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Credit Suisse Fair Value 2012
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31 May 2012
Fixed Income Research
http://www.credit-suisse.com/researchandanalytics
Equilibrium Exchange Rates
International FX Strategy
Research Analyst Credit Suisse Fair Value 2012
Baron Chan
In our 2012 Credit Suisse fair value update, we re-estimate our long-term
+44 20 7883 4188
baron.chan@credit-suisse.com equilibrium exchange rate model, extending the sample period from 1980-2006
to 1980-2010. We find that the inclusion of recent observations results in
meaningful impact on the results. The key conclusions of our 2012 updates are:
The valuation spectrum reveals interesting patterns related to regions and
currency features. Non-Japan Asia currencies are cheap to their fair values.
This is followed by EMEA and Latam currencies, and then G10 low-yielding
currencies, such as GBP, JPY and SEK. The high-yielding commodity-
related currencies as well as the Swiss franc appear very expensive
The US dollar is the cheapest among G10 currencies, and the current USD
undervaluation versus G10 currencies is close to the bottom of its historical
range. The US dollar appears to remain rich against a broader set of
currencies, thanks to its overvaluation against EM currencies.
Euro-dollar fair value is at $1.18. On a trade-weighted basis, the EUR is
close to fairly priced. Within the European context, the euro is now trading
cheap to its major trading partners.
We estimate fair value for USDJPY at 83.6, largely unchanged from last
year‟s estimate of 83.4. Our 2012 EURJPY fair value estimate is 98.6, up
marginally from 97.0 last year.
Commodity-related currencies are among the most expensive in our
framework. However, after adjusting for elevated commodity prices, we note
that the Canadian dollar is the most overvalued, followed by the Kiwi dollar.
Joining the “expensive” club, the Swiss franc is among the few currencies to
diverge by multiple standard deviations from fair value. Given the extreme
valuation in the CHF and the SNB‟s EURCHF floor firmly in place, we see
good value in being short the CHF versus the “cheap” G10 currencies.
We also extend our framework to cover a few more emerging market
currencies, such as the Chilean peso (CLP), Israeli shekel (ILS), Indian
rupee (INR), Malaysian ringgit (MYR), and Indonesian rupiah (IDR).
ANALYST CERTIFICATIONS AND IMPORTANT DISCLOSURES ARE IN THE DISCLOSURE APPENDIX. FOR OTHER
IMPORTANT DISCLOSURES, PLEASE REFER TO https://firesearchdisclosure.credit-suisse.com.
CREDIT SUISSE SECURITIES RESEARCH & ANALYTICS BEYOND INFORMATION®
Client-Driven Solutions, Insights, and Access
31 May 2012
The CSFV Model – 2012 Update
In our 2012 Credit Suisse fair value update, we re-estimate our long-term equilibrium
exchange rate model, extending the sample period from 1980-2006 to 1980-2010. We
find that the inclusion of recent observations results in meaningful impact on the model
parameters and regression results1. This is partly due to the sharp fluctuation in exchange
rates, as well as market and macroeconomic variables, recorded throughout the 2008-
2010 turbulence period.
We also extend our framework to cover a few more emerging market currencies, such as
the Chilean peso (CLP), Israeli shekel (ILS), Indian rupee (INR), Malaysian ringgit (MYR),
and Indonesian rupiah (IDR).
Exhibit 1 compares the 2012 fair values of most commonly traded pairs to our
previous 2011 fair value estimates. For details and a longer history of Credit Suisse
fair value estimates, please refer to Appendix II.
Exhibit 1: Summary of changes in Credit Suisse Fair Value estimates
vs USD vs EUR vs JPY Other crosses
2012 2011 2012 2011 2012 2011 2012 2011
EUR 1.18 1.16
JPY 83.7 83.4 98.7 97.0
GBP 1.47 1.56 0.80 0.75 123 130
G10
CHF 1.15 1.17 1.35 1.36 73 71
CAD 1.26 1.20 1.48 1.40 67 69
AUD 0.70 0.62 1.68 1.87 58.8 51.8 AUDNZD AUDNZD
NZD 0.57 0.49 2.08 2.37 47.5 41.0 1.24 1.26
SEK 7.06 6.73 8.32 7.82 11.9 12.4
NOK 6.91 7.51 8.14 8.74 12.1 11.1
CNY 3.60 3.26
INR 38.8
IDR 9376
KRW 788 829
MYR 2.38
Emerging Markets
SGD 0.96 1.00
TWD 19.4 20.5
THB 25.4 27.0
MXN 12.7 12.6
CLP 530
PLN 3.02 3.59 3.57 4.18
HUF 213 265 251 308
CZK 19.9 25.4 23.5 29.6
ILS 3.62
ZAR 8.37 8.07
By market conventions
Source: Credit Suisse
Glancing across the spectrum of deviations from fair value, Exhibit 2 reveals interesting
patterns related to regions and currency features. The findings are similar to what we
previously reported. From left to right, most non-Japan Asia currencies appear to be
cheap to their equilibrium exchange rates. This is followed by the EMEA and LATAM
currencies, which seem to be slightly underpriced to fairly priced. G10 low-yielding
1 For technical details of the 2012 model updates and recalibrations, please refer to Appendix I.
Equilibrium Exchange Rates 2
31 May 2012
currencies, such as GBP, JPY and SEK, are trading within one standard deviation band
rich versus the USD relative to their fair values. On the expensive side, the high-yielding
commodity-related currencies as well as the Swiss franc have further stretched their
valuations against the USD close to record levels.
