2012 international finance part 1.pdf

International Finance

Part 1 – Introduction

Global Asset Classes and their Characteristics

Dr. Peter Oertmann

[email protected]

2© 2012 Peter Oertmann

Agenda

• Prologue: The asset allocation process

• Brush up: Risk and return

• Market parameters of global asset classes

• Some facts on stock market volatilities and correlations


Agenda






Building blocks of an asset allocation process

Investor’s preferences

Portfolio

construction

Risks

Covariance

Matrix

Expected

returns

Selection of

asset classes

Global

investment

universe

Regulatory

restrictions

10%

15%

20%40%

5%

10%

Investor’s portfolio


Aspects along the process

• Investor’s preferences

– Return target

– Liability structure

– Investment philosophy (benchmark-oriented, absolute return, …)

– Risk budget / capability (reserves, …)

• Regulatory restrictions (for pension plans, insurance companies, …)

– Restrictions on asset classes

– Restrictions on investment products

– Restrictions on risk management

• Selection of asset classes

– Availability of investment opportunities (asset manager, funds, derivatives, …)

– Investment philosophy


Aspects along the process (cont.)

• Asset risks

– How to calculate the covariance matrix (data period, frequency, …)

• Expected asset returns

– Choice of an asset pricing approach

• Portfolio construction

– General structure (traditional, core-satellite, …)

– Choice of an optimization method (Markowitz, Black-Litterman, ...)


Overview – Part 1

Asset returns, volatilities, and correlations

Regulatory

restrictions

Portfolio

construction

Risks

Covariance

Matrix

Expected

returns

Selection of

asset classes

Investor’s

preferences

Content

• Brush-up: Return calculation

• Data for international markets

• Empirical facts


Overview – Part 2-4

IAPM, Multifactor Models, Return Forecasting, and Asset Pricing

Regulatory

restrictions

Portfolio

construction

Risks

Covariance

Matrix

Expected

returns

Selection of

asset classes

Investor’s

preferences

Content

• International parity relations

• Theoretical backgrounds

• Structures of IAPM

• Specification of multifactor models

• Application of multifactor models

• Forecasting returns

• Modeling of risk premiums

• Sentiment and asset returns

• Conditional asset pricing

• Market integration


Overview – Part 5

Global Asset Allocation

Regulatory

restrictions

Portfolio

construction

Risks

Covariance

Matrix

Expected

returns

Selection of

asset classes

Investor’s

preferences

Content

• Strategic asset allocation

• Global tactical asset allocation

• Managing capital market risks

• Overlay management


Overview – Part 6

Institutional Investing in the 2nd Decade

Regulatory

restrictions

Portfolio

construction

Risks

Covariance

Matrix

Expected

returns

Selection of

asset classes

Investor’s

preferences

Content

• Investing in a changing world

• BCG report: Trends in institutional

investing

• Structuring the risk-return space

• 1/N for asset allocation

• Commodities as an alternative asset class


Literature

• Zimmermann/Drobetz/Oertmann: Global Asset Allocation, Wiley Finance,

2002, ISBN: 978-0-471-26426-2

• Selected references to books and

journals are given in the lecture


Agenda






Brush-up:

Calculating returns

Time period

t-1 t

Simple return

Continuously compounded return

1t,i

1t,iitit

P

PPR

−

−−=

=

−1t,i

itit

P

PlnR

Example

Monthly returns

S&P 500 (USD) 2008-2010

-20,0%

-15,0%

-10,0%

-5,0%

0,0%

5,0%

10,0%

15,0%

20,0%

Jan

08

Mrz

08

Mai

08

Jul

08

Sep

08

Nov

08

Jan

09

Mrz

09

Mai

09

Jul

09

Sep

09

Nov

09

Jan

10

Mrz

10

Mai

10

Jul

10

Sep

10

Nov

10


Brush-up:

