rational international investment

1

Rational International InvestmentRational International Investment

Campbell R. Harvey, Ph.D.,Professor,

Duke Universityhttp://www.duke.edu/~charvey

WHU Campus for Finance“Rationality of Stock Markets and Empirical Finance”

January 2003

2

The PlanThe Plan

• Returns, diversification and predictability• Long horizon vs. short horizon• Expected performance• Prospect theory or skewness preference?• Importance of GPRs• The stock markets play a role in the world economy

3

6.0%

7.0%

8.0%

9.0%

10.0%

11.0%

12.0%

13.0%

0% 5% 10% 15% 20% 25%

Volatility(May 1986 to June 2002)

Ret

urn

(May

198

6 to

Ju

ne

2002

)

One Year Treasury STRIP

Two Year STRIP

Five Year Treasury STRIP

Seven Year Treasury STRIP

Ten Year Treasury STRIP

Twenty Year Treasury STRIPThirty Year Treasury STRIP

MBS Credit

AggregateGovernment

Three Year Treasury STRIP

Wilshire Small Cap

Wilshire 5000Wilshire Large Cap

Wilshire Mid Cap

EAFE X-Japan

International Performance

The International Track RecordThe International Track Record

Source: Erb and Harvey (2002)

GermanyEAFE

4

-30

-20

-10

0

10

20

30

Australi

a

Austria

Belg

ium

Canad

a

Den

mar

k

Finlan

d

France

Ger

man

y

Hong K

ong

Irelan

d It

aly

Japan

Nether

lands

New

Zea

land

Norway

Portugal

Spain

Swed

en

Switzer

land UK US

World

World

ex-U

S

EAFE

Expansion geometric mean Recession geometric mean

Average Annual Returns During U.S. Business Cycle Phases

Returns and DiversificationReturns and Diversification

Data from MSCI

5


-30

-20

-10

0

10

20

30

Argen

tina

Bahrai

n

Brazil

Chile

China

Colombia

Czech

Rep

ublic

Egypt

Greece

Hungary

India

Indones

ia

Israe

l

Jord

an

Korea

Mala

ysia

Mex

ico

Moro

cco

Nigeri

a

Oman

Pakist

an

Peru

Philippin

es

Poland

Russia

Saudi A

rabia

Slovak

ia

South A

frica

Sri Lan

ka

Taiwan

Thailan

d

Turkey

Venez

uela

Zimbab

we

Composite

Expansion geometric mean Recession geometric mean

Average Returns During U.S. Business Cycle Phases

AnnualReturnU.S. $

Data from IFC

6


0

10

20

30

40

50

60

Australi

a

Austria

Belg

ium

Canad

a

Den

mar

k

Finlan

d

France

Ger

man

y

Hong K

ong

Irelan

d It

aly

Japan

Nether

lands

New

Zea

land

Norway

Portugal

Spain

Swed

en

Switzer

land

UK USW

orld

World

ex-U

S

EAFE

Expansion std.dev. Recession std.dev.