Compared with last year‟s values, the cross-sectional dispersion of valuation
misalignments has declined somewhat. This is attributable to a combination of
fundamental reasons (exchange rate mean reversion), and technical reasons (re-
calibration of the model and re-alignment of the fixed effects, particularly in some
emerging market currencies).
Exhibit 2: Deviation from 2012 Credit Suisse fair value (against the USD)
80% NJA ccys Deviation from fair value, in % expensive
+ / - 1 stdev G10 QE low
60%
yielders
40%
20%
0%
-20%
-40% cheap EMEA AND G10 Commodity
LATAM ccys bloc and CHF
-60%
TWD
ILS
JPY
MYR
NOK
PLN
MXN
KRW
INR
IDR
EUR
CAD
NZD
AUD
USD
THB
SEK
CZK
ZAR
CLP
CNY
SGD
HUF
CHF
GBP
Source: Credit Suisse
Focusing on individual currencies and specific currency blocs, the main conclusions from
our fair value update are:
US Dollar
The US dollar is the cheapest among G10 currencies. Although the US dollar trade-
weighted index (TWI) against the major currencies has been trading in “cheap” territory
since 2004, we note that the current USD undervaluation versus G10 currencies is close
to the bottom of its historical range. The US dollar undervaluation ranges from 6.0%
versus the Japanese yen, to as much as 40% versus the Antipodean currencies. We note
that the cross-sectional distribution of deviations from fair value continues to mirror
the yield premia (i.e., carry) dimension, with the Swiss franc being the exception.
Exhibit 3 shows that the US dollar TWI (majors) is trading around 1.2 standard deviation
cheap to its implied fair value.
On a broader trade-weighted basis, the US dollar appears to be 1.1 standard
deviations rich to fair value (Exhibit 4), as the US dollar‟s overvaluation versus the
emerging market currencies, particularly the non-Japan Asia bloc, outweighed its
undervaluation against the major G10 currencies.
Equilibrium Exchange Rates 3
31 May 2012
Exhibit 3: The US dollar TWI (Majors) is trading 1.5 Exhibit 4: ... but the US dollar is fairly traded on a
std dev cheap … broad TWI basis
140 USD TWI "Majors" FV +/-1 StDev 140 140 USD TWI "Broad" FV +/-1 StDev 140
130 130 130 130
120 120
120 120
110 110
110 110 100 100
100 100 90 90
80 80
90 90
70 70
80 80
60 60
70 70 50 50
60 60 40 40
1984 1988 1992 1996 2000 2004 2008 2012
1984 1988 1992 1996 2000 2004 2008 2012
Source: Credit Suisse Source: Credit Suisse
Euro
We estimate the 2012 fair value for EURUSD at $1.18, slightly higher compared with last
year‟s estimate of 1.16. We note that technical reasons are behind the higher EURUSD
fair value, as our 2011 estimate has also been revised higher to 1.23. Fundamentally, our
model suggests that EURUSD fair value has continuously fallen since 2009.
At the current rate of 1.26, EURUSD is 7%, or 0.5 standard deviations, rich to its fair value.
We suspect that global central bank reserve diversification flows have been an important
factor supporting the euro and preventing it from a powerful reversion to fair value during
the height of the sovereign fiscal crisis.
On a trade-weighted basis, the EUR TWI has exhibited mean reversion over the past three
years, although it is almost fairly priced (Exhibit 5). Within the European context, the euro
is now trading cheap to its major partners. Exhibit 6 shows that EUR overvaluation against
an equally weighted basket of NOK, SEK, GBP and CHF has declined from 15%
overvalued in mid-2009 to 5% undervalued now. As such, we see more value in EURUSD
and EURJPY downside, rather than in the G10 European crosses, particularly if the euro
zone fiscal stress intensifies.
Exhibit 5: EUR TWI is close to fairly valued … Exhibit 6: ... but cheap vs. a basket of European currencies
20% EUR TWI Deviations from FV 15%
15% expensive Peaked at
+/-1StDev expensive 10% Mar 2009
10% 5%
5%
0%
0%
-5%
-5% cheap
-10%
-10%
-15% EUR_Euroean crosses deviations from FV
-15% (GBP, CHF, NOK and SEK, 25% each)
-20% cheap -20% +/-1StDev
1982 1987 1992 1997 2002 2007 2012 1982 1987 1992 1997 2002 2007 2012
Source: Credit Suisse Source: Credit Suisse
Equilibrium Exchange Rates 4
31 May 2012
Japanese yen
We estimate fair value for USDJPY at 83.6, essentially unchanged from last year‟s estimate
of 83.4. Our 2012 EURJPY fair value estimate is 98.6, up marginally from 97.0 last year.
The yen has substantially mean-reverted over the past few years amidst persistent risk
aversion and compression of G10 yield differentials, and is now close to its fair value.
Exhibit 7: USDJPY is trading close to its fair value … Exhibit 8: ... so is EURJPY
260 USDJPY FV 260 EURJPY FV
240 240
+1 StDev -1 StDev +1 StDev -1 StDev
210 210
200 200
160 160 160 160
110 110 120 120
60 60 80 80
1984 1988 1992 1996 2000 2004 2008 2012 1984 1988 1992 1996 2000 2004 2008 2012
Source: Credit Suisse Source: Credit Suisse
G10 commodity currencies (AUD, NZD, CAD and NOK)
Commodity-related currencies are among the most expensive in our framework, both
against the dollar and on a trade-weighted basis. In fact, four out of five currencies which
currently exceed one standard deviations rich to fair value are G10 commodity currencies.