Measuring investment risk

Variance of return

• Measure of dispersion

• Mean squared deviation of

returns form the mean return

Volatility

• Square root of variance

∑ −⋅==σ=

T

1t

2iiti

2i )RR(

T

1)R(Var

∑ −⋅==σ=

T

1t

2iitii )RR(

T

1)R(Std

Example

Monthly returns

S&P 500 (USD) 2008-2010

-20,0%

-15,0%

-10,0%

-5,0%

0,0%

5,0%

10,0%

15,0%

20,0%

Jan

08

Mrz

08

Mai

08

Jul

08

Sep

08

Nov

08

Jan

09

Mrz

09

Mai

09

Jul

09

Sep

09

Nov

09

Jan

10

Mrz

10

Mai

10

Jul

10

Sep

10

Nov

10

Monthly volatility 6.6%


Brush-up:

Measuring investment risk (cont.)

Volatility from different perspectives

Transformation rules

• (daily volatility) × √(22 days)

= (monthly volatility)

• (monthly volatility) × √(12 months)

= (yearly volatility)

Volatility calculations

Yearly Monthly Daily

100.0% 28.9% 6.2%

80.0% 23.1% 4.9%

60.0% 17.3% 3.7%

50.0% 14.4% 3.1%

40.0% 11.5% 2.5%

30.0% 8.7% 1.8%

20.0% 5.8% 1.2%

15.0% 4.3% 0.9%

10.0% 2.9% 0.6%


Brush-up:

Calculating portfolio returns

Approach

• Weighting the returns of portfolio components (single assets)

• Using simple (!) returns, not continuous returns

Two asset case

Mean:

N (many) asset case

Mean:

t22t11pt RwRwR ⋅+⋅=

∑ ⋅==

N

1iitipt RwR

2211p RwRwR ⋅+⋅=

∑ ⋅==

N

1iiip RwR


Brush-up:

Measuring the risk of a portfolio

Starting point

• Simple weighting of the variances / volatilities of the portfolio components is not adequate

• Return covariances have to be taken into account

Portfolio variance

2 asset case

3 asset case

122122

22

21

21

2p ww2ww σ⋅⋅⋅+σ⋅+σ⋅=σ

233213311221

23

23

22

22

21

21

2p

ww2ww2ww2

www

σ⋅⋅⋅+σ⋅⋅⋅+σ⋅⋅⋅+

σ⋅+σ⋅+σ⋅=σ


Brush-up:

Measuring the risk of a portfolio (cont.)

General formula of portfolio variance

Matrix notation

‚Double-sum‘ notation

[ ]

assets two between covariance

variance asset

asset an of weight portfoliowwhere

w

w

w

wwwwV'w

ij

ii

3

2

1

333231

332221

131211

3212p

σ

σ

σσσ

σσσ

σσσ

==σ

MM

L

L

∑ ∑ σ⋅⋅=σ= =

N

1i

N

1jijji

2p ww


Brush-up:

Measuring the risk of a portfolio (cont.)

Crucial insights

• Portfolio risk is based on the variances of its components as well

as on the covariance between its components

• Covariances between the portfolio components contribute the largest

part to portfolio risk

Covariances dominate

Number of ...

Assets VAR‘s COV‘s

2 2 2

3 3 6

4 4 12

5 5 20

10 10 90

100 100 9900

1000 1000 999000

2500 2500 6247500


Agenda






Relative sizes of world stock markets

Data source: Elroy Dimson, Paul Marsh and Mike Staunton, Triumph of the Optimists, 2002; Credit Suisse AG, 2011; own calculations

end-1899 end-2010

UK 30,5% 8,1%

USA 19,3% 41,4%

France 14,3% 3,9%

Germany 6,9% 3,2%

Japan 4,0% 8,2%

Canada 1,8% 4,1%

Russia 3,9%

Belgium 3,8%

Austria-Hungary 3,5%

Netherlands 1,6%

Italy 1,6%

Australia 3,4%

Switzerland 3,0%

Spain 1,4%

Sweden 1,3%

Others 3,7% 16,8%

5,2%

5,1%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

UK USA France Germany Japan Canada

end-1899

end-2010


Sector weightings within US stock market

Data source: Elroy Dimson, Paul Marsh and Mike Staunton, Triumph of the Optimists, 2002

