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International Equity Market Correlations by mercy2beans119

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									        International Equity Market
               Correlations
presented at Northfield Research Conference 4 December, 2000




                   Rosemary Macedo
                  Bailard, Biehl & Kaiser
            950 Tower Lane #1900, Foster City, CA 94404
                 rmacedo@bailard.com   650-483-7953
                                              2


Discussion Topics


• Is our ability to diversify international
  portfolios deteriorating?

• Does diversification disappear right
  when you need it most?

• Should the country approach be
  replaced with a sector approach?
                                                           3


          Why the Answers Matter

Stress-testing--assessment of effects of high volatility
on portfolio should include expected changes in the
correlation.

Choice of long-term or recent history to estimate
covariance.

Better assessment of risk and opportunity.

Optimal allocation of assets.

Hedging strategies.
                                                                    4


                             Data

Datastream indices:

Daily market returns ( Jan 1973 through Oct 2000, US$)
60 day cross-country correlations (           231 pairs of countries)


Weekly individual country sector returns
(9cty X 10sect, Jan 1990 - Oct 2000, E)
eg: French telecom, German telecom . . .
    French banks, German banks . . .

Weekly regional sector returns ( Jan 1973 through Oct 2000, E)
Weekly country returns ( Jan 1973 through Oct 2000, E)
                                                    5


     Deteriorating Diversification


Globalization--countries, companies and markets
becoming more and more alike.

Euroland--move to single currency, single market.

Cross border mergers and acquisitions.

Multiple listings, expanded trading hours.

Institutional portfolio manager herding.
                                -.1
                                                   0.0
                                                         .1
                                                              .2
                                                                   .3
                                                                        .4
                                                                             .5
                                                                                  .6
                                                                                       .7
                                                                                            .8
                                                                                                 .9
                                                                                                      1.0
                           730328
                           730912
                           740301
                           740816
                           750204
                           750722
                           760108
                           760624
                           761209
                           770526
                           771110
                           780501
                           781016
                           790404
                           790919
                           800307
                           800822
                           810210
                           810728
                           820112
                           820629
                           821214
                           830531
                           831115
                           840502
                           841017




Trailing 60days (yymmdd)
                           850405
                           850920
                           860311
                           860826
                           870212
                           870730
                           880118
                           880704
                           881219
                           890606
                           891121
                           900510
                           901025
                           910415
                           910930
                           920318
                           920902
                           930219
                           930806
                           940121
                           940708
                                                                                                        across country pairs: ρ(USA,UK),ρ(USA,Jpn),ρ(USA,Ger) . . .




                           941223
                           950612
                           951127
                                                                                                                                                                      Average Correlations With USA




                           960515
                           961030
                           970418
                           971003
                           980324
                           980908
                           990225
                           990812
                           000127
                                    Source: BB&K
                                                                                                                                                                                                      6




                           000713
                                0.0
                                                   .1
                                                        .2
                                                             .3
                                                                  .4
                                                                       .5
                                                                            .6
                                                                                 .7
                                                                                      .8
                                                                                           .9
                                                                                                1.0
                           730328
                           730912
                           740301
                           740816
                           750204
                           750722
                           760108
                           760624
                           761209
                           770526
                           771110
                           780501
                           781016
                           790404
                           790919
                           800307
                           800822
                           810210
                           810728
                           820112
                           820629
                           821214
                           830531
                           831115
                           840502
                           841017




Trailing 60days (yymmdd)
                           850405
                           850920
                           860311
                           860826
                           870212
                           870730
                           880118
                           880704
                           881219
                           890606
                           891121
                           900510
                           901025
                           910415
                           910930
                           920318
                           920902
                                                                                                      across country pairs: ρ(Fra,Ger),ρ(Fra,Ita),ρ(Ger,Ita) . . .