We show that most of these currencies‟ misalignments can be explained by the still
elevated level of commodity prices. We employ a two-stage estimation to incorporate
commodity prices into our fair value framework 2 . Exhibit 9 compares the original fair
values and the commodity price adjusted fair values. After adjustment, we note that at 7%
the Canadian dollar is the most overvalued among the commodity currency bloc, followed
by the New Zealand dollar which is 5% overvalued.
We also use AUDUSD as an illustration below for scenario analysis. Exhibit 10 shows that
AUDUSD is almost fairly priced after adjusting for the commodity prices, and Exhibit 11
illustrates the AUDUSD commodity price adjusted fair value under different commodity
price scenarios. Similar analyses and charts for the other G10 commodity price currencies
can be found in Appendix II (USDCAD – Exhibits 26-28; AUDUSD – Exhibits 27-29;
NZDUSD – Exhibits 30-32; USDNOK – Exhibits 33-35).
Exhibit 9: Comparison between original fair values and commodity price
adjusted fair values
Original Deviation Commodity price Deviation
Spot fair value from FV adjusted fair value from FV
AUDUSD 0.98 0.70 39% 0.99 -1%
NZDUSD 0.75 0.57 32% 0.72 5%
USDCAD 1.02 1.25 22% 1.10 7%
USDNOK 5.98 6.91 13% 5.78 -3%
Source: Credit Suisse
2 For technical details about the two stage estimation, please refer to Appendix I.
Equilibrium Exchange Rates 5
31 May 2012
Exhibit 10: AUDUSD is close to fairly priced after Exhibit 11: AUDUSD commodity price augmented
adjusting for commodity prices FVs under different levels of commodity prices
Scenario Analysis
50% Residuals (orginal FV - AUDUSD)
40% Residuals (commodity price augmented FV) AUDUSD fair value 0.70
+ / - 1 stdev RBA commodity price index (real terms) Commodity price augmented FV
30%
Current lvl = 138 AUDUSD
20% 110.0 0.90
10% 120.0 0.93
130.0 0.97
0%
140.0 1.00
-10% 150.0 1.02
-20% 160.0 1.05
170.0 1.08
-30% 180.0 1.10
1982 1986 1990 1994 1998 2002 2006 2010
Source: Credit Suisse Source: Credit Suisse
Swiss franc
Joining the “expensive” club, the Swiss franc is among the few currencies which exceed 2
standard deviations from fair value. At the Swiss National Bank’s (SNB) official EURCHF
floor of 1.200 (with spot trading at 1.201), the Swiss franc is over two standard deviations
rich to its fair value of 1.35 against the euro. The Swiss franc overvaluation has also
reached a record level on a TWI basis. Exhibit 13 shows that this is the largest
overvaluation on record, substantially larger than the extreme levels seen in 1994/95, in
the aftermath of the ERM crisis. We think CHF overvaluation supports the SNB’s
concerns over deflationary risk and its FX policy stance. Even with EURCHF at the 1.20
floor, the CHF remains expensive and should weaken over time.
Given the extreme valuation in the CHF and with the SNB’s EURCHF floor firmly in place,
we see good value in being short the CHF versus the “cheap” G10 currencies such as the
USD and the JPY.
Exhibit 12: EURCHF is over 2 standard deviations Exhibit 13: ... the Swiss franc overvaluation has also
cheap to its fair value of 1.35 … reached a record level on a TWI basis
EURCHF FV 25%
+1 StDev -1 StDev
CHF TWI Deviations from FV expensive
2 2
20% +/-1StDev
1.8 1.8 15%
1.6 1.6 10%
5%
1.4 1.4
0%
1.2 1.2
-5%
cheap
1 1 -10%
1984 1988 1992 1996 2000 2004 2008 2012 1982 1987 1992 1997 2002 2007 2012
Source: Credit Suisse Source: Credit Suisse
Equilibrium Exchange Rates 6
31 May 2012
Appendix I The CSFV Model – 2012 Update
In our 2012 Credit Suisse fair value update, we have re-estimated our long-term
equilibrium exchange rate model, extending the sample period from 1980-2006 to 1980-
2010. We find that the inclusion of recent observations resulted in meaningful impacts on
the model parameters and regression results.
We have made two modifications to the existing model. First, we removed the net
investment income (NII) variable from the model, as it has lost statistical significance. We
acknowledge that the extreme volatility in the NII variable saw in 2008 and 2009 has
largely impaired the variable‟s usefulness in explaining FX price movement. In addition,
we note that trade balance, another external balance variable in the model, has lost some
explanatory power (although it remains significant) relative to other variables such as PPP,
yield and productivity.
Second, we used semi-truncated panel dataset, via dummy variables, to control for the
time effect of pre and post eurozone inception. Although explanatory variables in euro
zone members exhibited certain degree of fluctuation post 1999, the independent
variables are essentially brought in line with EURUSD price action. This mitigates the
problem of under-estimation bias induced by limited variation in the currency movement
for the euro zone members in our panel database.
Exhibit 14 depicts the new estimates for the long-run coefficients, comparing them with the
estimates obtained in the previous updates in 2004 and 2008. These coefficient estimates
represent the long-term elasticity of the nominal exchange rate with respect to each
variable.
