                  KOZAL TI           Gold, Silver                                                                                    0.1      0.0      0.0      0.0
Kp Chemical                064420 KS           Commodity Chemicals                                                                             0.3      0.0      0.0      0.0
Kumba Iron Ore                KIO SJ           Iron Ore                                                                                        1.1      0.0      0.0      0.0
Lafarge Malayan              LMC MK            Construction Materials                                                                          0.1      0.0      0.0      0.0
Lee & Man Paper              2314 HK           Paper,Forest Products                                                                           0.2      0.0      0.0      0.0
Lcy Chemical                 1704 TT           Commodity Chemicals                                                                             0.1      0.0      0.0      0.0
Lg Chem                    051910 KS           Commodity Chemicals                                                                             2.5      0.0      0.0      0.0
Lg Chem 1Pf                051910 KS           Commodity Chemicals                                                                             0.4      0.0      0.0      0.0
Mechel Oao                  MTLR RM            Iron Ore                        Steel (Integrated)             Power                            0.5      0.1      0.0      0.0
Mexchem                   MEXCHEM*MM           Commodity Chemicals                                                                             0.3      0.0      0.0      0.0
Mfrisco                   MFRISCOAMM           Gold, Silver                         Copper              Zinc, Molyb, Lead                      0.0      0.0      0.0      0.0
Minmetals Res.               1208 HK           Copper                          Zinc, Molyb, Lead            aluminium                          0.2      0.1      0.0      0.0
Mmx Miner On Nm            MMXM3 BZ            Iron Ore                                                                                        0.1      0.0      0.0      0.0
Nan Ya Plastics              1303 TT           Commodity Chemicals                                                                             1.5      0.0      0.0      0.0
Nine Dragons                 2689 HK           Paper,Forest Products                                                                           0.2      0.0      0.0      0.0
Mmc Norilsk                GMKN RM             Nickel                                Copper                  Platinum                          1.3      0.6      0.6      0.0
Northam Platinum             NHM SJ            Platinum                                                                                        0.1      0.0      0.0      0.0
Ojsc Novolipetsk            NLMK RM            Steel (Integrated)                   Iron Ore                                                   0.3      0.1      0.0      0.0
Oci                        010060 KS           Che.Fer, Agri,Logi                                                                              1.1      0.0      0.0      0.0
Petronas Chem.             PCHEM MK            Commodity Chemicals                                                                             0.6      0.0      0.0      0.0
Posco                      005490 KS           Steel (mazufacturer)                                                                            5.2      0.0      0.0      0.0
Pretoria Port.Cmt.           PPC SJ            Construction Materials                                                                          0.2      0.0      0.0      0.0
Ptt Global Chem            PTTGC TB            Commodity Chemicals                                                                             0.7      0.0      0.0      0.0
Sappi                        SAP SJ            Paper,Forest Products                                                                           0.2      0.0      0.0      0.0
Semen Gresik                 SMGR IJ           Construction Materials                                                                          0.4      0.0      0.0      0.0
Sesa Goa                     SESA IN           Iron Ore                                                                                        0.7      0.0      0.0      0.0
Severstal                   CHMF RM            Iron Ore                        Steel (Integrated)                                              0.3      0.6      0.0      0.0
Shougang Fushan               639 HK           Coal                                                                                            0.3      0.0      0.0      0.0
Siam Cement Fb               SCC TB            Construction Materials                                                                          0.5      0.0      0.0      0.0
Sinofert Holdings             297 HK           Che.Fer, Agri,Logi                                                                              0.1      0.0      0.0      0.0
Sinopec Shai.                 338 HK           Commodity Chemicals                                                                             0.2      0.0      0.0      0.0
Sqm 'B'                     SQM/B CI           Che.Fer, Agri,Logi                                                                              0.4      0.0      0.0      0.0
Southern Copper             SCCO US            Copper                                                                                          0.9      0.0      0.0      0.0
Sterlite Inds.(India)        STLT IN           Copper                          Zinc, Molyb, Lead            aluminium                          0.1      0.6      0.0      0.0
Suzano Papel Pna            SUZB5 BZ           Paper,Forest Products                                                                           0.0      0.0      0.0      0.0
Synthos                      SNS PW            Commodity Chemicals                                                                             0.2      0.0      0.0      0.0
Taiwan Cement                1101 TT           Construction Materials                                                                          0.5      0.0      0.0      0.0
Taiwan Fertilizer            1722 TT           Che.Fer, Agri,Logi                                                                              0.2      0.0      0.0      0.0
Tata Steel                   TATA IN           Steel (Integrated)            Steel (manufacturer)                                              0.3      0.5      0.0      0.0
Tsrc                         2103 TT           Commodity Chemicals                                                                             0.3      0.0      0.0      0.0
Tung Ho Stl.Enter.           2006 TT           Steel (mazufacturer)                                                                            0.1      0.0      0.0      0.0
Ultratech Cement           UTCEM IN            Construction Materials                                                                          0.1      0.0      0.0      0.0
United Phosph.               UNTP IN           Che.Fer, Agri,Logi                                                                              0.1      0.0      0.0      0.0
Uralkali                    URKA RM            Che.Fer, Agri,Logi                                                                              0.6      0.0      0.0      0.0
Usiminas On                 USIM3 BZ           Steel (mazufacturer)                                                                            0.1      0.0      0.0      0.0
Usiminas Pna                USIM3 BZ           Steel (mazufacturer)                                                                            0.2      0.0      0.0      0.0
Vale On                     VALE3 BZ           Iron Ore                             Copper                    Nickel      Che.Fer, Agri,Logi   11.3     0.5      0.1      0.5
Vale Pna                    VALE3 BZ           Iron Ore                             Copper                    Nickel      Che.Fer, Agri,Logi   17.3     0.2      0.8      0.8
Volcabc1                  VOLCABC1PE           Copper                          Zinc, Molyb, Lead                                               0.0      0.3      0.0      0.0
Fibria On                   FIBR3 BZ           Paper,Forest Products                                                                           -0.2     0.0      0.0      0.0
Yingde Gases                 2168 HK           Paper,Forest Products                                                                           0.1      0.0      0.0      0.0
Zhaojin Mining               1818 HK           Gold, Silver                                                                                    0.2      0.0      0.0      0.0
Zijin Mining Group           2899 HK           Gold, Silver                                                                                    0.5      0.0      0.0      0.0
Source: MSCI, Bloomberg. Note: Che, Fer, Agri, Logi represents Chemicals, Fertilizers, agriculture, logistics.




78
   Adrian Mowat                           Emerging Markets Equity Research
   (852) 2800-8599                        23 February 2012
   adrian.mowat@jpmorgan.com




   China property data: Insights
   The data is produced by the National Bureau of Statistics.
   It is available from CEIC and Bloomberg.                             Construction starts
                                                                        Total construction starts data is available monthly from
                                                                        January 1996.
  CEIC Identifiers
 Total floor space started: CECD                                       Residential construction starts data is monthly from
                                                                        January 2009.
 Total floor space sold: CECF
 Total floor space completed: CRKAGSE                                  Sales
                                                                        Total floor space sold and residential floor space sold is
 Residential floor space started: CRKARRI                              available monthly from January 1996 and March 1998
 Residential floor space sold: CECJ                                    respectively.

 Residential floor space completed: CECM                               Completions
 YTD Residential ASP RMB/sqm: CEGAA (Note that                         Total floor space and residential floor space completed
  this is a simple average figure and it ignores the change             data are available monthly.
  in product mix)
                                                                        The data on total floor space completed does not
                                                                        reconcile with total construction starts in a year. Total
  Bloomberg Tickers                                                     floor space completed is on average 65% higher than
 Residential floor space under construction : CHRESPRE                 total floor space started in a year offset by 12 months
  Index                                                                 since 2005.
 Residential floor space sold: CHRESARE Index
 Residential floor space completed: CHRECORE Index




                                                                                                                                     79
Adrian Mowat                            Emerging Markets Equity Research
(852) 2800-8599                         23 February 2012
adrian.mowat@jpmorgan.com




Seasonality
Methodology                                                                     so that they sum to exactly 100% times the
We perform seasonal adjustment using the centered                               number of periods in a season, or 1200% in this
moving average approach.                                                        case.

     1.   We first take the mean of two one-year-wide                      4.   Finally the seasonalized data is calculated as
          moving averages of the data around each of the                        actual monthly data divided by the monthly
          months. These moving averages are offset by                           seasonal factor.
          one period relative to each other.
                                                                      Do not expect any spike in residential sales data at
     2.   Next we compute the ratio of the original data in           year end
          each month by this calculated mean.                         In contrast to the national data we do not see any sharp
                                                                      rise in residential sales in the eight large cities during
     3.   Seasonal factor for each month is then                      December. Residential sales are lowest in the months
          computed by averaging all the ratios for that               January and February for eight large cities following the
          particular month. These are then renormalized               trend in the national residential sales.




80
Adrian Mowat                                         Emerging Markets Equity Research
(852) 2800-8599                                      23 February 2012
adrian.mowat@jpmorgan.com