US Sectors

end-1899 end-2000

Railroads 62,8% 0,2%

Banks and Finance 6,7% 12,9%

Mining 0,0% 0,0%

Textiles 0,7% 0,2%

Iron, Coal, Steel 5,2% 0,3%

Breweries and Distillers 0,3% 0,4%

Utilities 4,8% 3,8%

Telegraph and Telephone 3,9% 5,6%

Insurance 0,0% 4,9%

Other Transport 3,7% 0,5%

Chemicals 0,5% 1,2%

Food Manufacturing 2,5% 1,2%

Retailers 0,1% 5,6%

Tobacco 4,0% 0,8%

Sectors that were small in 1900 4,8% 62,4%

Weight

0%

10%

20%

30%

40%

50%

60%

70%

Ra

ilro

ad

s

Ba

nks a

nd

Fin

an

ce

Min

ing

Te

xtile

s

Iro

n,

Co

al, S

tee

l

Bre

we

rie

s a

nd

Dis

tille

rs

Utilit

ies

Te

legra

ph

an

d

Te

lep

hon

e

Insu

ran

ce

Oth

er

Tra

nsp

ort

Che

mic

als

Fo

od

Ma

nu

factu

rin

g

Re

taile

rs

To

ba

cco

Se

cto

rs t

hat

we

re

sm

all

in 1

90

0

end-1899

end-2000


Returns and risk

of international stock and fixed income markets from 1900 to 2010

Equities Bonds Bills Equities Bonds Bills Equities Bonds Bills

USA New York Stock Exchange, est. 1792 6,3% 1,8% 1,0% 9,4% 4,8% 3,9% 20,3% 10,2% 4,7%

Canada Toronto Stock Exchange, est. 1861 5,9% 2,1% 1,6% 9,1% 5,2% 4,7% 17,2% 10,4% 4,9%

Belgium Brussels stock exchange, est. 1801 2,5% -0,1% -0,3% 8,0% 5,2% 5,0% 23,6% 12,0% 8,0%

Finland Helsinki Stock Exchange, est. 1912 5,4% -0,2% -0,5% 13,1% 7,1% 6,8% 30,3% 13,7% 11,9%

France Paris stock exchange dates back to 1724 3,1% -0,1% -2,8% 10,5% 7,1% 4,2% 23,5% 13.0% 9,6%

Germany German stock exchange dates back to 1685 3,1% -1,9% -2,4% 8,3% 2,8% 2,3% 32,2% 15,5% 13,2%

Ireland Stock exchanges in Dublin and Cork date back to 1793 3,8% 0,9% 0,7% 8,2% 5,2% 5,0% 23,2% 14,9% 6,7%

Italy Stock exchange in Milan dates back to 1808 2,0% -1,7% -3,6% 10,6% 6,7% 4,5% 29,0% 14,1% 11,5%

Netherlands Amsterdam stock exchange dates back to 1611 5,0% 1,4% 0,7% 8,0% 4,4% 3,6% 21,8% 9,4% 5,0%

Spain Madrid Stock Exchange, est. 1831 3,6% 1,3% 0,3% 9,6% 7,2% 6,2% 22,3% 11,8% 5,9%

Denmark Copenhagen Stock Exchange, est. 1808 5,1% 3,0% 2,3% 9,2% 7,1% 6,2% 20,9% 11,7% 6,0%

Norway Oslo Stock Exchange, est. 1819 4,2% 1,7% 1,2% 8,1% 5,5% 4,9% 27,4% 12,2% 7,2%

Sweden Stockholm Stock Exchange, est. 1863 6,3% 2,4% 1,9% 10,1% 6,1% 5,5% 22,9% 12,4% 6,8%

Switzerland Swiss stock markets date back to 1850 4,2% 2,1% 0,8% 6,6% 4,5% 3,1% 19,8% 9,3% 5,0%

UK Stock trading dates back to 1698 5,3% 1,4% 1,0% 9,5% 5,4% 5,0% 20,0% 13,7% 6,4%