Exhibit 14: Long-term coefficient estimates
Panel DOLS – Panel DOLS – Panel DOLS –
2012 Update 2008 Update 2004 Update
PPP -0.81 -0.78 -0.88
t-stat -14.45 -15.49 -15.49
p-value 0.00 0.00 0.00
Yield differential 4.60 3.64 4.21
t-stat 8.51 7.95 8.39
p-value 0.00 0.00 0.00
Relative productivity 0.77 0.50 0.59
t-stat 4.57 3.41 3.56
p-value 0.00 0.00 0.00
Trade Balance 0.69 0.85 1.08
t-stat 2.17 3.65 2.81
p-value 0.00 0.00 0.01
Net Investment Income - 1.43 1.59
t-stat - 2.15 1.87
p-value - 0.0 0.00
R-squared adjusted 0.996 0.996 0.996
Akaike Information Criterion -0.995 -0.980 -1.010
Schwartz Information Criterion -0.646 -0.633 -0.611
Source: Credit Suisse
Equilibrium Exchange Rates 7
31 May 2012
Long term coefficients: We note that the explanatory power of the PPP and yield
differential remain strong, and are highly significant. At the same time, the relative
productivity variable also gained explanatory power in explaining currency movement.
However, the usefulness of external balances in explaining FX has weakened substantially
– Although the coefficient on trade balance remains statistically significant, its magnitude
has been largely reduced. Overall, we think the inclusion of recent observations resulted
in meaningful impacts on the model parameters and regression results. This is partly due
to the sharp fluctuation in exchange rates, as well as market and macroeconomic
variables, recorded throughout the 2008-10 turbulence period. In addition, the recent
observations also feature new risk factors, such as sovereign credit and liquidity risk
premium, which have heavily influenced market variables and currency market price action.
Short term dynamic coefficients: The PDOLS estimation also generates a set of
powerful short-term dynamics, which captures the simultaneous, and potentially
endogenous, interaction between the nominal exchange rate and the different
macroeconomic variables, and helps address the issue of serial correlation in the residuals.
At the same time, they add some dynamics to our long-term fair value, enhancing the
usefulness of the fit of our estimates.
Country-specific intercepts: The model also estimates country-specific intercepts, which
effectively rebase each exchange rate, such that the fair value is on average equal to spot
over the sample period. The extension of the sample period has, therefore, affected the
fair value estimates, making the fair value more in line with the spot rate in the sample. In
most cases, this had a marginal impact. In a few cases, such as the case of Asian and
EMEA currencies, the impact was more pronounced.
Equilibrium Exchange Rates 8
31 May 2012
TECHNICAL NOTE I: A brief recap of the CSFV model
Our CSFV model is rooted in traditional purchasing power parity (PPP) theory, but is
augmented by several structural and cyclical factors, which help explain, both
theoretically and empirically, much of the observed deviation from basic PPP in the
floating exchange rate period. We employ a panel dynamic OLS (PDOLS) framework,
which allows us to obtain robust long-run estimates of our fair values with rich short-term
dynamics. In this way we focus on the “true” long-run determinant of exchange rates in
general, rather than simply describing the history of any single exchange rate, as a more
traditional country-by-country approach may do. The PDOLS estimator also helps to
address potential serial correlation in the residuals introduced by the presence of non-
stationary variables in our data set.
In the 2012 update, our panel data set consists of 21 OECD countries, with a sample
period of 30 years, starting in 1980. We estimate our long-term exchange rate
equilibrium values with the following equation:
sit i 1 ( pit pt* ) 2 ( Rit Rt* ) 3 ( gdppcit gdppct* )
[1]
4 ( BALit BAL* ) 5 ( NII it NII t* ) it
t
where s is USD per unit of home currency, p is Table 1: Long-Run Coefficients
the home price level as measured by GDP PANEL DOLS
deflator, R is the ten-year-bond yield, gdppc is PPP -0.81
real GDP per capita (a proxy for productivity), t-stat -14.45
BAL is the goods and services trade balance as p-value 0.00
percentage of GDP, and NII is net investment Yield differential 4.60
income as a percentage of GDP. t-stat 8.51
Lower cases indicate data are in logarithmic p-value 0.00
terms, and * indicates a „foreign‟ variable, which Relative productivity 0.77
in each case here is the US. t-stat 4.57
p-value 0.00
In Table 1 we display the estimated long-run Trade Balance 0.69
coefficients (representing the long-term elasticity t-stat 2.17
of the nominal exchange rate with respect to p-value 0.00
each variable). The estimated coefficients are
signed and sized in accordance with R-squared adjusted 0.996
expectations. Akaike I.C. -0.995
We highlight that, in practice, this reading Schwartz I.C. -0.646
provides only a long-run anchor, around which Source: Credit Suisse
we would expect the currency to drift
significantly. The direction and extent of such drift is viewed as being driven by more
idiosyncratic or exogenous factors, such as shocks to the terms of trade, capital flows, and
fiscal / monetary policies.
Equilibrium Exchange Rates 9
31 May 2012
nd
TECHNICAL NOTE II: 2 Stage - Apply CSFV to idiosyncratic modeling
Our CSFV model can be further extended to capture cross sectional idiosyncrasy, as
well as currency specific factors. For instance, we discussed in Credit Suisse Fair Value
2010 about how to incorporate commodity prices into our valuation framework. Although
our CSFV model indirectly captures the impact of commodity prices and changes in the
terms of trade via the trade balance variable, we note that deviations from fair values for
AUDUSD, NZDUSD, USDCAD and USDNOK currency pairs have co-varied tightly with
commodity prices over the past decades.