Table 42: China cement production data (million tonnes)
Date           Data         Trend-Cycle          Ratio       Seasonal   Seasonally     3 Month Moving       3 Month Moving Average       Seasonally
                           (Ctr-Mov-Avg)     (Seasonality)    Index      Adjusted         Average          Seasonally Adjusted (%oya)   Adjusted Data
                                                                           Data      Seasonally Adjusted                                   (%oya)
Jan-07         83.70            109.39         76.51%         74.76%      111.96           109.56                    16.68                  28.97
Feb-07         65.01            110.44         58.87%         63.23%      102.81           107.15                    16.31                  13.08
Mar-07         93.09            111.29         83.64%         97.00%       95.97           103.58                    13.73                  0.49
Apr-07        116.44            112.02         103.94%       109.94%      105.92           101.57                     8.51                  12.23
May-07        128.69            111.29         115.64%       115.40%      111.51           104.47                    10.19                  17.97
Jun-07        127.33            109.30         116.49%       113.82%      111.86           109.76                    14.44                  13.18
Jul-07        117.48            110.23         106.58%       102.79%      114.29           112.56                    13.36                  9.35
Aug-07        120.81            113.31         106.62%       103.91%      116.26           114.14                    10.90                  10.29
Sep-07        125.20            115.13         108.75%       106.54%      117.52           116.02                    10.37                  11.47
Oct-07        123.80            115.84         106.87%       104.87%      118.06           117.28                     9.85                  7.88
Nov-07        125.47            115.66         108.48%       104.50%      120.06           118.55                     9.46                  9.12
Dec-07        123.28            115.45         106.78%       103.23%      119.42           119.18                     9.62                  11.92
Jan-08         82.68            115.67         71.48%         74.76%      110.59           116.69                     6.51                  -1.22
Feb-08         59.58            115.72         51.49%         63.23%       94.22           108.08                     0.86                  -8.35
Mar-08        113.23            115.76         97.82%         97.00%      116.74           107.18                     3.48                  21.63
Apr-08        124.88            115.86         107.78%       109.94%      113.59           108.18                     6.52                  7.25
May-08        131.98            114.03         115.74%       115.40%      114.36           114.90                     9.98                  2.56
Jun-08        131.81            112.21         117.47%       113.82%      115.80           114.59                     4.39                  3.52
Jul-08        119.43            114.62         104.19%       102.79%      116.19           115.45                     2.57                  1.66
Aug-08        119.86            118.32         101.30%       103.91%      115.35           115.78                     1.44                  -0.79
Sep-08        124.23            120.53         103.07%       106.54%      116.61           116.05                     0.02                  -0.77
Oct-08        123.09            122.44         100.53%       104.87%      117.38           116.44                    -0.71                  -0.57
Nov-08         126.8            123.93         102.32%       104.50%      121.34           118.44                    -0.09                  1.06
Dec-08        125.27            125.60         99.74%        103.23%      121.35           120.02                     0.71                  1.61
Jan-09          75.8            128.16         59.14%         74.76%      101.39           114.69                    -1.71                  -8.32
Feb-09          82.9            130.80         63.38%         63.23%      131.10           117.95                     9.13                  39.14
Mar-09        122.07            133.11         91.71%         97.00%      125.85           119.45                    11.44                  7.81
Apr-09        146.78            134.88         108.82%       109.94%      133.51           130.15                    20.31                  17.54
May-09        148.88            135.19         110.13%       115.40%      129.01           129.46                    12.67                  12.80
Jun-09         157.6            135.11         116.64%       113.82%      138.46           133.66                    16.65                  19.57
Jul-09        144.87            137.46         105.39%       102.79%      140.94           136.13                    17.92                  21.30
Aug-09        149.75            141.01         106.20%       103.91%      144.11           141.17                    21.93                  24.94
Sep-09        156.31            143.54         108.90%       106.54%      146.72           143.92                    24.02                  25.82
Oct-09        156.35            145.55         107.42%       104.87%      149.10           146.64                    25.93                  27.02
Nov-09        150.96            146.82         102.82%       104.50%      144.46           146.76                    23.91                  19.05
Dec-09        144.98            147.98         97.97%        103.23%      140.44           144.66                    20.53                  15.73
Jan-10        115.21            149.66         76.98%         74.76%      154.10           146.33                    27.59                  51.99
Feb-10         83.78            151.00         55.48%         63.23%      132.49           142.34                    20.69                  1.06
Mar-10        135.99            152.31         89.28%         97.00%      140.20           142.26                    19.10                  11.40
Apr-10        161.15            153.81         104.77%       109.94%      146.59           139.76                     7.38                  9.79
May-10        173.58            153.42         113.14%       115.40%      150.41           145.73                    12.57                  16.59
Jun-10        174.48            151.27         115.34%       113.82%      153.29           150.09                    12.30                  10.71
Jul-10        164.92            153.34         107.55%       102.79%      160.44           154.71                    13.65                  13.84
Aug-10         167.8            158.35         105.97%       103.91%      161.48           158.40                    12.21                  12.05
Sep-10        170.46            161.61         105.48%       106.54%      160.00           160.64                    11.62                  9.05
Oct-10         170.3            163.90         103.91%       104.87%      162.40           161.29                     9.99                  8.92
Nov-10        176.58            165.16         106.91%       104.50%      168.97           163.79                    11.61                  16.97
Dec-10        169.66            166.17         102.10%       103.23%      164.35           165.24                    14.22                  17.02
Jan-11        116.15            167.71         69.26%         74.76%      155.36           162.89                    11.32                  0.82
Feb-11         88.14            169.35         52.05%         63.23%      139.39           153.03                     7.51                  5.20
Mar-11        164.56            170.81         96.34%         97.00%      169.66           154.80                     8.81                  21.01
Apr-11        185.56            171.43         108.24%       109.94%      168.79           159.28                    13.97                  15.15
May-11        196.28            171.45         114.48%       115.40%      170.08           169.51                    16.31                  13.08
Jun-11        197.94            252.44         78.41%        113.82%      173.90           170.92                    13.88                  13.45
Jul-11        183.08            344.50         53.14%        102.79%      178.11           174.03                    12.48                  11.01
Aug-11        182.43            365.20         49.95%        103.91%      175.56           175.86                    11.02                  8.72
Sep-11        190.31            385.27         49.40%        106.54%      178.63           177.43                    10.45                  11.64
Oct-11        190.63            408.25         46.69%        104.87%      181.78           178.66                    10.77                  11.94
Nov-11        188.06            436.63         43.07%        104.50%      179.96           180.12                     9.97                  6.50
Dec-11        175.08            475.00         36.86%        103.23%      169.60           177.11                     7.19                  3.19
Source: Bloomberg, J.P.Morgan calculations




                                                                                                                                                    81
Adrian Mowat                                          Emerging Markets Equity Research
(852) 2800-8599                                       23 February 2012
adrian.mowat@jpmorgan.com




Table 43: Steel production data (thousand tonnes)
Date                 Data      Trend-Cycle          Ratio   Seasonal    Seasonally     3 Month Moving     3 Month Moving Average       Seasonally
                                                                                          Average                                     Adjusted Data
                              (Ctr-Mov-Avg) (Seasonality)     Index    Adjusted Data Seasonally Adjusted Seasonally Adjusted (%oya)      (%oya)
Jan-07              38119         39275         97%            98%         38895           38525                     23                    26
Feb-07              36135         39767         91%            92%         39118           38578                     23                    23
Mar-07              40157         40104        100%           102%         39370           39128                     24                    22
Apr-07              40318         40310        100%           101%         40062           39517                     21                    20
May-07              41304         40535        102%           104%         39838           39757                     19                    15
Jun-07              42121         40660        104%           102%         41424           40441                     16                    15
Jul-07              41252         41025        101%           101%         40667           40643                     15                    14
Aug-07              41583         41535        100%           102%         40779           40957                     14                    13
Sep-07              42712         41927        102%           100%         42884           41443                     15                    18
Oct-07              42922         42363        101%           100%         42824           42162                     15                    14
Nov-07              39691         42687         93%            97%         40740           42149                     12                      5
Dec-07              41314         42844         96%           101%         40923           41495                       9                     8
Jan-08              40564         42819         95%            98%         41390           41017                       6                     6
Feb-08              38884         42481         92%            92%         42094           41469                       7                     8
Mar-08              44868         41921        107%           102%         43989           42491                       9                   12
Apr-08              44676         41551        108%           101%         44393           43492                     10                    11
May-08              46013         41473        111%           104%         44380           44254                     11                    11
Jun-08              46944         41467        113%           102%         46167           44980                     11                    11
Jul-08              44886         41620        108%           101%         44250           44932                     11                      9
Aug-08              42568         41678        102%           102%         41745           44054                       8                     2
Sep-08              39614         41628         95%           100%         39774           41923                       1                    -7
Oct-08              35901         41651         86%           100%         35819           39112                      -7                   -16
Nov-08              35189         41742         84%            97%         36118           37237                     -12                   -11
Dec-08              37792         42119         90%           101%         37434           36457                     -12                    -9
Jan-09              41193         42655         97%            98%         42031           38528                      -6                     2
Feb-09              40530         43387         93%            92%         43876           41114                      -1                     4
Mar-09              42900         44346         97%           102%         42060           42656                       0                    -4
Apr-09              42340         45457         93%           101%         42071           42669                      -2                    -5
May-09              45900         46528         99%           104%         44271           42801                      -3                     0
Jun-09              45390         47172         96%           102%         44638           43660                      -3                    -3
Jul-09              49930         47840        104%           101%         49222           46044                       2                   11
Aug-09              51720         48807        106%           102%         50720           48193                       9                   21
Sep-09              49670         49811        100%           100%         49870           49937                     19                    25
Oct-09              51530         50593        102%           100%         51412           50667                     30                    44
Nov-09              48930         51087         96%            97%         50223           50502                     36                    39
Dec-09              51040         51430         99%           101%         50557           50731                     39                    35
Jan-10              49800         51440         97%            98%         50813           50531                     31                    21
Feb-10              45930         51321         89%            92%         49722           50364                     22                    13
Mar-10              53160         51182        104%           102%         52119           50885                     19                    24
Apr-10              55400         51208        108%           101%         55048           52296                     23                    31
May-10              55950         51453        109%           104%         53964           53710                     25                    22
Jun-10              52620         51630        102%           102%         51749           53587                     23                    16
Jul-10              51524         52230         99%           101%         50794           52169                     13                      3
Aug-10              52700         52951        100%           102%         51681           51408                       7                     2
Sep-10              49220         53338         92%           100%         49418           50631                       1                    -1
Oct-10              49070         53662         91%           100%         48958           50019                      -1                    -5
Nov-10              48510         54051         90%            97%         49792           49389                      -2                    -1
Dec-10              52640         54628         96%           101%         52141           50297                      -1                     3
Jan-11              53699         55157         97%            98%         54792           52242                       3                     8
Feb-11              51740         55636         93%            92%         56011           54315                       8                   13
Mar-11              59587         55946        107%           102%         58420           56408                     11                    12
Apr-11              58242         56093        104%           101%         57872           57435                     10                      5
May-11              60371         56113        108%           104%         58228           58173                       8                     8
Jun-11              59405         56123        106%           102%         58421           58174                       9                   13
Jul-11              59300         56424        105%           101%         58460           58369                     12                    15
Aug-11              59847         53919        111%           102%         58690           58523                     14                    14
Sep-11              58130         50859        114%           100%         58364           58505                     16                    18
Oct-11              56223         49959        113%           100%         56095           57716                     15                    15
Nov-11              50130         48787        103%            97%         51454           55304                     12                      3
Dec-11              51284         47367        108%           101%         50798           52783                       5                    -3
Jan-12              50385         45465        111%            98%         51410           51221                      -2                    -6
Source: Bloomberg, CISA, J.P. Morgan calculations




82
Adrian Mowat                                              Emerging Markets Equity Research
(852) 2800-8599                                           23 February 2012
adrian.mowat@jpmorgan.com