Australia Australian Securities Exchange (ASX), est. 1861 7,4% 1,5% 0,7% 11,6% 5,4% 4,6% 18,2% 13,2% 5,4%

Japan Tokyo stock exchange, est. 1878 3,8% -1,1% -1,9% 11,1% 5,8% 5,0% 29,8% 20,1% 13,9%

New Zealand New Zealand Exchange dates back to 1870 5,8% 2,0% 1,7% 9,8% 5,8% 5,5% 19,7% 9,0% 4,7%

South Africa Johannesburg stock exchange (JSE), est. 1887 7,3% 1,8% 1,0% 12,6% 6,8% 6,0% 22,6% 10,4% 6,2%

World GDP-weighted indices, denominated in USD 5,5% 1,6% 1,0% 8,6% 4,7% 3,9% 17,7% 10,4% 4,7%

Asia-Pacific

Africa

North America

Europe (Eurozone)

Europa (Others)

Real return Nominal return Standard deviation

Data source: Elroy Dimson, Paul Marsh and Mike Staunton, Triumph of the Optimists, 2002; Credit Suisse AG, 2011; Wikipedia; own calculations


Real returns



-4%

-2%

0%

2%

4%

6%

8%

USA CAN BEL FIN FRA GER IRE ITA NET SPA DEN NOR SWE SWI UKI AUS JAP NZE SAF WRL

Equities Bonds Bills


Standard deviations



0%

5%

10%

15%

20%

25%

30%

35%

USA CAN BEL FIN FRA GER IRE ITA NET SPA DEN NOR SWE SWI UKI AUS JAP NZE SAF WRL

Equities Bonds Bills


Equity risk premiums of international stock markets

1900-2010 1961-2010 2001-2010

USA 4,4% 2,6% -3,9%

Canada 3,7% 1,7% -0,9%

Belgium 2,6% 1,0% -4,7%

Finland 5,6% 4,6% -7,3%

France 3,2% -0,9% -6,0%

Germany 5,4% -0,1% -4,3%

Ireland 2,9% 3,5% -6,2%

Italy 3,7% -1,9% -7,3%

Netherlands 3,5% 3,3% -7,1%

Spain 2,3% 3,4% 1,3%

Denmark 2,0% 1,2% 0,9%

Norway 2,5% 2,8% 3,1%

Sweden 3,8% 4,8% 0,3%

Switzerland 2,1% 2,1% -4,2%

UK 3,9% 3,4% -1,3%

Australia 5,9% 3,5% 2,7%

Japan 5,0% -1,4% -5,2%

New Zealand 3,8% 2,2% 1,1%

South Africa 5,5% 6,9% 5,8%

World 3,8% 1,2% -4,0%

Asia-Pacific

Africa

Equity risk premium vs. bonds

North America

Europe (Eurozone)

Europa (Others)

0,0%

1,0%

2,0%

3,0%

4,0%

5,0%

6,0%

7,0%

US

A

Ca

nad

a

Belg

ium

Fin

lan

d

Fra

nce

Ge

rmany

Ire

lan

d

Italy

Neth

erlands

Spain

Denm

ark

Norw

ay

Sw

eden

Sw

itze

rla

nd

UK

Au

str

alia

Japa

n

New

Zeala

nd

Sou

th A

fric

a

1900-2010



Stock-bond correlations

rolling over a window of 60 months for real returns

Inflation accelerating

Bonds = save haven

Bonds = save haven

Data source: Credit Suisse Global Investment Returns Yearbook 2011, Credit Suisse AG


Stock-bond correlations

over various time horizons for real returns

Data source: Credit Suisse Global Investment Returns Yearbook 2011, Credit Suisse AG (and Antti Ilmanen)