We suggested a two-stage approach to incorporate commodity prices into our fair value
framework with the following equations: This methodology allows us to integrate short
term market variables with high frequency data
into a medium / long term macro valuation Table 2: FX / commodity elasticity
model . nd 2 stage commodity price adjusted fair values
^
AUDUSD / RBA commodity
it i * Comdty it e it ...... Eq(2)
price index (in USD) 0.43
^ ^ ^ p-value 0.00
FV it i i * Comdty it ...... Eq(3) ^ R-squared 0.71
it i * Comdty it e it
^
NZDUSD / ANZ commodity
^ ^
price i * Comdty it
FV it iindex (in USD) 0.48
Where ε is residual series obtained from the p-value 0.00
original fair value model (equation (1)), Comdty R-squared 0.38
is the corresponding price of commodity USDCAD / WTI crude oil
baskets, denominated in USD term (in price (USD / barrel) -0.14
logarithm). p-value 0.00
R-squared 0.58
Table 2 illustrates the estimated elasticity of USDNOK / WTI crude oil
currency valuation with respect to various price (USD / barrel) -0.24
basket of commodity prices. Deviation from fair p-value 0.00
value and commodity prices are tested to be co- R-squared 0.63
Source: Credit Suisse
integrated over time, and that the regression
residuals yielded from eq (2) are stationary.
Finally, we note that similar methodology can be easily applied to capture other currency
specific factors, which are not directly modeling in our FV. A few examples are (1)
capital account flows drive emerging markets currencies; (2) reserve diversification flow
and credit risk proxy are important for the euro.
Equilibrium Exchange Rates 10
31 May 2012
Appendix II Fair Value Chart Pack – G10
US dollar
Exhibit 15: US dollar TWI (Majors) is trading close to 1.2 standard deviations cheap
Country % Weight
140 USD TWI "Majors" FV +/-1 StDev 140
Canada 30.7%
130 130
Euro area 35.7%
120 120 Japan 17.6%
110 110 UK 8.7%
Switzerland 2.9%
100 100
Sweden 2.0%
90 90 Australia 2.4%
80 80
70 70
60 60
1984 1988 1992 1996 2000 2004 2008 2012
Source: Credit Suisse, US Federal Reserve
Exhibit 16: However, the USD is close to fairly price on a broader measure
Country % Weight
140 USD TWI "Broad" FV +/-1 StDev 140
130 130 Canada 17.4%
120 120 Euro area 20.2%
110 110 Japan 10.0%
100 100 UK 4.9%
90 90 Switzerland 1.6%
80 80 Sweden 1.1%
70 70 Australia 1.4%
60 60 Mexico 11.1%
50 50 Ex-Japan Asia 32.3%
40 40 CE3 and S.Africa 0.0%
1984 1988 1992 1996 2000 2004 2008 2012
Source: Credit Suisse, US Federal Reserve
Equilibrium Exchange Rates 11
31 May 2012
Euro
Exhibit 17: EURUSD Fair Value
EURUSD FV 2012 CSFV 1.18
1.6 +1 StDev -1 StDev 1.6
1.5 1.5 + 1 st. dev. 1.35
1.4 1.4 - 1 st. dev. 1.03
1.3 1.3
1.2 1.2
1.1 1.1
1 1.0
0.9 0.9
0.8 0.8
0.7 0.7
1984 1988 1992 1996 2000 2004 2008 2012
Source: Credit Suisse
Exhibit 18: EUR TWI is still close to 2% expensive Exhibit 19: ...... but is now trading cheap relative to a
basket of European currencies
Dotted line represents intra-year peak in EUR TWI vs the European ccys.
20% EUR TWI Deviations from FV 15%
15% expensive Peaked at
+/-1StDev expensive 10% Mar 2009
10% 5%
5%
0%
0%
-5%
-5% cheap
-10%
-10%
-15% EUR_Euroean crosses deviations from FV
-15% (GBP, CHF, NOK and SEK, 25% each)
-20% cheap -20% +/-1StDev
1982 1987 1992 1997 2002 2007 2012 1982 1987 1992 1997 2002 2007 2012
Source: Credit Suisse Source: Credit Suisse
Equilibrium Exchange Rates 12
31 May 2012
Japanese yen
Exhibit 20: USDJPY Fair Value
260 260 2012 CSFV 83.7
USDJPY FV +1 StDev -1 StDev
+ 1 st. dev. 100.2
210 210 - 1 st. dev. 69.9
160 160
110 110
60 60
1984 1988 1992 1996 2000 2004 2008 2012
Source: Credit Suisse
Exhibit 21: EURJPY Fair Value
2012 CSFV 98.7
240 EURJPY FV +1 StDev -1 StDev 240
+ 1 st. dev. 119.7
- 1 st. dev. 81.3
200 200
160 160
120 120
80 80
1984 1988 1992 1996 2000 2004 2008 2012
Source: Credit Suisse
Equilibrium Exchange Rates 13
31 May 2012
Swiss franc
Exhibit 22: EURCHF Fair Value