Average Annual Volatility During U.S. Business Cycle Phases

Data from MSCI

7


-0.2

0

0.2

0.4

0.6

0.8

1

Australi

a

Austria

Belg

ium

Canad

a

Den

mar

k

Finlan

d

France

Ger

man

y

Hong K

ong

Irelan

d It

aly

Japan

Nether

lands

New

Zea

land

Norway

Portugal

Spain

Swed

en

Switzer

land

UK USW

orld

World

ex-U

S

EAFE

Expansion correlation with US Recession correlation with US

Correlations During U.S. Business Cycle Phases

Data from MSCI

8


0

5

10

15

20

25

30

35

40

45

Australi

a

Austria

Belg

ium

Canad

a

Den

mar

k

Finlan

d

France

Ger

man

y

Hong K

ong

Irelan

d It

aly

Japan

Nether

lands

New

Zea

land

Norway

Portugal

Spain

Swed

en

Switzer

land

UK US

World

World

ex-U

S

EAFE

Expansion covariance with US Recession covariance with US

Covariances During U.S. Business Cycle Phases

Data from MSCI

9


-60

-40

-20

0

20

40

60

Australi

a

Austria

Belg

ium

Canad

a

Den

mar

k

Finlan

d

France

Ger

man

y

Hong K

ong

Irelan

d It

aly

Japan

Nether

lands

New

Zea

land

Norway

Portugal

Spain

Swed

en

Switzer

land

UK US

World

World

ex-U

S

EAFE

US+ geometric mean US- geometric mean

Average Returns During U.S. Up and Down Markets

Data from MSCI

10


-60

-40

-20

0

20

40

60

Argen

tina

Bahrai

n

Brazil

Chile

China

Colombia

Czech

Rep

ublic

Egypt

Greece

Hungary

India

Indones

ia

Israe

l

Jord

an

Korea

Mala

ysia

Mex

ico

Moro

cco

Nigeri

a

Oman

Pakist

an

Peru

Philippin

es

Poland

Russia

Saudi A

rabia

Slovak

ia

South A

frica

Sri Lan

ka

Taiwan

Thailan

d

Turkey

Venez

uela

Zimbab

we

Composite

US+ geometric mean US- geometric mean

Average Returns During U.S. Up and Down Markets

AnnualReturnU.S. $

Data from IFC

11

US Business Cycle is PredictableUS Business Cycle is Predictable

US Yield Curve Inverts Before Last Six US Recessions(5-year US Treasury bond - 3-month US Treasury bill)

-6

-4

-2

0

2

4

6

8 % Real annual GDP growth

Yield curve

RecessionCorrect 2 Recessions

Correct

RecessionCorrect Yield curve accurate

in recent forecast

RecessionCorrect

Annual GDP growthor Yield Curve

Data though 1/12/03

12


Evolution of Correlation with U.S.

0

0.2

0.4

0.6

0.8

1

19701972

19741976

19781980

19821984

19861988

19901992

19941996

19982000

2002

Corr(WorldXUS, US) Corr(IFC,US)

Data from IFC and MSCI

13


Source: Goetzmann, Li and Rouwenhorst (2002)

14


Source: Goetzmann, Li and Rouwenhorst (2002)

0

10

20

30

40

50

60

1860 1880 1900 1920 1940 1960 1980 2000

Nu

mb

er o

f C

ou

ntr

ies

Core Markets Total Available Markets

15

The Long HorizonThe Long Horizon

100 Years of Real Equity Returns

0

1

2

3

4

5

6

7

8

9

Australi

a

Belgiu

m

Canad

a

Denmark

France

German

Irelan

d Ita

ly

Japan

Netherl

ands

South A

frica

Spain

Sweden

UK

U.S.

World

World

X-U

S

Data from Dimson, Marsh and Stauton (2002)

16


100 Years of Real Equity Returns

-5

0

5

10

15

20

1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

U.S. equity World X-US equity


17


100 Years of Real Bond Returns

-2.5

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

2.5

3

Australi

a

Beligum

Canad

a

Denmark

France

German

Irelan

d Ita

ly

Japan

Netherl

ands

South A

frica

Spain

Sweden

UK

U.S.

World

World

X-U

S


18


100 Years of Real Bond Returns

-10

-5

0

5

10

1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

U.S. World X-US


19

What to ExpectWhat to Expect

Dividend Yields Correlated With Future Returns

0

1

2

3

4

5

6

7

8

Div

iden

d Y

ield

1900 Yield 2000 Yield


20


Price Earnings Ratios

-40

-30

-20

-10

0

10

20

30

40

50

PE

rat

io

Dec-99 Dec-02

Data from MSCI. Japan divided by 10.

21


Price to Trailing Peak Earnings vs 5 Year Average CPI(overlapping annual data)

Pric

e t

o T

raili

ng

Pe

ak

Ea

rnin

gs

Source: Bloomberg, Standard & Poor’s

0

5

10

15

20

25

30

35

-10.0% -5.0% 0.0% 5.0% 10.0% 15.0% 20.0%

.