Table 44: Determinants of home prices in China
                    Actual house                             Deviation    Change in
                                       Actual house                                             Impact of                                       Impact of House price House price
                        price                                   from     house price                            Impact of   Impact of
City                                   price growth                                               GDP                                             loan     to income    to income
                    (rmb/sqm) in                           fundamentals fundamentals                           urbanization inflation
                                      4Q08-2Q10 (%)                                              growth                                          growth   ratio (2007) ratio (2010)
                        2Q10                                in 2Q10 (%)      (%)
Beijing                25800                 25.1               24.8        19.4                    3.5              9.7            0.6            3.9        17.5         23.0
Tianjing                9563                 23.2                -3.2       20.1                    9.2            10.0             0.8            4.0        13.2         13.7
Shijiazhuang            5455                 6.9                 -8.4       20.6                    4.5              5.5            6.4           15.7        12.1         10.2
Taiyuan                 4917                 7.0                -13.4        9.3                    5.2             -0.8            1.9           10.6        10.1         10.2
Hohhot                  3263                 15.9               -17.1       21.7                   12.5              5.0            4.2            2.7         5.0          4.8
Shenyang                4799                 0.1                -12.6       10.8                    9.3             -1.7            4.6            4.7        10.1          6.5
Dalian                  8823                 8.3                 -3.3       17.0                   10.4              2.5            5.7            3.6        13.6         11.2
Changchun               5272                 17.5                 8.9       14.3                    7.2              0.6            8.0            5.2        12.3          8.5
Harbin                  4525                 9.8                  3.8        8.9                    7.9              2.4            1.5            3.2         8.8          8.1
Shanghai               18428                 47.3               16.6        26.6                    3.1            16.1             3.3            3.0        11.5         16.3
Nanjing                 6997                 0.7                -26.8       15.5                    8.2              2.3            2.8            3.2        10.7          7.5
Hangzhou               17237                 42.4               30.3        22.4                    4.5              4.4            6.4            8.3        12.6         17.2
Ningbo                 14960                 39.0               15.5        12.5                    6.1              1.0            0.6            6.5        12.0         15.2
Hefei                   5819                 39.1                 9.2       15.1                   14.4              3.2            1.1           -0.1         7.6          8.2
Fuzhou                  9685                 29.0               22.4        15.9                    8.0              1.4            4.4            5.6         9.7         14.1
Xiamen                 10825                 28.9                 7.8       21.8                    6.3              8.0            1.1            4.6        14.9          9.9
Nanchang                5005                 36.9               13.5         9.1                    9.0              2.2            1.7            6.9         8.5          8.7
Jinan                   6727                 37.8               15.0         9.8                    8.2              0.9            2.8            3.5         6.9          7.7
Qingdao                 6983                 20.0               -11.9       12.1                    7.5              0.3            3.3            4.2         9.5         15.7
Zhengzhou               5361                 11.3                 2.6       16.7                    6.8              1.8            7.1            4.7         9.0          9.9
Wuhan                   7364                 9.1                  1.3       13.1                   10.4              0.9            1.5            5.0        11.8         10.3
Changsha                5904                 -5.6                 2.6       15.4                   13.0              3.6            2.5            3.6        13.2          8.7
Guangzhou              13341                 13.3                -5.5       12.4                    6.8              0.5            3.6            2.5        15.6         10.8
Shenzhen               22224                 84.6               46.3        15.9                    4.2              3.9            1.1            5.9         7.9         16.9
Nanning                 7744                 53.6               28.5        11.8                    7.9              1.8           -0.4            7.6         8.9         11.6
Haikou                  6243                 41.3               13.5        20.6                    8.7              3.5            5.0            7.5         7.7          9.9
Chongqing               4366                 14.9                -5.5       18.3                   17.8              0.3            5.4           -0.4         6.5          7.1
Chengdu                 7615                 36.8                 0.7       25.3                    9.8              3.0            7.2           12.6        11.5         10.3
Guiyang                 7395                 43.9               14.9         9.8                   10.5              0.6            2.3            1.7        10.9         15.1
Kunming                 8624                 54.3               26.1        25.2                    6.9            12.0             8.4            2.3        11.6         16.3
Xian                    6282                 29.6               13.1        16.4                   12.9              5.6            2.6            6.4         9.6         11.5
Lanzhou                 7035                 87.2               42.3        15.2                    6.8              2.7            3.6            5.9         7.8         15.5
Xining                  3734                 23.7                 6.8        3.2                   19.7            -22.1           12.9            2.1         8.3          7.8
Yinchuan                4860                 21.5                -6.6       14.6                    9.9              2.9            3.5            4.0         8.2          8.9
Urumqi                  5680                 34.4               11.2        17.2                    4.4              1.6            3.3           12.2         9.6         13.7
Average                 8539                 28.2                 7.5       15.8                    8.6              2.7            3.7            5.2        10.0         10.6
Source: J.P.Morgan Economics. Note: The results are based on a panel EGLS regression using data from 35 cities in China from 1Q2004 to 2Q2011




                                                                                                                                                                                  83
                                                                                                            Global Emerging Markets Equity
                                                                                                            Research
                                                                                                            13 June 2012




                                                                                                                     EM 101
China challenged
Lessons from other Asian bubbles


 MSCI China’s trailing PE of 9 is lowest of the major EMs. It is not rated                                 Emerging Markets Equity Strategy
  as a growth market. This is rational. The three inflection points for its                                 Adrian Mowat
                                                                                                                              AC

  economy and returns are demographic, 2008/9 stimulus and June 2011                                        (852) 2800-8599
  peak in the property market bubble.                                                                       adrian.mowat@jpmorgan.com

                                                                                                            J.P. Morgan Securities (Asia Pacific) Limited
 Japan’s and Taiwan’s late ’80s bubbles are good analogies. Both
  countries had excess savings (large current account surplus), momentum                                    David Aserkoff, CFA
                                                                                                            (44-20) 7325-1775
  in equity and property markets plus demographic challenge. Unlike the                                     david.aserkoff@jpmorgan.com
  Western property bubbles, household leverage was modest. But credit to
                                                                                                            J.P. Morgan Securities Ltd.
  GDP was high. Equity markets peaked three to four years prior to
  property prices. Equity valuations corrected faster than property prices.                                 Rajiv Batra
                                                                                                            (91-22) 6157-3568
  The deflation in property prices was a multiyear event.                                                   rajiv.j.batra@jpmorgan.com

 The post bubble period in Japan and Taiwan for equities investors was                                     J.P. Morgan India Private Limited
  challenging, characterized by a self defeating market timing herd. The                                    Sanaya Tavaria
  track record of H and A-shares is poor. Both Chinese savers and the                                       (1-212) 622-5469
  government need an equity investment culture.                                                             sanaya.x.tavaria@jpmorgan.com

                                                                                                            J.P. Morgan Securities LLC
 All is not lost. The deflation in Chinese equity valuations was rapid.
                                                                                                            Prateek Parekh
  Even if economic growth slows to 3-6% it will still be higher than EM                                     (91-22) 6157-3277
  average, let alone DM. We believe modest changes in governance,                                           prateek.parekh@jpmorgan.com
  particularly a progressive dividend policy, can convert a trading market                                  J.P. Morgan India Private Limited
  into a destination for long term savings. The fiscal burden will grow due
  to an ageing population, slower growth and the need to subsidize low
  return assets. Privatization of SoEs could help this but only if there are
  local and international investors willing to buy.                                                         For more reports on China
                                                                                                            please see:
 On pages 90 to 95, we compare monetary, economic and market
  characteristics of Japan, Taiwan and China. The time period is 10 years
                                                                                                            Impact of China slowdown on
  around the equity market bubble. Property price appreciation in China                                     Equities: EM equities as China
  was faster. Chinese apartment prices are a third of Japan’s but per capita                                slows, Mowat et. al, 23 February
  GDP was a tenth of Japan’s at the bubble!                                                                 2012
Figure 107: Not discounting growth: China trailing PE relative to EM and World
  200
                                                                                                            Demographics: China 2020:130
                                                   MSCI World    MSCI EM
                                                                                                            million swing, Mowat et. al 31
  150
                                                                                                            May 2011
  100
    50                                                                                                      Comparison of China with Asia
     0                                                                                                      Bubbles: Triple merit theme,
   -50                                                                                                      Mowat et. al., 11 January 2007
  -100
     Dec 97                  Dec 00                Dec 03       Dec 06             Dec 09



Source: J.P. Morgan economics, %oya, both scales


See page 98 for analyst certification and important disclosures, including non-US analyst disclosures.
J.P. Morgan does and seeks to do business with companies covered in its research reports. As a result, investors should be aware that the
firm may have a conflict of interest that could affect the objectivity of this report. Investors should consider this report as only a single factor in
making their investment decision.

                                                                                                                    www.morganmarkets.com
Adrian Mowat                           Global Emerging Markets Equity Research
(852) 2800-8599                        13 June 2012
adrian.mowat@jpmorgan.com




Three inflection points
China’s labour market is tight. A China Confidential                 Figure 108: More 19-year-olds in Tertiary Education - Less for
survey of 203 companies found that 30% of job                        construction, manufacturing and agriculture
vacancies were unfilled in May. This decade the non-                 Millions
graduate population between 15-39 will decline by
                                                                      30.0
130million or 25% (see China 2020: 130 million swing,                                                        Under-graduates       Non-graduates
Mowat et al, 31 May 2011). The result is that labour has              25.0
pricing power. Overall GDP growth can slow while                      20.0
household income continues to rise. The challenge for
the PBoC is wage inflation equals core inflation.                     15.0
Balancing price stability and growth will be much harder              10.0
in this decade than the past three. The second challenge
is xiaobailing (white collar) employment. Can China find               5.0
jobs for the 10million graduates entering the workforce                0.0
each year? A low cost of capital and competitive