EURCHF FV 2012 CSFV 1.35
2 +1 StDev -1 StDev 2
+ 1 st. dev. 1.41
- 1 st. dev. 1.30
1.8 1.8
1.6 1.6
1.4 1.4
1.2 1.2
1 1
1984 1988 1992 1996 2000 2004 2008 2012
Source: Credit Suisse
Exhibit 23: USDCHF Fair Value
3.0 3.0
2012 CSFV 1.15
USDCHF FV
+1 StDev -1 StDev
2.6 2.6 + 1 st. dev. 1.29
- 1 st. dev. 1.02
2.2 2.2
1.8 1.8
1.4 1.4
1.0 1.0
0.6 0.6
1984 1988 1992 1996 2000 2004 2008 2012
Source: Credit Suisse
Equilibrium Exchange Rates 14
31 May 2012
UK pound
Exhibit 24: GBPUSD Fair Value
GBPUSD FV 2012 CSFV 1.47
2.1 +1 StDev -1 StDev 2.1
2.0 2.0 + 1 st. dev. 1.61
1.9 1.9 - 1 st. dev. 1.33
1.8 1.8
1.7 1.7
1.6 1.6
1.5 1.5
1.4 1.4
1.3 1.3
1.2 1.2
1.1 1.1
1984 1988 1992 1996 2000 2004 2008 2012
Source: Credit Suisse
Exhibit 25: EURGBP Fair Value
1.00 EURGBP FV 1.00 2012 CSFV 0.80
+1 StDev -1 StDev
0.95 0.95 + 1 st. dev. 0.88
0.90 0.90 - 1 st. dev. 0.73
0.85 0.85
0.80 0.80
0.75 0.75
0.70 0.70
0.65 0.65
0.60 0.60
0.55 0.55
1984 1988 1992 1996 2000 2004 2008 2012
Source: Credit Suisse
Equilibrium Exchange Rates 15
31 May 2012
Canadian dollar
Exhibit 26: USDCAD Fair Value
2012 CSFV 1.26
USDCAD FV +1 StDev -1 StDev
1.6 1.6
+ 1 st. dev. 1.37
1.5 1.5 - 1 st. dev. 1.16
1.4 1.4
1.3 1.3
1.2 1.2
1.1 1.1
1 1
0.9 0.9
1984 1988 1992 1996 2000 2004 2008 2012
Source: Credit Suisse
Exhibit 27: USDCAD valuation less stretched after Exhibit 28: USDCAD commodity price augmented
accounted for oil prices FVs under different levels of crude oil prices
Scenario Analysis
20% Residuals (original FV framework)
Residuals (commodity price augmented FV)
USDCAD fair value 1.25
+ / - 1 stdev
10% WTI Crude Oil Prices (in real term) Commodity price augmented FV
Current lvl = 93 USDCAD
0% 70.0 1.14
80.0 1.12
90.0 1.10
-10%
100.0 1.09
110.0 1.07
-20%
120.0 1.06
130.0 1.04
-30% 140.0 1.04
1982 1986 1990 1994 1998 2002 2006 2010
Source: Credit Suisse Source: Credit Suisse
Equilibrium Exchange Rates 16
31 May 2012
Australian dollar
Exhibit 29: AUDUSD Fair Value
AUDUSD FV 2012 CSFV 0.70
1.1 1.1
+1 StDev -1 StDev
+ 1 st. dev. 0.80
1.0 1.0
- 1 st. dev. 0.62
0.9 0.9
0.8 0.8
0.7 0.7
0.6 0.6
0.5 0.5
0.4 0.4
1984 1988 1992 1996 2000 2004 2008 2012
Source: Credit Suisse
Exhibit 30: AUDUSD close to fair value after Exhibit 31: AUDUSD commodity price augmented
adjusting for commodity prices FVs under different levels of commodity prices
Scenario Analysis
50% Residuals (orginal FV - AUDUSD)
40% Residuals (commodity price augmented FV) AUDUSD fair value 0.70
+ / - 1 stdev RBA commodity price index (real term) Commodity price augmented FV
30%
Current lvl = 138.9 AUDUSD
20% 110.0 0.90
10% 120.0 0.93
130.0 0.97
0%
140.0 1.00
-10% 150.0 1.02
-20% 160.0 1.05
170.0 1.08
-30% 180.0 1.10
1982 1986 1990 1994 1998 2002 2006 2010
Source: Credit Suisse Source: Credit Suisse
Equilibrium Exchange Rates 17
31 May 2012
New Zealand dollar
Exhibit 32: NZDUSD Fair Value
NZDUSD FV 2012 CSFV 0.57
0.85 +1 StDev -1 StDev 0.85
+ 1 st. dev. 0.64
- 1 st. dev. 0.50
0.75 0.75
0.65 0.65
0.55 0.55
0.45 0.45
0.35 0.35
1984 1988 1992 1996 2000 2004 2008 2012
Source: Credit Suisse
Exhibit 33: NZDUSD is still over 6% rich after Exhibit 34: NZDUSD commodity price augmented
adjusted for commodity prices FVs under different levels of commodity prices
Scenario Analysis
50% Residuals (original FV framework)
Residuals (commodity price augmented FV)
40% NZDUSD fair value 0.57
+/- 1 stdev
ANZ Commodity Prices (nominal term) Commodity price augmented FV
30%
Current lvl = 196 NZDUSD
20% 160.0 0.65
10% 180.0 0.69
200.0 0.73
0%
220.0 0.76
-10% 240.0 0.79
-20% 260.0 0.82
280.0 0.85
-30%
300.0 0.88
1982 1986 1990 1994 1998 2002 2006 2010
Source: Credit Suisse Source: Credit Suisse
Equilibrium Exchange Rates 18
31 May 2012
Norwegian krone
Exhibit 35: EURNOK Fair Value
EURNOK FV 2012 CSFV 8.14
10 10
+1 StDev -1 StDev
+ 1 st. dev. 8.51
- 1 st. dev. 7.80
9 9
8 8
7 7
6 6
1997 1999 2001 2003 2005 2007 2009 2011
Source: Credit Suisse