                           930219
                           930806
                           940121
                           940708
                           941223
                           950612
                           951127
                           960515
                           961030
                           970418
                           971003
                           980324
                                                                                                                                                                     Average Correlations Within Euroland




                           980908
                           990225
                           990812
                           000127
                                    Source: BB&K
                                                                                                                                                                                                            7




                           000713
                                0.0
                                                   .1
                                                        .2
                                                             .3
                                                                  .4
                                                                       .5
                                                                            .6
                                                                                 .7
                                                                                      .8
                                                                                           .9
                                                                                                1.0
                           730328
                           730912
                           740301
                           740816
                           750204
                           750722
                           760108
                           760624
                           761209
                           770526
                           771110
                           780501
                           781016
                           790404
                           790919
                           800307
                           800822
                           810210
                           810728
                           820112
                           820629
                           821214
                           830531
                           831115
                           840502
                           841017




Trailing 60days (yymmdd)
                           850405
                           850920
                           860311
                           860826
                                                                                                                                                            Rim




                           870212
                           870730
                           880118
                           880704
                           881219
                           890606
                           891121
                           900510
                           901025
                           910415
                           910930
                           920318
                           920902
                           930219
                           930806
                           940121
                           940708
                                                                                                      across country pairs: ρ(Jpn,HKg),ρ(Jpn,Sng),ρ(HKg,Sng) . . .




                           941223
                           950612
                           951127
                           960515
                           961030
                           970418
                                                                                                                                             Average Correlations Within Pacific




                           971003
                           980324
                           980908
                           990225
                           990812
                           000127
                                    Source: BB&K
                                                                                                                                                                                   8




                           000713
                                                               9


             Regional Comparison


                     73-81         82-91        92-10/00
                  avg     st dev avg    st dev avg    st dev
Euro-Other Eur     0.28   0.22   0.44   0.21   0.48   0.18
within Euroland    0.27   0.22   0.43   0.21   0.47   0.19
within Other Eur 0.21     0.22   0.43   0.21   0.45   0.16
within Pacific Rim 0.17   0.20   0.30   0.22   0.31   0.20
Pac Rim-Other Eur 0.13    0.18   0.27   0.19   0.22   0.16
Pac Rim-Euro       0.14   0.18   0.25   0.20   0.21   0.16
with USA          0.19    .21    0.23   0.21   0.28   0.18
                                                                                                                                                                  10


                                                                         Correlation Stability
Standard Deviation of 60day Correlations


                                                .3
                                            LESS
                                           STABLE                                                   ITA,POR



                                                                                                      ITA,FRA
                                                                                                  ITA,GER
                                                                                                ITA,NET
                                                                                                                UK,SWI
                                                                                                                         SPA,POR
                                                                                                                             FRA,UK    FRA,GER
                                                                                                                                        GER,AUT
                                                                                                                                                  FRA,SPA
                                                                         USA,DEN
                                                .2
                                                           USA,AUT

                                                         USA,POR
                                                                              USA,JPN                                                                       GER,SWI

                                                     CAN,POR                                                                                             GER,NET
                                                        CAN,ITA
                                                                                                USA,FRA         USA,NET
                                                            CAN,UK                                    USA,SWE
                                                                                                                                                  USA,CAN
                                                                  CAN,FRA
                                                                            NZE,BEL                                                   AUS,NZE
                                            MORE                                               NZE,NET
                                           STABLE
                                                                                           NZE,UK
                                                .1
                                                  0.0               .1                .2               .3         .4              .5                .6                .7
                                                        MORE                                                                                               LESS
                                                        DIVERSIFYING                                                                               DIVERSIFYING
                                                                                Average of 60day Correlations
                                                       11

            Phantom Diversification
             vanishes when most needed

Higher correlations when markets fall.

Higher correlations when markets are volatile.

Does this reflect a real change in the relationships
between asset returns?

How inconsistent is this with constant correlation
assumption? Normality assumption? Compare with
theoretical conditional correlations.