Correlation “heat map”

of international asset classes – 2001-2011

Asset Class 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

1 MSCI World ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

2 MSCI EMU ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

3 MSCI Switzerland ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

4 MSCI UK ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

5 MSCI USA ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

6 MSCI Japan ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

7 MSCI EM East Europe ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

8 MSCI EM Latin America ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

9 MSCI EM Asia ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

10 iboxx € Sovereigns ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

11 iboxx € Corporates ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

12 BarCap Inflation Linked Bond Index ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

13 JPM EMBI ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

14 ML Global High Yield BB-B Index ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

15 Global Convertibles ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

16 DJ UBS Commodities Index ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

17 CYD MarketNeutral+ Index ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

18 HFRI Fund of Fund Index ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

19 EPRA/NAREIT Global Real Estate Index ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

20 Macquarie Global Infrastructure Index ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

21 LPX Index ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

Source: Vescore


Correlation “heat map”

of international asset classes – various time periods

Source: Vescore

Asset Class 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

1 MSCI World ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

2 MSCI EMU ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

3 MSCI Switzerland ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

4 MSCI UK ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

5 MSCI USA ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

6 MSCI Japan ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

7 MSCI EM East Europe ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

8 MSCI EM Latin America ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

9 MSCI EM Asia ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

10 iboxx € Sovereigns ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

11 iboxx € Corporates ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

12 BarCap Inflation Linked Bond Index ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

13 JPM EMBI ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

14 ML Global High Yield BB-B Index ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

15 Global Convertibles ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

16 DJ UBS Commodities Index ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

17 CYD MarketNeutral+ Index ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

18 HFRI Fund of Fund Index ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

19 EPRA/NAREIT Global Real Estate Index ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

20 Macquarie Global Infrastructure Index ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

21 LPX Index ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

2001-2006

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##

2006-2011


Summary of facts

• Stock markets considerably changed since 1900

• International stock markets returned 2.5 to 7.4% on a yearly basis in real terms

over the period 1900 to 2010, the return of the “world market” was 5.5%

• The long-term equity risk premium is positive, the “world market” equity risk premium is 3.8% over the period 1900 to 2010

• Over the first decade of the 21st century (2000-2010) the equity risk premium was significantly negative for many stock markets

• The average long-term correlation between stock and bond markets is positive

with a coefficient of 0.24

• Bonds diversify stock portfolios, especially in times of an increased risk aversion;

but inflation shocks lead to a higher co-movement between stocks and bonds


Agenda






A study for 13 stock markets

Source: Global Asset Allocation, Chapter 3

Research questions

• Does stock market risk depend on market conditions?

• How do volatility and correlation interact?

• Is stock market risk related to economic conditions?


Descriptive statistics for the stock markets in the study



Correlations over the sample period



Up and down volatility



Correlation and volatility

Approach of Solnik, Boucrelle, and Le Fur (1996)

• Regression of 36-month moving correlation between two countries on both countries’ 36-month moving volatilities

• Using monthly innovations to correct for autocorrelation

t,ijt,it,jt,ij ubba +σ∆⋅+σ∆⋅+=ρ∆21



Correlation and volatility – U.S. vs. other markets



Correlation and volatility – Switzerland vs. other markets



Correlation and average volatility



Semi-correlations – “up-up” vs. “down-down”



Correlations during expansions and recessions



Empirical evidence

• Stock market volatility is higher when markets go down

• In periods of high volatility, stock markets become more correlated – and in periods of low volatility, they are less correlated

• Higher correlations are detected when equity market go down simultaneously, as well as when real economic activity is shrinking



Implications for investors

• Optimal portfolios are unstable because market parameters are time-varying

• Bad news lead to higher volatility than good news

• International diversification benefits seem to vanish in exactly those market

environments when they are most strongly needed

• Widely used portfolio risk measures such as VaR, or shortfall, are affected by asymmetric parameters



Literature

• Global Asset Allocation: Chapter 3

• Dimson, E., P. Marsh, and M. Staunton (2002): Triumph of the Optimists, Princeton University Press

• Dimson, E. et al. (2011): Credit Suisse Global Investment Returns, Credit Suisse AG

2012 international finance part 1.pdf

Documents

asset returns

asset risks

asset allocation commodities

asset classes restrictions

asset allocation process

alternative asset class11

peter oertmannoverview

peter oertmannaspects