Exhibit 36: USDNOK is close for fair value after Exhibit 37: USDNOK commodity price augmented
adjusted for oil prices FVs under different levels of commodity prices
Scenario Analysis
Residuals (orginal FV framework)
40% Residuals (comdty augmented FV)
+/- 1 Stdev USDNOK fair value 6.91
30% WTI Crude Oil Prices (in real term) Commodity price augmented FV
20% Current lvl = 93 USDNOK
70.0 6.19
10% 80.0 6.00
0% 90.0 5.83
100.0 5.69
-10%
110.0 5.55
-20% 120.0 5.42
130.0 5.31
-30%
140.0 5.20
1997 1999 2001 2003 2005 2007 2009 2011
Source: Credit Suisse Source: Credit Suisse
Equilibrium Exchange Rates 19
31 May 2012
Swedish krona
Exhibit 38: EURSEK Fair Value
EURSEK FV 2012 CSFV 8.32
12 12
+1 StDev -1 StDev
+ 1 st. dev. 8.91
11 11 - 1 st. dev. 7.78
10 10
9 9
8 8
7 7
1993 1996 1999 2002 2005 2008 2011
Source: Credit Suisse
Exhibit 39: USDSEK Fair Value
11 USDSEK FV 11 2012 CSFV 7.06
+1 StDev -1 StDev
10 10 + 1 st. dev. 7.87
- 1 st. dev. 6.32
9 9
8 8
7 7
6 6
5 5
1993 1996 1999 2002 2005 2008 2011
Source: Credit Suisse
Equilibrium Exchange Rates 20
31 May 2012
Appendix III Fair Value Charts – EM
Non-Japan Asia
Exhibit 40: USDCNY Fair Value
2012 CSFV 3.60
14 USDCNY FV 14
+1 StDev -1 StDev + 1 st. dev. 5.32
12 12
- 1 st. dev. 2.44
10 10
8 8
6 6
4 4
2 2
0 0
1990 1994 1998 2002 2006 2010
Source: Credit Suisse
Exhibit 41: USDINR Fair Value
USDINR FV 2012 CSFV 38.8
60 60
+1 StDev -1 StDev
+ 1 st. dev. 45.7
50 50 - 1 st. dev. 32.9
40 40
30 30
20 20
1992 1995 1998 2001 2004 2007 2010
Source: Credit Suisse
Equilibrium Exchange Rates 21
31 May 2012
Exhibit 42: USDIDR Fair Value
USDIDR FV 2012 CSFV 9376
16000 +1 StDev -1 StDev 16000
+ 1 st. dev. 13137
- 1 st. dev. 6692
12000 12000
8000 8000
4000 4000
0 0
1988 1992 1996 2000 2004 2008 2012
Source: Credit Suisse
Exhibit 43: USDKRW Fair Value
USDKRW FV 2012 CSFV 788
1900 1900
+1 StDev -1 StDev
+ 1 st. dev. 1020
1700 1700
- 1 st. dev. 609
1500 1500
1300 1300
1100 1100
900 900
700 700
500 500
1984 1988 1992 1996 2000 2004 2008 2012
Source: Credit Suisse
Exhibit 44: USDMYR Fair Value
USDMYR FV 2012 CSFV 2.38
6 6
+1 StDev -1 StDev
+ 1 st. dev. 2.87
5 5
- 1 st. dev. 1.98
4 4
3 3
2 2
1 1
1988 1992 1996 2000 2004 2008 2012
Source: Credit Suisse
Equilibrium Exchange Rates 22
31 May 2012
Exhibit 45: USDSGD Fair Value
2012 CSFV 0.96
3.0 USDSGD FV 3.0
+1 StDev -1 StDev
2.6 2.6 + 1 st. dev. 1.24
- 1 st. dev. 0.75
2.2 2.2
1.8 1.8
1.4 1.4
1.0 1.0
0.6 0.6
1984 1988 1992 1996 2000 2004 2008 2012
Source: Credit Suisse
Exhibit 46: USDTWD Fair Value
50 50 2012 CSFV 19.4
USDTWD FV
45 +1 StDev -1 StDev 45 + 1 st. dev. 25.7
40 40 - 1 st. dev. 14.7
35 35
30 30
3
25 25
20 20
15 15
10 10
1988 1992 1996 2000 2004 2008 2012
Source: Credit Suisse
Exhibit 47: USDTHB Fair Value
USDTHB FV 2012 CSFV 25.4
60 60
+1 StDev -1 StDev
+ 1 st. dev. 33.9
50 50 - 1 st. dev. 19.1
40 40
30 30
20 20
10 10
1984 1988 1992 1996 2000 2004 2008 2012
Source: Credit Suisse
Equilibrium Exchange Rates 23
31 May 2012
Latin America
Exhibit 48: USDMXN Fair Value
USDMXN FV 2012 CSFV 12.7
16 16
+1 StDev -1 StDev
+ 1 st. dev. 15.2
14 14
- 1 st. dev. 10.6
12 12
10 10
8 8
6 6
4 4
2 2
1992 1995 1998 2001 2004 2007 2010
Source: Credit Suisse
Exhibit 49: USDCLP Fair Value
USDCLP FV 2012 CSFV 530
1000 1000
+1 StDev -1 StDev
+ 1 st. dev. 634
900 900
- 1 st. dev. 444
800 800
700 700
600 600
500 500
400 400
300 300
1992 1995 1998 2001 2004 2007 2010
Source: Credit Suisse
Equilibrium Exchange Rates 24
31 May 2012
Europe, Middle East and Africa
Exhibit 50: USDZAR Fair Value
USDZAR FV 2012 CSFV 8.37
13 +1 StDev -1 StDev 13
+ 1 st. dev. 10.0
11 11 - 1 st. dev. 6.99
9 9
7 7
5 5
3 3
1 1
1984 1988 1992 1996 2000 2004 2008 2012
Source: Credit Suisse
Exhibit 51: USDILS Fair Value
USDILS FV 2012 CSFV 3.62
5.50 +1 StDev -1 StDev 5.50
+ 1 st. dev. 4.19
- 1 st. dev. 3.13
5.00 5.00
4.50 4.50
4.00 4.00
3.50 3.50
3.00 3.00
1999 2001 2003 2005 2007 2009 2011
Source: Credit Suisse
Equilibrium Exchange Rates 25