What about “contagion”?
                                                                                   12


                                Extreme Market Moves
                          0.7




                          0.6




                          0.5
Conditional Correlation



                                     bottom
                                     decile
                          0.4
                                     returns

                          0.3




                          0.2

                                                       top
                          0.1                          decile
                                                       returns
                           0
                                0    0.1   0.2   0.3      0.4    0.5   0.6   0.7


                                    Unconditional Correlation
                                                                                  13

Constant Correlation Mandates Higher
 Conditional Correlation in the Tails




                                        Var(x|A)
                           ρA = f(    ρ, Var(x)      )


                                         ρ
               ρA=
                          ρ2 + (1-ρ2) Var(x) / Var(x|A)
 Significant differences between the conditional correlations are caused by the
 choice of subsamples alone; they do not necessarily indicate any change in the
 parameters of the data generating process, merely the time-varying market
 volatility.
                                                                                                                                               Expected Increase                                      14


                                                                                                                                            Conditional Correlation vs.
                                                                                                                                                  Unconditional
Expected Increase (bivariate normal random variables)



                                                                                                                                 0.35
Conditional Correlation vs. Unconditional Correlation




                                                                                                                                 0.30
                                                        (effects would be more pronounced for distributions with fatter tails)




                                                                                                                                 0.25


                                                                                                                                                                                     Two-sided event
                                                                                                                                 0.20
                                                                                                                                                                                          probability


                                                                                                                                 0.15                                                                 5%
                                                                                                                                                                                                     10%
                                                                                                                                 0.10
                                                                                                                                                                                                     20%
                                                                                                                                                                                       top&bottom decile
                                                                                                                                                                                                     50%
                                                                                                                                 0.05                                                top&bottom quartile


                                                                                                                                 0.00                                                        Source: BB&K
                                                                                                                                        0   0.1   0.2       0.3   0.4   0.5    0.6   0.7       0.8          0.9

                                                                                                                                                        Unconditional Correlation
                                                                15


                   Observations

Expect correlations to increase significantly, especially for
unconditional correlations between 0.4-0.5, and
especially for more extreme conditions:
    .4 --> .5+ conditioned on top&bottom quartile returns
   .4 --> .6+ conditioned on top&bottom decile returns

Correlations do not increase uniformly. Optimal portfolios
based on the conditional variance-covariance matrix
therefore will differ from those based on the
unconditional.

Market returns exhibit significant excess kurtosis &
negative skewness--affects will be worse than shown on
previous slide.
                                                                                                     Average Correlations With USA                           16


                                                                                                             vs. Volatility
                            across country pairs: ρ(USA,UK),ρ(USA,Jpn),ρ(USA,Ger) . . .




                                                                                          1.0

                                                                                           .9

                                                                                           .8
Average 60day Correlation




                                                                                           .7

                                                                                           .6

                                                                                           .5

                                                                                           .4

                                                                                           .3

                                                                                           .2

                                                                                           .1

                                                                                          0.0

                                                                                          -.1
                                                                                                .3   .4   .5   .6   .7   .8   .9   1             2   3   4        5
                                                                                                                              60day Volatility
                                                                                                Average Correlations Within Euroland                       17


                                                                                                           vs. Volatility
                                                              1.0
                            across country pairs: ρ(Fra,Ger),ρ(Fra,Ita),ρ(Ger,Ita) . . .




                                                                                   .9

                                                                                   .8
Average 60day Correlation




                                                                                   .7

                                                                                   .6

                                                                                   .5

                                                                                   .4

                                                                                   .3

                                                                                   .2

                                                                                   .1

                                                              0.0
                                                                                           .3      .4   .5   .6   .7   .8   .9   1             2   3   4    5

                                                                                                                            60day Volatility
                                                                                                Average Correlations Within Pacific                       18

                                                                                                               Rim
                                                                                                          vs. Volatility
                                                              1.0
                            across country pairs: ρ(Fra,Ger),ρ(Fra,Ita),ρ(Ger,Ita) . . .