                                                                             1990
                                                                             1993
                                                                             1996
                                                                             1999
                                                                             2002
                                                                             2005
                                                                             2008
                                                                             2011
                                                                             2014
                                                                             2017
                                                                             2020
                                                                             2023
                                                                             2026
                                                                             2029
                                                                             2032
                                                                             2035
                                                                             2038
                                                                             2041
                                                                             2044
                                                                             2047
currency can boost manufacturing. Fiscal spending and
loan growth can boost construction activity. But creating            Source: PRC NBS, Ministry of Education PRC, US Census, J.P. Morgan calculation
service sector jobs for the expanding xiaobailing work
force is difficult to achieve via policy. Generational               Figure 109: Running low on factory workers - Change in the non-
change may be another challenge. The rapid growth                    graduate available workforce 15-39 years old
since 1979 was a combination of large ambitious                      %oya, Millions
industrious underemployed agrarian workforce combined                   3%                                                                            600
with good macroeconomic policy. The result was a                        2%                                          %oya           Number
period of rapid growth with low inflation. The generation                                                                                             500
                                                                        1%
entering the workforce appreciation of the hardship of                  0%                                                                            400
China’s pre-reform economy may be less willing to                      -1%
                                                                                                                                                      300
accept manual jobs and long hours.                                     -2%
                                                                       -3%                                                                            200
Savings are now trapped in low return assets                           -4%
                                                                                                                                                      100
Between September 2008 and March 2010 total bank                       -5%
loans increased by 44% from RMB29.6trillion to                         -6%                                                                            0
                                                                                 1990
                                                                                 1993
                                                                                 1996
                                                                                 1999
                                                                                 2002
                                                                                 2005
                                                                                 2008
                                                                                 2011
                                                                                 2014
                                                                                 2017
                                                                                 2020
                                                                                 2023
                                                                                 2026
                                                                                 2029
                                                                                 2032
                                                                                 2035
                                                                                 2038
                                                                                 2041
                                                                                 2044
                                                                                 2047
RMB42.6trillion. The increase in loans in this period was
equivalent to half nominal GDP. At the end of 2010 local
                                                                     Source: PRC NBS, Ministry of Education PRC, US Census, J.P. Morgan calculation
government funding vehicles loans were 27% of GDP.
China is a growing economy. It needs infrastructure,
                                                                     Figure 110: China: real fixed asset investment and bank loan
housing, factories etc. But assets need to service capital.          growth
A vibrant economy needs to recycle capital in that high
return investment provide a return and repay capital                     50                                                                                    35
freeing up the money for new projects. The risk post the                                                 Fixed asset
                                                                                                         investment
2008/9 stimulus is that capital is trapped in low return                 40                           (adjusted by PPI)                                        30
assets.
                                                                         30                                                                                    25

                                                                         20                                                                                    20

                                                                         10                                                       Bank loans                   15

                                                                             0                                                                                 10
                                                                                 02   03   04    05     06     07       08   09     10   11     12        13
                                                                     Source: J.P. Morgan economics, %oya, both scales




                                                                                                                                                          85
Adrian Mowat                            Global Emerging Markets Equity Research
(852) 2800-8599                         13 June 2012
adrian.mowat@jpmorgan.com
With local government revenue weak, increase transfers                 Figure 111: Japan Government Gross Debt/GDP
from Central government will add to fiscal stress. This               % of GDP
potential fiscal stress plus a fear of adding to low return             250
or even non-performing assets constrains a fiscal
stimulus. The IMF estimate China’s gross debt to GDP                    200
to be 10%. But if local government, railroad and
development bank bonds are included, Chinese public
                                                                        150
sector debt to GDP is above 60%. This is similar to
Japanese government debt to GDP ratio when its equity
                                                                        100
bubble burst. As is the case in Japan, China's ageing
population increases health and social security liabilities.
Japan attempted to maintain growth through large, and                    50




                                                                                 1980
                                                                                 1982
                                                                                 1984
                                                                                 1986
                                                                                 1988
                                                                                 1990
                                                                                 1992
                                                                                 1994
                                                                                 1996
                                                                                 1998
                                                                                 2000
                                                                                 2002
                                                                                 2004
                                                                                 2006
                                                                                 2008
                                                                                 2010
                                                                                 2012
                                                                                 2014
                                                                                 2016
often wasteful, public works projects. The result was a
rapid deterioration in public finances (see Figure 111).
                                                                      Source: IMF, Bloomberg

Two private sector impact of the stimulus. The first is
overestimating growth rates. In 2009 car sales doubled,               Figure 112: Car and truck sales…2009 boom 2012 bust?
                                                                      %oya, 3mmva
M2 growth increased by 28% and retail sales grew by
                                                                       150
18%. The second is overestimating profitability. The                                               Passenger Vehicle Sales (3mmva, %oya)
strong pickup in demand helped pricing power and                                                   Commercial Vehicles sales (3mmva, %oya)
margins. The private sector inflated capex plans, both                 100
overestimating profitability and growth. This year
demand is weak, discounting common and profits weak.                    50
The outlook for private investment is poor. Note the
weakness in truck sales.
                                                                         0
A slowing deflating property price balloon rather
bubble bursting. The average property price in 2010                    -50




                                                                                                                                            May 11



                                                                                                                                                          May 12
                                                                             Mar 06



                                                                                          Mar 07



                                                                                                     Mar 08



                                                                                                                  Apr 09



                                                                                                                               Apr 10
was 10.6 household income (see China’s housing
market: wide regional differences in manageable overall
price adjustment, Zhu et al, 4 November 2011). In 2010                Source: CEIC
the government introduced anti-speculative policies.
These policies target investors rather than owner                     Figure 113: China residential construction starts (advanced 12
occupiers. Anecdotal evidence of property price                       months) vs. residential property sales
discounting by developers started in a year ago. The                   150       sqm mn             Residential construction starts, 3mmva
deflation in prices is typically a multi-year event (see
page 89 for what happened in Japan and Taiwan). In                     130
                                                                                                    Residential Sales, 3mmva
Hong Kong, property prices fell 70% between 1997 and                   110
2003. Where China is different is the scale of the primary
property market. Construction activity is large and out-                90
of-step with demand (see Figure 113). The scale of
                                                                        70
construction activity is best demonstrated by the level of
per capita cement use (see Figure 134).                                 50

                                                                        30
                                                                         Jan-06 Feb-07 Feb-08 Feb-09 Feb-10 Mar-11 Mar-12 Mar-13
                                                                      Source: CEIC, J.P. Morgan calculations, May 2012. Note the numbers are seasonally
                                                                      adjusted




86
Adrian Mowat                                               Global Emerging Markets Equity Research
(852) 2800-8599                                            13 June 2012
adrian.mowat@jpmorgan.com
The North Asian analogies
Japan and Taiwan’s late ’80s bubbles are good analogies.                                              China however provided stimulus to global economy in
Both countries had excess savings (large current account                                              2009. China accounts for more than a third of GDP
surplus see Figure 127), momentum in equity and                                                       growth. A slowdown in economy would dampen global
property markets plus demographic challenge (For more                                                 risk sentiment. In EM equities as China slows, Mowat et.
please see Triple merit Theme: The sequel, Mowat et al,                                               al, 23 February 2012, we explain the impact on MSCI
11 January 2007). Unlike the Western property bubbles,                                                EM if China continues to slow.
household leverage was modest. But credit to GDP was
high. Equity markets peaked three to four years prior to                                              Figure 114: Oil in 1990 spiked
property prices. Equity valuations corrected faster than                                                   200
property prices. The deflation in property prices was a
                                                                                                           180
multiyear event—in Japan from 2H 1991 to 2H 1997 and
in Taiwan from 1994 Q2 to 1996Q2. Low loan to value                                                        160
ratios provide a large cushion to the financial system. But                                                140
the large equity stake in the property market extends the
period of deflation as sellers anchor on unrealistically                                                   120
high selling prices. Our main concern is the economic                                                      100
impact of the slowdown in construction activity.                                                             80

Using cement consumption as a proxy for construction                                                         60
                                                                                                              Jan 90    Mar 90      May 90     Jul 90   Sep 90        Nov 90
activity China is similar to Taiwan in 1994. Taiwan's per
capita cement consumption peaked at 1.3tonnes.                                                        Source: IMF, J.P. Morgan Economic

Consumption today is just 0.5tonnes. It is possible that
China's per capita cement consumption falls more as its                                               Figure 115: Exports to China as a % of total exports
                                                                                                      25
per capita GDP in today's dollars is a quarter of Taiwan's
in 1994.                                                                                              20

                                                                                                      15
The Japan analogy highlights the risk of failing to change
the growth model. China's advantage is that its leaders                                               10
acknowledge the need for change (Premier Wen Jiabao
                                                                                                       5
speech at NPC March 2012). But the incentives for local
government to follow an investment driven growth                                                       0
model are strong. Perhaps the biggest threat is an
unwillingness to accept lower headline GDP growth.

Post the equity market bubbles in Japan and Taiwan,                                                   Source: IMF, J.P. Morgan Economic
there was global recession due to spike in oil prices. The
oil prices doubled from June 1990 to September 1990. In
China, post the equity market bubble peak, there was
global financial crisis.
Figure 116: China in a class of its own: Fixed investment as a % of GDP around the equity market bubble
  50
                                         Japan             Taiwan              China
  45

  40

  35

  30

  25

  20
       -10y   -9y      -8y      -7y      -6y      -5y      -4y      -3y      -2y     -1y       0y       1y        2y      3y      4y      5y      6y    7y       8y       9y   10y
Source J.P. Morgan Economics. Note:. Ratios centered on peak of each equity market. Japan and Taiwan it is 1989 and China it is 2007.


                                                                                                                                                                                 87
Adrian Mowat                            Global Emerging Markets Equity Research
(852) 2800-8599                         13 June 2012
adrian.mowat@jpmorgan.com

Outlook for equity investors                                          Figure 117: Market composition based on major shareholders
                                                                                                      Institutional
All is not lost. The deflation in Chinese equity valuations                      Cross                   10%
was rapid. Even if economic growth slows to 3-6% it will                      shareholding
still be higher than EM average, let alone DM. We                                 1%
believe modest changes in governance, particularly a
progressive dividend policy, can convert a trading market                          Family
into a destination for long term savings. The fiscal                                13%
burden will grow due to an ageing population, slower                                                                                                                                        Government
growth and the need to subsidize low return assets.                                                                                                                                            75%
Privatisation of State owned Enterprises (SoEs) could
help this but only if there are local and international
investors willing to buy.
                                                                      Source: MSCI, J.P. Morgan
The SoEs are central to the outlook for Chinese equities.             Figure 118: Performance of MSCI China, China SOE's and
If policy makers wish, they can generate shareholder                  Tencent
                                                                        280
value. State-owned Assets Supervision and                                                                               MSCI China                                    China SOE                                    Tencent
Administration Commission (SASAC) in 2004 asked
SoEs to improve RoEs and increase dividends. This                       230
combined with healthy economic growth resulted in
sharp outperformance of major SoEs, including China
                                                                        180
Mobile (941 HK, N). But SoEs suffer from policy risk.
This was demonstrated with partial interest rate
deregulation in early June. In theory banks with low loan               130
to deposit ratios could choose not to offer a premium to
the minimum deposit rate. They did not. The result is a
                                                                          80
decline in net interest margins. Policy effectively                        Jun 09                     Dec 09                 Jun 10                 Dec 10                    Jun 11                Dec 11            Jun 12
transferred wealth from bank shareholders to depositors
                                                                      Source: MSCI, J.P. Morgan
and borrowers. More than three quarters of the MSCI
China is SoEs (see Figure 117).                                       Figure 119: Basket of stocks by dividend track record - HKSE
                                                                        450