1996-2001

5 yr Average CPI

(1920- August 2002)

Current environment:Inflation: 2.3%P/E: 24.7x January 2003

Source: Goldman Sachs (2002)

22


• Ten-year risk premium around 3.5% and stable whereas one-year risk premium quite variable

0

1

2

3

4

5

6

6-Jun-00 7-Sep-00 4-Dec-00 12-Mar-017-Jun-01 10-Sep-01 4-Dec-01 11-Mar-024-Jun-02 16-Sep-02 2-Dec-02

0

1

2

3

4

5

6

6-Jun-00 7-Sep-00 4-Dec-00 12-Mar-017-Jun-01 10-Sep-01 4-Dec-01 11-Mar-024-Jun-02 16-Sep-02 2-Dec-02

10-year premium 1-year premium

Source: Graham and Harvey (2003)

23


y = 0.794x + 0.0791

R2 = 0.167

-15.00%

-10.00%

-5.00%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

40.00%

-15.00% -10.00% -5.00% 0.00% 5.00% 10.00% 15.00% 20.00%

Rolling Five Year Long Term Bond Return(June 1932 to June 2002)

Rol

ling

Fiv

e Y

ear

S&

P 5

00 R

etu

rn

U.S. Equity and Bond Returns are Positively Correlated


24


World Real Equity and Real Bond Returns are Positively Correlated


y = 0.6783x + 4.815

R2 = 0.3984

-30

-20

-10

0

10

20

30

40

-40 -30 -20 -10 0 10 20

Ten Year Real Bond Return

Ten

Yea

r R

eal S

tock

Ret

urn

25


Inflation Negatively Related to Real US Bill Returns


y = -0.7078x + 0.0294

R2 = 0.5373

-20.0%

-15.0%

-10.0%

-5.0%

0.0%

5.0%

10.0%

15.0%

-15.0% -10.0% -5.0% 0.0% 5.0% 10.0% 15.0% 20.0%

Inflation

T-B

ill R

eal R

etu

rn

26


Inflation Negatively Related to Real US Intermediate Bond Returns


y = -0.9873x + 0.0545

R2 = 0.3639-20.0%

-15.0%

-10.0%

-5.0%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

-15.0% -10.0% -5.0% 0.0% 5.0% 10.0% 15.0% 20.0%

Inflation

Inte

rmed

iate

Bon

d R

eal R

etu

rn

27


Inflation Negatively Related to Real US Bond Returns


y = -1.3027x + 0.0664

R2 = 0.2767-30.0%

-20.0%

-10.0%

0.0%

10.0%

20.0%

30.0%

40.0%

-15.0% -10.0% -5.0% 0.0% 5.0% 10.0% 15.0% 20.0%

Inflation

Lon

g B

ond

Rea

l Ret

urn

28


Inflation Negatively Related to Real US Equity Returns


y = -1.1054x + 0.1299

R2 = 0.0546

-60.0%

-40.0%

-20.0%

0.0%

20.0%

40.0%

60.0%

-15.0% -10.0% -5.0% 0.0% 5.0% 10.0% 15.0% 20.0%

Inflation

S&

P R

eal R

etu

rn

29


Inflation Negatively Related to Real International Bill Returns


y = -0.9226x + 4.7819

R2 = 0.8021

-5

-4

-3

-2

-1

0

1

2

3

4

0 1 2 3 4 5 6 7 8 9 10

100 Year Inflation Rate

100

Yea

r R

eal B

ill R

etu

rn

30


Inflation Negatively Related to Real International Bill Returns


y = -0.6731x + 3.9725

R2 = 0.6097

-3

-2

-1

0

1

2

3

0 1 2 3 4 5 6 7 8 9 10


100

Yea

r R

eal B

ond

Ret

urn

31


Inflation Negatively Related to Real International Equity Returns


y = -0.6333x + 8.3176

R2 = 0.4935

0

1

2

3

4

5

6

7

8

0 1 2 3 4 5 6 7 8 9 10


100

Yea

r R

eal E

qu

ity

Ret

urn

32


Inflation Negatively Related to Real International Equity Returns


y = -0.9226x + 4.7819

R2 = 0.8021

y = -0.6731x + 3.9725

R2 = 0.6097

y = -0.6333x + 8.3176

R2 = 0.4935

-6

-4

-2

0

2

4

6

8

10

0 1 2 3 4 5 6 7 8 9 10


100

Yea

r R

eal R

etu

rn

Real Bill Real Bond Real Equity

33

Rethinking RiskRethinking Risk

• Traditional models maximize expected returns for some level of volatility

• Is volatility a complete measure of risk?

34


• Much interest in prospect theory, downside risk, asymmetric volatility, semi-variance, extreme value analysis, regime-switching, jump processes, ...