                                                                                 .9

                                                                                 .8
Average 60day Correlation




                                                                                 .7

                                                                                 .6

                                                                                 .5

                                                                                 .4

                                                                                 .3


                                                                                 .2

                                                                                 .1

                                                              0.0
                                                                                           .3     .4   .5   .6   .7   .8   .9   1             2   3   4        5

                                                                                                                           60day Volatility
                                                                                   19


               Worse in Euroland?

Does the steeper slope (correlation vs volatility) in
Euroland indicate some effect beyond what statistics
predicts?

Probably not. The unconditional
correlations within Euroland are
higher than for other regions,
closer to peak impact from               0   0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9


sampling effects.

Check by comparing actual increase in conditional
correlation for top quartile of volatility with expected.
(from Monte Carlo Simulation)
                                                                                                                       20


                                                                       Top Quartile of Volatility
Increase: Conditional Correlation vs. Unconditional




                                                      0.20



                                                      0.15



                                                      0.10



                                                      0.05                                                     Monte
                                                                                                               Carlo
                                                                                                               Simulation
                                                                                                               median
                                                      0.00
                                                                                                                   Within
                                                                                                                   Euroland

                                                      -0.05                                                        others




                                                      -0.10
                                                           0.0   0.1      0.2    0.3     0.4     0.5   0.6   0.7

                                                                         Unconditional Correlation
                                              21


               Summary


Very easy to make compelling, in some cases
alarming, pictures.

Especially post mortem.

Autopsy reveals statistics not pathology.
                                                           22


                   2 Aspirin


Use a conditional variance-covariance matrix:
• if downside risk control is paramount
• when stress-testing portfolios

Significant serial correlation in volatility: around 0.5
for larger markets, 0.3-0.4 for most other markets.
• ARCH, GARCH, SWARCH, M ARCH etc.  c
    prescribed by some researchers (see references).
                                                   23


         Sectors vs Countries


Many of the same arguments as for deteriorating
ability to diversify.

Premise: stocks more correlated with other
stocks in same sector in any market than they
are with other stocks in their own market but in
different sectors.

Self-fulfilling prophesy?
                                                  24


          Counterarguments

Structural differences among countries-- taxes,
government, regulation, labor, language,
accounting,

Asynchronous business cycles,

Asymmetric impact of single monetary policy,

Currency alone does not a single market make
(Hong Kong ),

Sell-side ploy.
                                                            25


            Countries vs. Sectors

Are correlations stronger:
• within the same sector across countries?
• within the same country across sectors?

I.E. is the German Financial sector more correlated with:
• French financials, Swiss Financials, Dutch financials
…
• or German Utilities, German Consumer Cyclicals …

Use a scatterplot to compare the average correlation for
each country--sector index with the indices for:
• other countries--same sector
• same country--other sectors
                                                                                                                                                                                                     26


                                                                                                                          Countries vs. Sectors
                                                Average correlation across sectors in same country


                                                                                                      .7
                                                                                                           1/90 - 10/00
                                                                                                                                                                                 IT
                                                                                                                                                                                 resources
                                                                                                      .6
                                                                                                                                                                                 basic industries
                                                                                                                                                                                 general industrials
                                                                                                              countries                                                          consumer cyclicals
                                                                                                                                                                                 consumer noncyclicals
ρ(GerFinl,GerUtil), ρ(GerFinl,GerConsCyc),...