China SoEs have marginally outperformed MSCI China                      400


by 1% over last 3 years (Figure 118). Note the top three                350


performers are non-SoEs, the three year CAGR for                        300
                                                                                                                                                                                                                             0 Cut
Brilliance China is 115%, Haier Electronics is 99% and                  250
                                                                                                                                                                                                                             1 Cut

Great Wall Motor is 92%. But there is a large dispersion                                                                                                                                                                     2 Cut
                                                                                                                                                                                                                             3 Cut
in returns across non-SoEs. China Dongxiang, Renhe                      200
                                                                                                                                                                                                                             4 Cut

Commercial and China Zhongwang are the worst                            150                                                                                                                                                  HSI
                                                                                                                                                                                                                             2 Cut ex HSBC
performing private companies.                                           100


                                                                         50

China State Construction, Weichai Power and Kunlun
                                                                          0
Energy are best performing SoEs over last three years.                    Jan 05    Jul 05   Jan 06   Jul 06   Jan 07   Jul 07   Jan 08   Jul 08   Jan 09   Jul 09   Jan 10    Jul 10   Jan 11   Jul 11   Jan 12

Sinofert Holding, Angang Steel and China Shipping                     Source: Bloomberg, Datastream, HKEx, J.P. Morgan
Development were the worst performers. Consumer                       Figure 120: Basket of stocks by dividend track record – Shanghai
discretionary, Consumer staples and IT stocks had the                 A
highest volatility adjusted three year returns (Table 45).              700



                                                                        600

What worked for investors are companies with a good
dividend track record (Figure 119 and Figure 120). The                  500


problem out of the 200 largest companies listed in                      400
                                                                                                                                                                                                                                   0 Cut
                                                                                                                                                                                                                                   1 Cut
Shanghai A-share market; there are only 12 companies                                                                                                                                                                               2 Cut

that have zero DPS cut since 2005, compared to 47                       300                                                                                                                                                        3 Cut
                                                                                                                                                                                                                                   4 Cut
companies in HKSE. A-share investing is currently                       200
                                                                                                                                                                                                                                   SHA Index

market timing, with investors particularly focused on
changes in government policy.                                           100



                                                                          0
                                                                          Jan 05    Jul 05   Jan 06   Jul 06   Jan 07   Jul 07   Jan 08   Jul 08   Jan 09   Jul 09   Jan 10   Jul 10    Jan 11   Jul 11   Jan 12


                                                                      Source: Bloomberg, Datastream, HKEx, J.P. Morgan

88
   Adrian Mowat                           Global Emerging Markets Equity Research
   (852) 2800-8599                        13 June 2012
   adrian.mowat@jpmorgan.com


   Property prices analysis
   The heterogeneous nature of property markets makes it                             Housing Index. This results in price of NT$8million or
   difficult to calculate average prices. In order to compare                        US$300,000 for 100sqm apartment in 1993 (peak in
   the property markets of China, Japan and Taiwan we use:                           property market).

   Indices/Data used:                                                           In 1993, the property prices in Taiwan were 13 times
   Japan: The cost per sqm of a condominium in Tokyo                             household disposable income. In 2010, the house price to
   area (Tokyo, Kanagawa, Saitama and Chiba) is used.                            income ratio was 23 for Beijing and 16 for Shanghai (see
                                                                                 China’s housing market: wide regional differences in
   Taiwan: Sinyi Housing Index is used. Sinyi is used                            manageable overall price adjustment, Zhu et al, 4
   based on real transaction price in the secondary market in                    November 2011).
   Northern Taiwan.                                                                  Figure 121: National average (RMB/sqm)
                                                                                       6,500
   China: National average house price per sqm is used. It
   is computed by dividing, total sales of residential
                                                                                       6,000
   buildings by floor space sold. These numbers are
   reported by National bureau of statistics.
                                                                                       5,500

  Conclusions:
                                                                                       5,000
 Property prices in Taiwan, peaked four years after equity
  markets peaked.
                                                                                       4,500
 We deflate the current property prices in Northern
  Taiwan (NT$17million for 100sqm flat) using Sinyi                                    4,000
                                                                                            May 09        Nov 09      May 10       Nov 10       May 11       Nov 11      May 12
                                                                                     Source: National Bureau of Statistics, J.P. Morgan calculations, May 2012


                                          Figure 122: Property prices trend around the equity market bubble

                                            140               Japan             Taiwan              China


Peak property prices in Japan in            130
1990 were US$700,000 for 100
sqm apartment (assuming
                                            120
exchange rate of 140).

                                            110
Property prices in Japan peaked
one year after equity markets
peaked.                                     100


                                             90
The correction in Japanese
property markets was very
severe. Property markets                     80
corrected by 23% in six months
post the peak.
                                             70


In Taiwan, the correction in                 60
property markets was gradual,
with prices coming of 8% in the
year post its peak                           50


                                             40
                                               -10y -9y -8y -7y -6y -5y -4y -3y -2y -1y 0y 1y 2y 3y 4y 5y 6y 7y 8y                                                9y 10y
                                          Source Sinyi: NBS, J.P. Morgan calculation, CEIC, Japan’s real estate economic institute. The property prices are rebased to 100 as
                                          of the year in which the equity markets peaked. For China, it is 2007, Japan and Taiwan it is 1989



                                                                                                                                                                            89
  Adrian Mowat                     Global Emerging Markets Equity Research
  (852) 2800-8599                  13 June 2012
  adrian.mowat@jpmorgan.com

                                   Figure 123: Performance of equity indices of China, Japan and Taiwan around equity market peak

                                   100
                                                                                                Life high = 100
Equity market peaks:
                                                             Japan - Nikkei
Japan – Nikkei 38915
        29 December 1989             90
                                                             Taiwan - TWSE
Taiwan – TWSE 12495
         10 February 1990            80
                                                             MSCI China
China -    A-shares 6395
                                     70
           16 October 2007
                                                             China A
           MSCI China 104.2
           30 October 2007           60
Correction one year post peak:
                                     50
Taiwan -80%

MSCI China -75%                      40
A-shares -70%
                                     30
Nikkei – 40%

                                     20
Taiwan and MSCI China, both
recovered 140% in less than one      10
year from their post bubble lows

                                      0
                                          -10y -9y -8y -7y -6y -5y -4y -3y -2y -1y 0y                             1y   2y   3y   4y   5y   6y   7y   8y   9y 10y
                                   Source: Bloomberg, 8 June 2012. Note:. Market rebased to 100 on peak of each equity market. For Japan it is 29 December 1989,
                                   Taiwan, 10 February 1990, SHASHR it is 16 October 2007 and MSCI China it is 30 October 2007




                                   Figure 124: Japan, Taiwan and China trailing PE around the peak in equity market

                                           100
Peak valuations (trailing PEs):                                     Japan

Japan 70                                    90
                                                                    Taiwan
Taiwan 85
                                            80
China (A-shares) 62                                                 China-A
China (MSCI) 32
                                            70
                                                                    MSCI China
A-shares trailing PE declined
from 62 to 9 one year.                      60


                                            50
Taiwan and Japanese re-rated
from their lows unlike China.
China is near its low post the              40
bubble. Taiwan and Japan re-
rated by more than 125% from                30
their trough valuations in four
and half years.
                                            20


                                            10


                                            0
                                                 -10y -9y   -8y   -7y   -6y   -5y   -4y   -3y    -2y   -1y   0y    +1y +2y +3y +4y +5y +6y +7y +8y +9y +10y

                                   Source: CEIC, Tosho stock exchange, Taiwan Economic Journal. For China, SHASHR Index is used. Note: Valuations are centered
                                   around peak in equity markets. For Japan: December 1989, Taiwan, February 1990, China, October 2007



  90
 Adrian Mowat                       Global Emerging Markets Equity Research
 (852) 2800-8599                    13 June 2012
 adrian.mowat@jpmorgan.com

                                    Figure 125: Loans to GDP for China, Japan and Taiwan around equity market peak
                                                                    Japan            Taiwan            China
                                            160

The loan to GDP ratio of Taiwan
increased steadily for next five
years from 100% to 150%. A                  140
possible explanation for this is
that Taiwanese business funding
investment in China.
                                            120

Japan’s loans to GDP ratio
decreased steadily post bubble.
                                            100


China’s loans to GDP ratio is
23% higher than Japan’s post
bubble.                                      80




                                             60




                                             40
                                                  -10y -9y   -8y   -7y   -6y   -5y   -4y   -3y   -2y     -1y   0y   +1y +2y +3y +4y +5y +6y +7y +8y +9y +10y

                                    Source: CEIC, Bank of Japan, Central Bank of China. The GDP numbers for every month are calendar weighted using GDP of the two
                                    consecutive years. Note: Ratios are centered on peak in equity markets. For Japan: December 1989, Taiwan, February 1990, China,
                                    October 2007


                                    Figure 126: Market cap to GDP around equity market bubble

                                      160                                                                                  Japan        Taiwan            China
 China’s market cap to GDP at
 the time of its bubble was 140%      140
 compared to Japan’s and
 Taiwan’s 150%.
                                      120


                                      100


                                       80
 The 2011 market cap to GDP of
 53% is the lowest amongst the
 three countries. The market cap
                                       60
 to GDP ratio of Taiwan and
 Japan, four years after the peak
                                       40
 were 84% and 67% respectively.

                                       20


                                        0
                                         -10y -9y -8y -7y -6y -5y -4y -3y -2y -1y 0y 1y 2y 3y 4y 5y 6y 7y 8y                                           9y 10y
                                    Source: CEIC, Tokyo Stock Exchange, Taiwan economic journal..Note:. Ratios centered on peak of each equity market. Japan and
                                    Taiwan it is 1989 and China it is 2007. China market cap includes A-shares and MSCI China




                                                                                                                                                                   91
   Adrian Mowat                        Global Emerging Markets Equity Research
   (852) 2800-8599                     13 June 2012
   adrian.mowat@jpmorgan.com

                                       Figure 127: Current account surplus as a % of GDP for China, Japan and Taiwan

                                         22.0
                                                                                                                                   Japan             Taiwan           China
 Taiwan and Japan both ran high
 current account surpluses which
 started to decline three years
 before the market peaked                17.0


 The current account surplus of
 China in 2011 is similar to that of
 Taiwan and Japan after their            12.0
 respective market peaks.



 The current account surplus or
 excess savings can contribute to         7.0
 a bubble when there are capital
 controls and limited
 opportunities for savers. This
 was particularly true for Taiwan
 and China                                2.0




                                         -3.0
                                             -10y -9y -8y -7y -6y -5y -4y -3y -2y -1y 0y 1y 2y 3y 4y 5y 6y 7y 8y 9y 10y

                                       Source: J.P. Morgan Economics. Note:. Ratios centered on peak of each equity market. Japan and Taiwan it is 1989 and China it is
                                       2007.