35


• In prospect theory (Kahneman and Tversky)– Investor risk averse in the case of gains, as a

small certain gain is preferred to a probable risky gain

– Investor risk seeking in the case of losses, as a probable risky loss is preferred to a small certain loss

• So investors do not evaluate outcomes based on true probabilities

36


• Loss aversion is a special case– Investor has a greater incremental utility

penalty for losses than for an equally large gain– Overall, investor looks risk averse

37


• But, perhaps we can think of these situations in terms of preference for higher moments

• Most asset allocation work operates in two dimensions: mean and variance -- but skew is important for investors.

• Examples:

38


1. The $1 lottery ticket. The expected value is $0.45 (hence a -55%) expected return.– Why is price so high? – Lottery delivers positive skew, people like

positive skew and are willing to pay a premium

39


2. High implied vol in out of the money OEX put options.– Why is price so high? – Option limits downside (reduces negative

skew).– Investors are willing to pay a premium for

assets that reduce negative skew– Is this loss aversion or skewness preference?

40


3. Some stocks that trade with seemingly “too high” P/E multiples– Why is price so high? – Enormous upside potential (some of which is

not well understood)– Investors are willing to pay a premium for

assets that produce positive skew– [Note: Expected returns could be small or

negative!]

41


0

5

10

15

Variance

- 2

- 1

0

1

2

Skewness

5

7.5

10

12.5

Expected Return

0

5

10

15

Variance

Source: Harvey and Siddique (2000)

42


-2

-1.5

-1

-0.5

0

0.5

1

Australi

a

Austria

Belg

ium

Canad

a

Den

mar

k

Finlan

d

France

Ger

man

y

Hong K

ong

Irelan

d It

aly

Japan

Nether

lands

New

Zea

land

Norway

Portugal

Spain

Swed

en

Switzer

land UK US

World

World

ex-U

S

EAFE

Average Skewness in Developed Markets

Data from MSCI

43


-2

-1.5

-1

-0.5

0

0.5

1

Argen

tina

Bahrai

n

Brazil

Chile

China

Colombia

Czech

Rep

ublicEgy

pt

Greece

Hunga

ry

India

Indo

nesia

Israe

l

Jord

an

Korea

Mala

ysia

Mex

ico

Mor

occo

Nigeria

Oman

Pakist

an

Peru

Philipp

ines

Poland

Russia

Saudi

Arabia

Slovak

ia

South

Africa

Sri Lan

ka

Taiw

an

Thaila

nd

Turke

y

Venez

uela

Zimba

bwe

Compo

site

Average Skewness in Emerging Markets

Data from IFC

44

-1

0

1

2

3

4

5

6

Australi

a

Austria

Belg

ium

Canad

a

Den

mar

k

Finlan

d

France

Ger

man

y

Hong K

ong

Irelan

d It

aly

Japan

Nether

lands

New

Zea

land

Norway

Portugal

Spain

Swed

en

Switzer

land UK US

World

World

ex-U

S

EAFE

Average Excess Kurtosis in Developed Markets


Data from MSCI

45

-1

0

1

2

3

4

5

6

Argen

tina

Bahrai

n

Brazil

Chile

China

Colombia

Czech

Rep

ublicEgy

pt

Greece

Hunga

ry

India

Indo

nesia

Israe

l

Jord

an

Korea

Mala

ysia

Mex

ico

Mor

occo

Nigeria

Oman

Pakist

an

Peru

Philipp

ines

Poland

Russia

Saudi

Arabia

Slovak

ia

South

Africa

Sri Lan

ka

Taiw

an

Thaila

nd

Turke

y

Venez

uela

Zimba

bwe

Compo

site

Average Excess Kurtosis in Emerging Markets


Data from IFC

46

Alternative VehiclesAlternative Vehicles

Alternate Asset Classes Often Involve Implicit or Explicit Options

-4-3-2-101234567

1 2 3 4 5

S&P 500Global Macro

Source: Agarwal and Naik (2002)