                                                                                                      .5        more                                                             cyclical services
                                                                                                              important                                                          noncyclical services
                                                                                                      .4
                                                                                                                                                                                 financials
                                                                                                                                                                                 utilities

                                                                                                      .3                                                                       Austria
                                                                                                                                                                               Belgium
                                                                                                                                                                               France
                                                                                                      .2
                                                                                                                                                                               Germany
                                                                                                                                                                               Italy
                                                                                                                                          sectors
                                                                                                      .1                                                                       Netherlands
                                                                                                                                           more                                Spain
                                                                                                                                         important         Source: BB&K
                                                                                                                                                                               Finland
                                                                                                     0.0
                                                                                                        0.0       .1      .2       .3       .4        .5       .6         .7
                                                                                                                                                                               Ireland
                                                                                                     Average correlation across countries in same sector
                                                                                                     ρ(GerFinl,FraFinl), ρ(GerFinl,ItaFinl), ρ(GerFinl,NetFinl) ...
                                                                                                                                                                                                     27

                                                Average correlation across sectors in same country
                                                                                                                          Countries vs. Sectors
                                                                                                      .7
                                                                                                           1/98 - 10/00
                                                                                                                                                                                 IT
                                                                                                                                                                                 resources
                                                                                                      .6                                                                         basic industries
                                                                                                                                                                                 general industrials
                                                                                                           countries                                                             consumer cyclicals
                                                                                                      .5     more                                                                consumer noncyclicals
ρ(GerFinl,GerUtil), ρ(GerFinl,GerConsCyc),...




                                                                                                           important                                                             cyclical services
                                                                                                                                                                                 noncyclical services
                                                                                                      .4                                                                         financials
                                                                                                                                                                                 utilities

                                                                                                      .3
                                                                                                                                                                               Austria
                                                                                                                                                                               Belgium
                                                                                                      .2                                                                       France
                                                                                                                                                                               Germany
                                                                                                                                          sectors                              Italy
                                                                                                      .1                                                                       Netherlands
                                                                                                                                           more
                                                                                                                                                                               Spain
                                                                                                                                         important         Source: BB&K
                                                                                                     0.0                                                                       Finland
                                                                                                        0.0      .1       .2       .3       .4        .5        .6        .7   Ireland
                                                                                                     Average correlation across countries in same sector
                                                                                                     ρ(GerFinl,FraFinl), ρ(GerFinl,ItaFinl), ρ(GerFinl,NetFinl) ...
                                                         28


                  “Risk Map”
Specifically which indices are most/least alike?
Plot each series as a point (x,y) so that proximity on
the map corresponds to strength of correlation.

Effectively a least squares fit with
       ρAB = correlation of series A and B
       zAB = (xA-xB)2+(yA-yB)2


Code the points on the plot & look for clusters
      by color for country
      by shape for sector
                                                                                            29


                         “Risk Map” 1/90-10/00
       Proximity on plot indicates
2.0
       correlation                                                      IT
                                                                        resources
1.5
                                                                        basic industries
                                                                        general industrials
1.0                                                                     consumer cyclicals
                                                                        consumer noncyclicals
                                                                        cyclical services
 .5                                                                     noncyclical services
                                                                        financials
0.0                                                                     utilities


 -.5                                                                  Austria
                                                                      Belgium
-1.0
                                                                      France
                                                                      Germany
                                                                      Italy
-1.5
                                                                      Netherlands
                                                                      Spain
-2.0                                                                  Finland
                                                 Source: BB&K         Ireland
-2.5
    -2.0   -1.5   -1.0   -.5   0.0   .5   1.0   1.5   2.0       2.5
                                                                                             30


                         “Risk Map” 1/98-10/00
       Proximity on plot indicates
2.5
       correlation
                                                                         IT
2.0                                                                      resources
                                                                         basic industries
                                                                         general industrials
1.5                                                                      consumer cyclicals
                                                                         consumer noncyclicals
1.0                                                                      cyclical services
                                                                         noncyclical services
                                                                         financials
 .5                                                                      utilities

0.0                                                                    Austria
                                                                       Belgium
 -.5
                                                                       France
                                                                       Germany
                                                                       Italy
-1.0
                                                                       Netherlands
                                                                       Spain
-1.5                                                                   Finland
                                            Source: BB&K               Ireland
-2.0
    -2.5   -2.0   -1.5   -1.0   -.5   0.0      .5    1.0   1.5   2.0
                                                                                                   31