                                       Figure 128: Growth in working age population (% oya)

                                                                   Japan            China          Taiwan
                                                  3
Demographics is the main
reason China’s growth will slow.
Note the rapid deceleration in                  2.5
the growth of the working age
population.
                                                  2



                                                1.5




The post bubble demographics                      1
of China and Japan are very
similar. But the per capita GDP
of Japan in 1990 was eight times                0.5
that of China in today’s dollars.

                                                  0



                                                -0.5
                                                       -10y -9y   -8y   -7y   -6y    -5y    -4y   -3y   -2y   -1y   0y   1y   2y     3y    4y   5y    6y   7y   8y   9y   10y


                                       Source: J PRC NBS, Ministry of Education PRC, US Census, J.P. Morgan calculation. Note:. Growth Centered on peak of each equity
                                       market. Japan and Taiwan it is 1989 and China it is 2007.



   92
 Adrian Mowat                       Global Emerging Markets Equity Research
 (852) 2800-8599                    13 June 2012
 adrian.mowat@jpmorgan.com

                                    Figure 129: Real GDP growth around the equity bubble (%oya)

                                     16               Japan             Taiwan              China


GDP growth for Japan peaked          14
three years before equity market
peaked. For China and Taiwan,
GDP growth peaked a quarter          12
earlier.
                                     10


                                      8


                                      6
Japan had the steepest decline
in GDP growth. It had a               4
recession three years post
bubble (second oil shock).
China's growth of last quarter is     2
similar to Taiwan’s post bubble.

                                      0


                                      -2


                                      -4
                                           -10y -9y -8y -7y -6y -5y -4y -3y -2y -1y 0y +1y +2y +3y +4y +5y +6y +7y +8y +9y +10y

                                    Source: J.P. Morgan Economics. Note: Growth Centered on peak of each equity market. Japan it is Q4 1989, Taiwan, Q1 1990, China,
                                    Q4 2007.


                                    Figure 130: FX movements around the peak

Japanese Yen and Taiwanese          180
Dollar appreciated 50% in four
years prior to peak in equity
market bubble.                      160               Japan             Taiwan             China



                                    140

The rapid appreciation in the
Yen was atypical. The Plaza
                                    120
Accord was signed on 22
September 1985 when the
JPY/USD was 240.
                                    100



                                      80
China had pegged its currency
till 2004 and also during the
global financial crisis. The peak
                                      60
to trough appreciation in CNY is
only 31%. Similar ratios for
Japan and Taiwan are 240% and
65% respectively.                     40
                                           -10y -9y -8y -7y -6y -5y -4y -3y -2y -1y                  0y    1y    2y    3y    4y   5y    6y    7y    8y    9y 10y


                                    Source: , 8 June 2012. Note:. Currency rebased to 100 on peak of each equity market. For Japan it is 29 December 1989, Taiwan, 10
                                    February 1990.




                                                                                                                                                                   93
   Adrian Mowat                      Global Emerging Markets Equity Research
   (852) 2800-8599                   13 June 2012
   adrian.mowat@jpmorgan.com

                                     Figure 131: Nominal GDP per capita (USD)
                                       45000


 At the peak of the Japanese                                Japan           Taiwan            China
                                       40000
 equity market the JPY/USD was
 145. Then currency continued to
 appreciate peaking at JPY/USD         35000
 80. This explains the bulk of the
 US dollar increase in nominal
 GDP in Japan. See Figure 130 for      30000
 appreciation in FX.

                                       25000

 GDP Per capita when equity
 market peaked:
                                       20000
 Japan: US$24,000

 Taiwan: US$7500                       15000

 China: US$2600
                                       10000
 China per capita GDP is now
 US$6300
                                        5000



                                           0
                                               -10y -9y   -8y   -7y   -6y   -5y   -4y   -3y   -2y     -1y   0y   1y   2y   3y   4y   5y   6y   7y   8y    9y   10y


                                     Source: J.P. Morgan Economics. Note: GDP per capita centered on peak of each equity market. Japan and Taiwan is 1989, China
                                     2007.


                                     Figure 132: GDP per capita adjusted for inflation (USD)
                                       60000


                                                            Japan           Taiwan            China

                                       50000

Real GDP per capita for Japan
declined in the year the equity
market peaked.                         40000




                                       30000




                                       20000


No post bubble recession in
China and Taiwan
                                       10000




                                           0
                                               -10y -9y   -8y   -7y   -6y   -5y   -4y   -3y   -2y     -1y   0y   1y   2y   3y   4y   5y   6y   7y   8y    9y   10y


                                     Source: J P. Morgan Economics. Note: GDP per capita centered on peak of each equity market. Japan and Taiwan is 1989, China
                                     2007.




   94
   Adrian Mowat                      Global Emerging Markets Equity Research
   (852) 2800-8599                   13 June 2012
   adrian.mowat@jpmorgan.com

                                     Figure 133: Cement consumption per capita (Tonnes) around the equity market bubble
                                            1.60

Per capita cement consumption
is a real measure of construction                                       Japan                   Taiwan                  China
activity. China’s per capita
                                            1.40
consumption is unprecedented.



Cement consumption per capita
                                            1.20
in China is 17% higher than
Taiwan's peak cement
consumption.

                                            1.00

Cement consumption in Taiwan
peaked four years after its equity
market peaked. It fell by 3%oya,
in next two years and then                  0.80
declined 15%oya. Cement
consumption per capita in
Taiwan in 2010 was 40% of its
peak. It is quite possible that             0.60
China follows the same
trajectory.

                                            0.40
                                                   -10y -9y         -8y     -7y    -6y          -5y       -4y    -3y    -2y      -1y       0y       1y       2y      3y        4y     5y    6y       7y          8y      9y    10y


                                     Source: US Geological Survey. Note:. Cement consumption Centered on peak of each equity market. Japan and Taiwan it is 1989 and
                                     China it is 2007


                                     Figure 134: Cement consumption per capita (Tonnes)
                                                                                                                                                                                                 Russia (1991-2010)
                                       Cement consumption per capita (tonnes)
                                                                                                                                                                                                 Brazil (1985-2010)
                                     1.7
                                                                                                                                                                                                 India (1985-2010)
                                                                                                                                                                                                 China (1985-2010)
                                                                                                                 t
                                                                                            1997: per capita cemen consumption peaked in Korea
Per capita consumption of China                                           China 2012E
                                                                                                                                                                                                 US (1930-2010)

in 2011 was 11% above that of        1.5
                                                                           China 2011
                                                                                                                                                                                                 UK (1985-2010)
                                                                                                                                              sumption peaked in Taiwan
                                                                                                                    1993: per capita cement con                                                  Germany (1985-2010)
Korea's peak. GDP per capita of
                                                                                                                                                                                                 Japan (1985-2010)
China was only a third of Korea                                                                                                                                                                  Taiwan (1985-2010)
                                     1.3
during its peak cement                                                                                                                                                                           South Korea (1985-2010)
consumption.                                                                                                                                                                                     Mexico (1985-2010)
                                                                                                                                                                                                 Spain (1985-2010)
                                     1.1
                                                                                                                                    S. Korea 2010                                                Indonesia (1985-2010)
                                                                                                                                                           Peak for Spain in 2006
                                                                                                                                                                                                 Hong Kong (1990 - 2010)


                                     0.9
                                                                                                                                                      Spain 2010
                                                                                                                                                                                            Japan 2009




                                     0.7

Cement consumption in Spain                                         Russia 2010                                                                                                                    Germany 2010
peaked in 2006. In 2010, the                                                                                             Taiwan 2010
                                     0.5
cement consumption was only                          Mexico 2010

40% of that in 2006.
                                     0.3




                                                           Indonesia 2010                   Brazil 2010
                                     0.1                                                                                                                                                                                   US 2010
                                                    India 2010
                                                                                                                                                           UK 2010


                                     -0.1
                                            0                    6000                   12000                   18000                24000                  30000                   36000                42000                 48000
                                                                                                                                             GDP per capita (USD)




                                     Source: US Geological Survey. Note:. Cement consumption Centered on peak of each equity market. Japan and Taiwan it is 1989 and
                                     China it is 2007.



                                                                                                                                                                                                                                     95
Adrian Mowat                                   Global Emerging Markets Equity Research
(852) 2800-8599                                13 June 2012
adrian.mowat@jpmorgan.com