31 May 2012
Exhibit 52: EURHUF Fair Value
EURHUF FV 2012 CSFV 251
350 +1 StDev -1 StDev 350
+ 1 st. dev. 286
300 300
- 1 st. dev. 219
250 250
200 200
150 150
100 100
1993 1996 1999 2002 2005 2008 2011
Source: Credit Suisse
Exhibit 53: EURPLN Fair Value
EURPLN FV 2011 CSFV 3.56
5 +1 StDev -1 StDev 5
+ 1 st. dev. 3.95
4.5 4.5 - 1 st. dev. 3.22
4 4
3.5 3.5
3 3
2.5 2.5
1995 1997 1999 2001 2003 2005 2007 2009 2011
Source: Credit Suisse
Exhibit 54: EURCZK Fair Value
EURCZK FV 2012 CSFV 23.5
40 +1 StDev -1 StDev 40
+ 1 st. dev. 25.1
- 1 st. dev. 22.0
35 35
30 30
25 25
20 20
1995 1997 1999 2001 2003 2005 2007 2009 2011
Source: Credit Suisse
Equilibrium Exchange Rates 26
FX RESEARCH AND STRATEGY > GLOBAL
Peter von Maydell, Director Eric Miller, Managing Director
Global Head of FX Strategy Global Head of Fixed Income and Economic Research
+44 20 7888 9558 +1 212 538 6480
peter.vonmaydell@credit-suisse.com eric.miller.3@credit-suisse.com
LONDON One Cabot Square, London E14 4QJ, United Kingdom
Aditya Bagaria, Vice President Baron Chan, Vice President Anezka Christovova, Analyst
+44 20 7888 7428 +44 20 7883 4188 +44 20 7888 6635
aditya.bagaria@credit-suisse.com baron.chan@credit-suisse.com anezka.christovova@credit-suisse.com
TECHNICAL ANALYSIS
David Sneddon, Managing Director Steve Miley, Director
+44 20 7888 7173 +44 20 7888 7172
david.sneddon@credit-suisse.com steve.miley@credit-suisse.com
Pamela McCloskey, Vice President Cilline Bain, Associate
+44 20 7888 7175 +44 20 7888 7174
pamela.mccloskey@credit-suisse.com cilline.bain@credit-suisse.com
NORTH AMERICA Eleven Madison Avenue, New York, NY 10010
Daniel Katzive, Director Alvise Marino, Associate
+1 212 538 2163 +1 212 325 5911
daniel.katzive@credit-suisse.com alvise.marino@credit-suisse.com
TECHNICAL ANALYSIS
Christopher Hine, Vice President
+1 212 538 5727
christopher.hine@credit-suisse.com
SINGAPORE One Raffles Link, Singapore 039393
Puay Yeong Goh, Associate
+65 6212 4464
puayyeong.goh@credit-suisse.com
ASIA MACRO STRATEGY
Ray Farris, Managing Director Trang Thuy Le, Analyst
Chief Asia Strategist +65 6212 4260
+65 6212 3412 trangthuy.le@credit-suisse.com
ray.farris@credit-suisse.com
TOKYO Izumi Garden Tower, 1-6 Roppongi 1-Chome, Minato-ku, Tokyo 106-6024
Koji Fukaya, Director
Japan Chief Currency Strategist
+81 3 4550 7413
koji.fukaya@credit-suisse.com
Disclosure Appendix
Analyst Certification
I, Baron Chan, certify that (1) the views expressed in this report accurately reflect my personal views about all of the subject companies and securities and
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Emerging Markets Bond Recommendation Definitions
Buy: Indicates a recommended buy on our expectation that the issue will deliver a return higher than the risk-free rate.
Sell: Indicates a recommended sell on our expectation that the issue will deliver a return lower than the risk-free rate.
Corporate Bond Fundamental Recommendation Definitions
Buy: Indicates a recommended buy on our expectation that the issue will be a top performer in its sector.
Outperform: Indicates an above-average total return performer within its sector. Bonds in this category have stable or improving credit profiles and are
undervalued, or they may be weaker credits that, we believe, are cheap relative to the sector and are expected to outperform on a total-return basis. These
bonds may possess price risk in a volatile environment.
Market Perform: Indicates a bond that is expected to return average performance in its sector.
Underperform: Indicates a below-average total-return performer within its sector. Bonds in this category have weak or worsening credit trends, or they may
be stable credits that, we believe, are overvalued or rich relative to the sector.
Sell: Indicates a recommended sell on the expectation that the issue will be among the poor performers in its sector.
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