47



-8

-6

-4

-2

0

2

4

6

8

1 2 3 4 5

S&P 500Trend Followers


48



-4-3-2-101234567

1 2 3 4 5

S&P 500FI Arb


49



-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

1 2 3 4 5

Delta(BAA-10yTBond)x10FI Arb


50



Panel B: PRAM Returns, 1990 - 1998

Ris

k A

rb R

etu

rn -

Ris

k-f

ree

Rat

e

Market Return minus Risk-free Rate

-.2 -.16 -.12 -.08 -.04 0 .04 .08 .12 .16 .2

-.1

-.08

-.06

-.04

-.02

0

.02

.04

.06

.08

.1

9808

9008

9001

9009

9607

9703

9106

9403

9111

9411

9708

97109004

94069805

9304

98079203

9402920892069409

93119010

9007

961295109109

9606900692019702930791049309

98019306

93029205

9508

9405

9804

9404960394129210

9002

9209

96109301951292029204

9410

9602

9110

9712

9212

9310

9501

9312

9003

9604

9504

9108

9503

96059303

9012

96019103

950697119305

9407

96089505

9401

980695099502

91059507

93089207

9211

9704

9511

9408

970691079101

9803

9701

9609

9709

9811

9812

9809

9011

9611

970598029810

91029707

90059112

Source: Figure 5 from Mitchell & Pulvino (2000)

51



-8

-6

-4

-2

0

2

4

6

-15 -10 -5 0 5 10

Russell 3000 Index Returns

Eve

nt D

riven

Inde

x R

etur

ns

LOWESS fit


52


Skewness has potential to explain one of the unsolved anomalies in finance: the profitability of momentum trading

y = -5.3067x + 24.869

R2 = 0.5934

0

5

10

15

20

25

0 0.5 1 1.5 2 2.5 3

Skew

Mea

n

Momentum portfolios

53


•Harvey, Liechty, Liechty and Müller (2002) “Portfolio Selection with Higher Moments” provide a new approach to portfolio selection which accounts for:

Higher momentsEstimation errors in the inputs

54

The Evolution of World RiskThe Evolution of World Risk

• The U.S. has become much more risky– High sensitivity to some GPRs– Disagreement on strength of economy– Financial information less credible

55

The Evolution of World RiskThe Evolution of World Risk ICRG Political Risk

Data from PRS

60

65

70

75

80

85

90

95

100

Jan-

01

Feb-0

1

Mar

-01

Apr-0

1

May

-01

Jun-

01

Jul-0

1

Aug-0

1

Sep-0

1

Oct-01

Nov-0

1

Dec-0

1

Jan-

02

Feb-0

2

Mar

-02

Apr-0

2

May

-02

Jun-

02

Jul-0

2

Aug-0

2

Sep-0

2

Oct-02

Nov-0

2

Dec-0

2

Jan-

03

Equally-weighted world G-7xUS Switzerland United States

56


Data from PRS

60

65

70

75

80

85

90

95

100

Jan-

01

Feb-0

1

Mar

-01

Apr-0

1

May

-01

Jun-

01

Jul-0

1

Aug-0

1

Sep-0

1

Oct-01

Nov-0

1

Dec-0

1

Jan-

02

Feb-0

2

Mar

-02

Apr-0

2

May

-02

Jun-

02

Jul-0

2

Aug-0

2

Sep-0

2

Oct-02

Nov-0

2

Dec-0

2

Jan-

03

Equally-weighted world Japan Switzerland United States

57


Data from PRS

60

65

70

75

80

85

90

95

100

EW world Japan Germany Switzerland United States

58


Risk Ratings December 2002

Data from PRS

Luxembourg 94.5 Netherlands 88.5 Bahamas 84.5Finland 94.0 Singapore 88.5 Spain 83.0Ireland 92.5 Portugal 87.5 Hungary 82.5Switzerland 92.5 Australia 87.0 France 81.0Iceland 92.0 Belgium 87.0 Italy 81.0Sweden 91.5 Japan 87.0 Slovenia 81.0Denmark 91.0 United Kingdom 87.0 Brunei 80.5New Zealand 91.0 Malta 86.5 United States 80.0Austria 90.5 Canada 86.0 Bahrain 79.5Norway 90.0 Germany 86.0 Poland 79.5