                                     Opportunity
     Ratio of weekly cross-sectional dispersion in European country indices
10
     to weekly cross-sectional dispersion in European sector indices.
 8
                                                  Country approach more favorable
6

4



2



 1
.8
.6

.4



.2                                                Sector approach more favorable
      Overall c70 i30
      pre ‘85 c57 i43)                                                                   Source: BB&K
.1
730112 750110 770107 790105 810102 821231 841228 861226 881223 901221 921218 941216 961213 981211
     740111 760109 780106 800104 820101 831230 851227 871225 891222 911220 931217 951215 971212 991210
                                                          32


                Observations

Evidence in the Countries vs. Sectors debate fluctuates
over time.

Last two years, the balance of opportunity (as well as
sentiment), has shifted to sectors.

Overall, countries have represented the greater
opportunity (70/30),

Even pre-1985 when countries were not as dominant.
(57/43)
                                                                                                           33


               References, Further Reading
“Pitfalls in Tests for Changes in Correlations,” Boyer, Brian H, Michael S Gibson and Mico Loretan,
Board of Governors of the Federal Reserve System International Finance Discussion Papers Number
597, December 1997.
•      how conditioning on events affects correlations (selection bias)

“Evaluating ‘Correlation Breakdowns’ During Periods of Market Volatility,” Loretan, Mico and William
B. English, Board of Governors of the Federal Reserve System International Finance Discussion
Papers Number 658, February 2000.
•     If “contagion” is defined as an elevation in correlations between asset returns,
      then contagion is a natural by-product of temporal variation in volatilities.

“Is the Correlation in International Equity Returns Constant: 1960-1990?” Longin, Francois, Bruno
Solnik, CEPR Financial Markets Paper, RePEc:cpr:ceprfm:0037, October 1993

“Covariance and Correlation in International Equity Returns: A Value-at-Risk Approach,” Campbell,
Rachel, Kees Koedijk, Paul Kaufman May 2000
•    fat tails in return distribution are better fit by student-t distribution than normal distribution.

“Correlation in International Equity and Currency Markets: A Risk Adjusted Perspective,” Sheedy,
Elizabeth, Centre for Studies in Money, Banking and Finance [CMBF] Paper No. 17, June 1997
•     accounting for volatility clustering effectively eliminates structure in return correlation
      GARCH-CC, BEKK, several other models evaluated
•     daily data significantly improve portfolio efficiency (Sharpe ratio), even when portfolio
      adjustments are made only monthly.
                                                                                                            34


                                                  ...
“Do World Markets Still Serve as a Hedge?” Erb, Claude B., Campbell R. Harvey, Tadas E. Viskanta,
Journal of Investing, Fall 1995 pp26-42
•    developed and emerging market stocks & bonds
•    correlations higher for extreme moves, especially negative moves
•    currency hedging increases correlation

“International Market Correlation and Volatility,” Solnik, Bruno, Cyril Boucrelle, Yann Le Fur. Financial
Analysts Journal, Sept/Oct 1996
•      r(US,XXX) monthly 1959-95 correlations increasing slightly
•      r(US,XXX) weekly 1982-95 correlations not increasing
•      correlations fluctuate widely over time
•      correlation increases during volatile markets

“European Equity Markets and the EMU,” Rouwenhorst, K Geert, Financial Analysts Journal,
May/June 1999 pp 57-64.
•    “no evidence supports the disappearance of differences between EMU countries’ equity returns.”

For very interesting work on emerging markets contagion tests, start with MIT Prof Kristin Forbes’
website & papers, with good links, also.
                                                      35


                          Conclusions

• Our ability to diversify international
  portfolios does not appear to be
  deteriorating.

• Correlations are inherently higher in
  extreme periods.
   – This is consistent with constant correlations.
   – Even so, worthwhile to diversify.


• Evidence for a permanent switch
  from countries- to sectors- focus is
  not compelling.

								
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