Appendix
Table 45: MSCI China constituents
Name                   BBG         Sectors         Ownership            Mkt Cap   3 Year Return (%)   Sharpe       5 Year Return (%)       Sharpe
                       Ticker                      Classification        $ Bn   Price Total CAGR       Ratio   Price     Total    CAGR      Ratio
Brilliance China       1114 HK     Cons. Disc.     Institutional          2.5    888     888    115     3.2     319       319        33      1.0
Haier Electronics      1169 HK     Cons. Disc.     Cross Shareholding     1.0    687     687     99     4.9     243       271        30      1.3
Great Wall Motor       2333 HK     Cons. Disc.     Family                 2.2    572     613     92     6.0     313       369        36      1.7
Dongyue Group          189 HK      Materials       Institutional          0.7    511     582     90     3.6     NA         NA       NA       NA
Dah Chong Hong         1828 HK     Cons. Disc.     Cross Shareholding     0.8    223     255     53     3.0     NA         NA       NA       NA
Skyworth Digital       751 HK      Cons. Disc.     Family                 0.9    191     223     48     2.2     172       237        27      1.2
China Ste.Con.Intl     3311 HK     Industrials     SOE                    1.3    172     190     43     3.2     251       299        32      1.7
Tencent Hldg           700 HK      IT              Institutional          30     156     158     37     3.8     612       623        49      3.8
China Resources        1193 HK     Utilities       Cross shareholding     1.3    143     149     36     3.1     220       233        27      0.9
Intime Dept.Store      1833 HK     Cons. Disc.     Family                 1.1    129     145     35     2.8     28         41         7      0.3
Want Want China        151 HK      CS              Family                 7.1    126     144     35     3.8     NA         NA         0     (0.4)
Weichai Power 'H'      2338 HK     Industrials     SOE                    1.7    126     130     32     1.8     115       124        17      0.8
Enn Energy Hldg        2688 HK     Utilities       Family                 2.8    124     129     32     3.0     228       245        28      2.0
Daphne Intl.Hldg       210 HK      Cons. Disc.     Institutional          1.0    123     133     33     3.3     55         67        11      0.4
Lenovo Group           992 HK      IT              Institutional          5.6    119     126     31     2.4     60         75        12      0.5
Hengan Intl.Gp.        1044 HK     CS              Family                 7.3    117     130     32     4.8     177       207        25      2.9
Inner Mongolia Yitai   900948 CH   Energy          Family                 3.0    114     125     31     2.7     292       331        34      1.8
Golden Eagle           3308 HK     Cons. Disc.     Family                 1.5    114     120     30     3.0     210       237        28      2.0
Kunlun Energy          135 HK      Energy          SOE                    5.3    113     120     30     2.6     214       249        28      1.8
Tsingtao Brewery       168 HK      Cons. Staples   SOE                    1.9    110     112     28     3.6     166       175        22      1.7
Zhuzhou Csr Times      3898 HK     Industrials     SOE                    1.2    101     107     27     2.1     67         79        12      0.7
Dongfeng Motor         489 HK      Cons. Disc.     SOE                    4.6     95     100     26     1.8     235       252        29      1.7
Geely Auto Hdg.        175 HK      Cons. Disc.     Family                 1.3     94     100     26     1.4     115       127        18      0.8
Bosideng Intl.Hldg     3998 HK     Cons. Disc.     Family                 0.7     93     149     36     2.3     NA         NA       NA       NA
Belle Intl Hdg.        1880 HK     Cons. Disc.     Family                 7.8     90     99      26     3.1     64         75        12      0.7
Wumart Stores 'H'      1025 HK     Cons. Staples   SOE                    1.1     87     92      24     2.1     148       166        22      1.5
China Gas Hldg         384 HK      Utilities       Institutional          1.4     80     84      22     1.3     45         50         8      0.3
China Southern         1055 HK     Industrials     SOE                    0.8     63     63      18     1.2     17         17         3     (0.0)
Shandong Weigao        1066 HK     Health Care     Family                 1.6     63     66      18     1.6     108       116        17      1.1
Minmetals Res          1208 HK     Materials       SOE                    0.7     56     56      16     0.9    (11)       (10)       (2)    (0.3)
Tingyi                 322 HK      Cons. Staples   Family                 4.8     56     63      18     2.1     114       132        18      1.7
Zhaojin Mining         1818 HK     Materials       SOE                    1.2     56     64      18     1.4     196       221        26      1.0
Picc Property &        2328 HK     Financials      SOE                    3.0     50     53      15     1.2     90         96        14      0.6
Csg Hldg 'B'           200012 CH   Materials       Institutional          0.5     48     67      19     1.4      2         23         4      0.1
Lee & Man Paper        2314 HK     Materials       Family                 0.8     45     56      16     0.8    (43)       (37)       (9)    (0.6)
China resources        291 HK      Cons. Staples   SOE                    3.6     44     52      15     1.5    (16)        (5)       (1)    (0.4)
Avichina Ind.&         2357 HK     Industrials     SOE                    0.7     43     44      13     0.8     41         41         7      0.2
Guangdong Inv.         270 HK      Utilities       SOE                    1.8     39     54      15     2.1     17         38         7      0.3
Jiangsu Express.       177 HK      Industrials     SOE                    1.1     38     51      15     1.8     (3)        18         3     (0.0)
Cnooc                  883 HK      Energy          SOE                    34      36     50      14     1.4     79        111        16      1.0
Csr 'H'                1766 HK     Industrials     SOE                    1.4     35     42      12     0.7     NA         NA       NA       NA
China Intl.Mar.Ctrs.   200039 CH   Industrials     SOE                    0.8     33     43      13     0.8    (46)       (39)       (9)    (1.0)
Air China 'H'          753 HK      Industrials     SOE                    1.2     29     31      10     0.7    (15)       (13)       (3)    (0.4)
Dongfang Electric      1072 HK     Industrials     SOE                    0.8     26     28      9      0.5      7         10         2     (0.1)
Anhui Conch            914 HK      Materials       SOE                    3.5     25     29      9      0.6     55         61        10      0.4
China Ptl.& Chm.       386 HK      Energy          SOE                    16      23     38      11     1.2    (15)        (0)       (0)    (0.3)
Hengdeli Hldg          3389 HK     Cons. Disc.     Family                 0.6     20     26      8      0.4     (5)         5         1     (0.2)
Beijing Enterprises    392 HK      Industrials     SOE                    2.9     18     22      7      0.7     70         85        13      1.0
Jiangxi Copper 'H'     358 HK      Materials       SOE                    3.0     17     20      6      0.3     29         36         6      0.2
China Shanshui         691 HK      Materials       Institutional          1.4     16     27      8      0.4     NA         NA       NA       NA
China Oilfield         2883 HK     Energy          SOE                    2.2     15     20      6      0.4     49         57         9      0.4
China Blue             3983 HK     Materials       SOE                    1.2     14     23      7      0.6     27         42         7      0.3
Yuexiu Property        123 HK      Financials      SOE                    1.2     13     20      6      0.3     (4)        10         2     (0.1)
Soho China             410 HK      Financials      Family                 1.4     12     30      9      0.9     NA         NA         0     (0.3)
Petrochina 'H'         857 HK      Energy          SOE                    28      11     24      7      0.7     (1)        19         4      0.0
China Nat.Bldg.'       3323 HK     Materials       SOE                    3.4     10     15      5      0.2     65         73        12      0.4
Yanzhou Coal           1171 HK     Energy          SOE                    3.1     10     14      5      0.2     15         27         5      0.1
Gome Elect..           493 HK      Cons. Disc.     Family                 1.4     8      11      4      0.1    (55)       (53)     (14)     (0.9)
China Mengniu          2319 HK     Cons. Staples   Family                 3.3     8      10      3      0.2    (18)       (16)       (3)    (0.5)
Poly (Hong Kong)       119 HK      Financials      Family                 1.0     6       9      3      0.1     (6)        (1)       (0)    (0.2)
Lonking Hldg           3339 HK     Industrials     Family                 0.5     2      14      5      0.2    (51)       (42)     (10)     (0.8)
China Con.Bank 'H'     939 HK      Financials      SOE                    49      0      10      3      0.2     19         39         7      0.3

96
Adrian Mowat                                              Global Emerging Markets Equity Research
(852) 2800-8599                                           13 June 2012
adrian.mowat@jpmorgan.com