59


Risk Ratings May 2001

Netherlands 96.5 Portugal 90.0 Chile 81.0Finland 95.0 Norway 90.0 Slovak Rep. 81.0Luxembourg 95.0 Singapore 89.5 Uruguay 81.0Denmark 93.5 Germany 88.0 Brunei 80.5Iceland 93.0 Japan 88.0 France 80.0Sweden 93.0 Australia 87.0 Qatar 80.0Switzerland 93.0 Belgium 87.0 U.A.E. 80.0United Kingdom 92.5 Malta 87.0 Hong Kong 79.5Canada 91.0 Bahamas 84.5 Poland 79.5Ireland 90.5 Costa Rica 83.5 Botswana 79.0New Zealand 90.5 Italy 83.0 Cyprus 79.0Austria 90.0 Spain 82.0 Czech Rep. 79.0United States 90.0 Slovenia 81.5 Greece 79.0

Data from PRS

60

R2 = 0.2976

-10%

0%

10%

20%

30%

40%

50%

0 10 20 30 40 50 60 70 80 90 100

II Rating

Ave

rage

ret

urns


Higher risk means equity investors require a higher rate of return

Risk Ratings from Institutional Investor

61

• Equation implies an increase in the medium-term risk premium– This helps explain the recent decline in the

equity market– This helps explain the recent behavior of the

U.S. dollar– This helps explain the slow down in real

investment (hurdle rates are up)


62

• Efficiently functioning stock markets make a difference in the real economy– There is now substantial cross-country evidence

on the impact of stock market development on the real economy

Stock Markets and the Real EconomyStock Markets and the Real Economy

63

• Market integration has a fundamental influence on asset prices


64


Prices

High Expected Announcement Implementation Low ExpectedReturns of Liberalization Returns

PI

PS

Time

Segmented Integrated

Asset Prices and Market Integration

Return to Integration

65

-0.10

0.00

0.10

0.20

0.30

0.40

0.50

0.60Pre Post

Average Annual Geometric Returns


66

-0.10-0.050.000.050.100.150.200.250.300.350.400.45 Pre Post

Correlation with World


67

Implications

• Lower cost of capital

• More investment, employment

• More economic growth

Geert Bekaert, Campbell Harvey and Chris Lundblad, Does Financial Liberalization Spur Growth?

• Not just an emerging markets effect: Euro also increased integration


68

Findings

• Liberalization increases real growth by 1% per year for five years – which is a large number

• The liberalization effect is robust to– different definitions of liberalization dates– to business cycle or interest rate controls– allowing for intensity of liberalization

...and independent of capital account liberalization


69

Findings

• We control » macroeconomic reforms» financial development» other regulatory reforms

...and effect is intact


70

But is there a cost?

• Foreign speculators• Economic crises• Irrational contagion


71


• Liberalization may lead to “hot speculative capital” and induce capital flight (Stiglitz & others)– One can always point to a particular country to support

this idea– What about looking at a broad cross section?


72


Geert Bekaert, Campbell Harvey and Chris Lundblad, Growth Volatility and Equity Market Liberalization, 2002.

• No evidence that GDP growth volatility increases after markets open up


73

Standard Deviation of GDP Growth Rates1980-2000

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

ARGBRA

CHLGRC

IND

KORM

EXZAF

THAZW

ECOL

JOR

MYS

NGAPAK

PHLVEN

IDN

PRTTUR

NZLESP

JPN

LKA

Average

Stan

dard

dev

iati

on

Pre-liberalization Post-liberalization


74

• Predictability arises naturally from business cycle fluctuations – it need not be confused with irrationality

• While the research is very important, the case has not yet been made for widespread application of behavioral models

• Stock markets, in general, play a positive role – not just for investors and corporations – but the economy

ConclusionsConclusions

75

• My articles on www.duke.edu/~charvey– The Drivers of Expected Returns in International Markets (2000)– Global Tactical Asset Allocation (2001) with Magnus Dahlquist– The Term Structure of Equity Risk Premia (2002) with Claude Erb– Characterizing Systematic Risk of Hedge Funds with Buy-and-Hold

and Option-Based Strategies, (2002) Vikas Agarwal and Naranyan Y. Naik

– Portfolio Selection with Higher Moments, with John Liechty, Merrill Liechty, and Peter Müller

– Does Financial Liberalization Spur Growth? with Geert Bekaert, and Chris Lundblad

– Growth Volatility and Equity Market Liberalization with Geert Bekaert, and Chris Lundblad

ReadingsReadings

http://www.duke.edu/~charvey

rational international investment

Documents

real us bond returnssource

real us bill returnssource

real us equity returnssource

real bond returns

month us treasury bill

expectworld real equity

expecttenyear risk premium

long horizondata