Name                      BBG               Sectors       Ownership                Mkt Cap   3 Year Return (%)    Sharpe       5 Year Return (%)       Sharpe
                          Ticker                          Classification            $ Bn   Price Total CAGR        Ratio   Price     Total    CAGR      Ratio
Ping An Insurance         2318 HK           Financials    SOE                        13      0       2       1     (0.1)    28         33         6      0.2
Zte 'H'                   763 HK            IT            Institutional              1.2    (2)      1       0     (0.1)    24         30         5      0.1
China Os.Ld.& Inv.        688 HK            Financials    SOE                        8.9    (2)      4       1     (0.1)    57         68        11      0.7
China Mrch.Hdg.           144 HK            Industrials   SOE                        3.3    (2)      0       0     (0.1)   (31)       (26)       (6)    (0.7)
Alibaba.Com               1688 HK           IT            Institutional              2.2    (3)     (1)     (0)    (0.1)    NA         NA       NA       NA
Agile Property Hdg.       3383 HK           Financials    Family                     1.7    (4)      4       1     (0.0)     7         29         5      0.1
Huaneng Power             902 HK            Utilities     SOE                        2.2    (5)      6       2      0.0    (34)       (20)       (4)    (0.7)
China Mobile              941 HK            Telecom       SOE                        62     (5)      7       2      0.1      9         29         5      0.2
Cosco Pacific             1199 HK           Industrials   SOE                        2.1    (5)      6       2      0.0    (52)       (42)     (10)     (0.9)
China Agri-               606 HK            Cons. Staples SOE                        1.1    (6)     (2)     (1)    (0.2)   (15)        (9)       (2)    (0.5)
China Shenhua             1088 HK           Energy        SOE                        11     (6)      2       1     (0.1)     4         20         4      0.0
China Vanke 'B'           200002 CH         Financials    Institutional              1.7    (6)     (4)     (1)    (0.3)     7         11         2     (0.1)
China Unicom              762 HK            Telecom       SOE                        6.7    (7)     (3)     (1)    (0.3)    (5)         1         0     (0.3)
China Telecom 'H'         728 HK            Telecom       SOE                        6.3    (8)     (2)     (1)    (0.3)   (23)       (14)       (3)    (0.6)
Zhejiang Express.         576 HK            Industrials   SOE                        1.0    (9)      2       1     (0.1)   (32)       (15)       (3)    (0.7)
Country Garden            2007 HK           Financials    Family                     1.8   (10)     (5)     (2)    (0.3)   (50)       (45)     (11)     (0.9)
Shanghai Elec.            2727 HK           Industrials   SOE                        1.2   (10)     (5)     (2)    (0.4)     2         13         3     (0.1)
China Resources           1109 HK           Financials    Family                     4.0   (11)     (7)     (2)    (0.4)    53         62        10      0.5
China Merchants           3968 HK           Financials    SOE                        7.2   (13)     (7)     (2)    (0.4)    (6)         3         1     (0.2)
Nine Dragons              2689 HK           Materials     Family                     1.1   (14)    (10)     (3)    (0.3)   (69)       (67)     (20)     (1.2)
Beijing Cap.Intl.'        694 HK            Industrials   SOE                        1.2   (14)    (13)     (4)    (0.7)   (42)       (41)     (10)     (0.9)
ICBC                      1398 HK           Financials    SOE                        36    (14)     (3)     (1)    (0.4)     8         31         6      0.2
Kingboard                 148 HK            IT            Family                     1.3   (15)     (8)     (3)    (0.3)   (52)       (46)     (11)     (0.9)
Franshion Props           817 HK            Financials    SOE                        1.0   (16)    (14)     (5)    (0.6)    NA         NA       NA       NA
China Ship.Ctnr.          2866 HK           Industrials   SOE                        0.9   (18)    (18)     (6)    (0.4)   (37)       (35)       (8)    (0.6)
China Res.Power           836 HK            Utilities     SOE                        3.6   (19)    (15)     (5)    (0.9)    (5)         2         0     (0.3)
China Citic Bank 'H'      998 HK            Financials    SOE                        3.7   (19)    (12)     (4)    (0.6)   (32)       (23)       (5)    (0.8)
Shimao Property           813 HK            Financials    Family                     2.0   (20)    (13)     (4)    (0.5)   (32)       (23)       (5)    (0.5)
Sinopec Shai.             338 HK            Materials     SOE                        0.7   (21)    (17)     (6)    (0.7)   (58)       (54)     (14)     (1.3)
China Taiping             966 HK            Financials    SOE                        1.4   (22)    (22)     (8)    (1.0)     9          9         2     (0.1)
Fosun Intl                656 HK            Materials     Family                     0.9   (22)    (16)     (6)    (0.7)    NA         NA       NA       NA
Bank Of China 'H'         3988 HK           Financials    SOE                        27    (23)     (6)     (2)    (0.5)   (22)        (2)       (0)    (0.4)
China Comms.              552 HK            Telecom       SOE                        1.2   (24)    (18)     (7)    (1.1)   (25)       (17)       (4)    (0.7)
Parkson Retail            3368 HK           Cons. Disc.   Family                     1.4   (26)    (22)     (8)    (1.2)   (21)       (14)       (3)    (0.6)
Bank Of Comms.'H'         3328 HK           Financials    SOE                        4.6   (27)    (22)     (8)    (1.1)   (30)       (20)       (4)    (0.6)
Anta Sports               2020 HK           Cons. Disc.   Family                     0.7   (32)    (23)     (8)    (1.0)    NA         NA       NA       NA
China Yurun Food          1068 HK           Cons. Staples Family                     1.4   (32)    (28)    (11)    (1.0)   (10)        (3)       (1)    (0.3)
Gcl-Poly Energy           3800 HK           IT            Institutional              1.7   (32)    (30)    (11)    (0.8)    NA         NA       NA       NA
China Coal Energy         1898 HK           Energy        SOE                        3.6   (33)    (28)    (10)    (0.9)   (37)       (30)       (7)    (0.5)
Citic Pacific             267 HK            Industrials   SOE                        1.8   (34)    (28)    (10)    (0.9)   (68)       (63)     (18)     (1.1)
China Comms.              1800 HK           Industrials   SOE                        4.1   (34)    (29)    (11)    (1.1)   (40)       (34)       (8)    (0.7)
China Life                2628 HK           Financials    SOE                        18    (38)    (35)    (13)    (2.0)   (24)       (17)       (4)    (0.7)
Datang Intl.Pwr.          991 HK            Utilities     SOE                        1.1   (39)    (32)    (12)    (1.3)   (42)       (31)       (7)    (0.8)
Shui On Land              272 HK            Financials    Family                     1.0   (39)    (33)    (13)    (1.6)   (50)       (43)     (11)     (0.8)
Shougang Fushan           639 HK            Materials     Family                     0.9   (39)    (30)    (11)    (0.9)   (33)       (23)       (5)    (0.5)
Guangzhou R&F             2777 HK           Financials    Family                     1.3   (40)    (29)    (11)    (1.1)   (46)       (33)       (8)    (0.6)
Semiconductor             981 HK            IT            SOE                        0.6   (40)    (40)    (16)    (0.8)   (76)       (76)     (25)     (1.3)
Shanghai Indl.Hdg.        363 HK            Industrials   SOE                        1.5   (41)    (34)    (13)    (1.3)    (5)        13         3     (0.1)
China Everbright          165 HK            Financials    SOE                        1.2   (44)    (38)    (15)    (1.4)   (28)       (20)       (4)    (0.5)
Zijin Mining Group        2899 HK           Materials     SOE                        2.1   (45)    (40)    (16)    (1.4)   (10)         2         0     (0.2)
China Railway             1186 HK           Industrials   SOE                        1.6   (47)    (45)    (18)    (1.5)    NA         NA       NA       NA
China Molybdenum          3993 HK           Materials     SOE                        0.5   (52)    (48)    (19)    (1.5)   (76)       (72)     (22)     (1.5)
Byd 'H'                   1211 HK           Cons. Disc.   Family                     1.0   (52)    (52)    (22)    (1.4)    23         27         5      0.1
China Railway             390 HK            Industrials   SOE                        1.6   (53)    (51)    (21)    (1.7)    NA         NA       NA       NA
Huabao Intl.Hdg.          336 HK            Materials     Family                     0.8   (54)    (50)    (21)    (1.4)   (45)       (39)       (9)    (0.9)
Sino-Ocean Land           3377 HK           Financials    SOE                        1.2   (57)    (53)    (22)    (2.2)    NA         NA         0     (0.2)
CHALCO                    2600 HK           Materials     SOE                        1.7   (61)    (61)    (27)    (2.1)   (69)       (68)     (20)     (1.3)
China Cosco               1919 HK           Industrials   SOE                        1.3   (63)    (61)    (27)    (2.3)   (60)       (57)     (16)     (0.9)
China Shipping            1138 HK           Industrials   SOE                        0.7   (63)    (61)    (27)    (2.1)   (75)       (72)     (22)     (1.6)
China Zhongwang           1333 HK           Materials     Family                     0.6   (66)    (63)    (28)    (3.0)    NA         NA       NA       NA
Angang Steel 'H'          347 HK            Materials     SOE                        0.6   (67)    (66)    (30)    (2.4)   (69)       (67)     (20)     (1.3)
Sinofert Hldg             297 HK            Materials     SOE                        0.3   (74)    (74)    (36)    (2.6)   (75)       (75)     (24)     (1.8)
Renhe Commercial          1387 HK           Financials    Family                     0.5   (78)    (74)    (36)    (2.7)    NA         NA         0     (0.2)
China Dongxiang           3818 HK           Cons. Disc.   Family                     0.3   (82)    (79)    (41)    (3.7)    NA         NA       NA       NA
Source: MSCI, Bloomberg, IBES, 11 June 2012. Note: Sorted by 3 year price return




                                                                                                                                                           97
Adrian Mowat                                    Asia Pacific Equity Research
(852) 2800-8599                                 31 May 2013
adrian.mowat@jpmorgan.com




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J.P. Morgan Equity Research Ratings Distribution, as of March 30, 2013
                                                           Overweight    Neutral        Underweight
                                                           (buy)         (hold)         (sell)
 J.P. Morgan Global Equity Research Coverage               43%           44%            13%
    IB clients*                                            54%           47%            38%
 JPMS Equity Research Coverage                             42%           50%            9%
    IB clients*                                            74%           64%            57%
*Percentage of investment banking clients in each rating category.
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above.




98
Adrian Mowat                                      Asia Pacific Equity Research
(852) 2800-8599                                   31 May 2013
adrian.mowat@jpmorgan.com




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                                                                                                                                                            99
Adrian Mowat                                       Asia Pacific Equity Research
(852) 2800-8599                                    31 May 2013
adrian.mowat@jpmorgan.com




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redistributed without the written consent of J.P. Morgan. #$J&098$#*P




100
Adrian Mowat                                      Asia Pacific Equity Research
(852) 2800-8599                                   31 May 2013
adrian.mowat@jpmorgan.com




J.P. Morgan Hong Kong and China Equity Research Team
Sunil Garg                    Asia Pacific Head of Research          852 2800 8518   sunil.garg@jpmorgan.com
Adrian Mowat                  Market Strategy                        852 2800 8599   adrian.mowat@jpmorgan.com
Joanne Cheung                 HK Strategy                            852 2800 8596   joanne.cy.cheung@jpmorgan.com.
Lan Deng                      China Specialist                       852 2800 8520   lan.x.deng@jpmorgan.com
Joshua Klaczek                Banks                                  285 2800 8534   josh.klaczek@jpmorgan.com
Katherine Lei                 Banks                                  285 2800 8552   katherine.lei@jpmorgan.com
Helen Ye                      Banks/Insurance                        852 2800 8513   helen.zj.ye@jpmorgan.com
Joy Wu                        Banks                                  852 2800 8557   joy.wu@jpmorgan.com
Ebru Sener                    Consumer                               852 2800 8521   ebru.sener@jpmorgan.com
Shen Li                       Consumer                               852 2800 8523   shen.w.li@jpmorgan.com
Henry Tan                     Consumer                               852 2800 8559   henry.wd.tan@jpmorgan.com
Kenneth Fong                  Gaming & Lodging                       852 2800 8597   kenneth.kc.fong@jpmorgan.com
Daisy lu                      Gaming & Lodging                       852 2800 8593   daisy.y.lu@jpmorgan.com
Karen Li                      Infrastructure                         852 2800 8589   karen.yy.li@jpmorgan.com
Chapman Deng                  Infrastructure                         852 2800 8577   chapman.zw.deng@jpmorgan.com
MW Kim                        Insurance                              852 2800 8517   mw.kim@jpmorgan.com
Dick Wei                      Internet & New Media                   852 2800 8535   dick.x.wei@jpmorgan.com
Evan Zhou                     Internet & New Media                   852 2800 8505   evan.z.zhou@jpmorgan.com
Daniel Kang                   Metal & Mining                         852 2800 8570   daniel.kang@jpmorgan.com
Karen Li                      Metal & Mining                         852 2800 8561   waiyin.karen.li@jpmorgan.com
Scott Darling                 Oil & Gas                              852 2800 8578   scott.darling @jpmorgan.com
Sophie Tan                    Oil & Gas                              852 2800 8531   sophie.lm.tan@jpmorgan.com
Akhil Handa                   Oil & Gas                              852 2800 8563   akhil.x.handa@jpmorgan.com
Robert Smith                  Quantitative                           852 2800 8569   robert.z.smith@jpmorgan.com
Chris Ma                      Quantitative                           852 2800 8530   christopher.x.ma@jpmorgan.com
Lucia Kwong                   Real Estate                            852 2800 8526   lucia.yk.kwong@jpmorgan.com
Amy Luk                       Real Estate                            852 2800 8524   amy.kp.luk@jpmorgan.com
Ryan Li                       Real Estate                            852 2800 8529   ryan.lh.li@jpmorgan.com
Leo Ng                        Real Estate                            852 2800 8522   leo.ng@jpmorgan.com
Leon HK Chik                  SMID Caps                              852 2800 8590   leon.hk.chik@jpmorgan.com
Andrew Hsu                    SMID Caps                              852 2800 8572   andrew.t.hsu@jpmorgan.com
Alvin Kwock                   Technology                             852 2800 8533   alvin.yl.kwock@jpmorgan.com
Gokul Hariharan               Technology                             852 2800 8564   gokul.hariharan@jpmorgan.com
Qin Zhang                     Technology                             852 2800 8532   qin.zhang@jpmorgan.com
Lucy Liu                      Telecoms                               852 2800 8566   lucy.y.liu@jpmorgan.com
Michelle Wei                  Telecoms                               852 2800 8562   michelle.z.wei@jpmorgan.com
Corrine Png                   Transportation                         65 6882 1514    corrine.ht.png@jpmorgan.com
Boris Kan                     Utilities                              852 2800 8573   boris.cw.kan@jpmorgan.com
Elaine Wu                     Utilities                              852 2800 8561   elaine.wu@jpmorgan.com
Lan Deng's role is limited to assisting gathering information in this report.




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