Download - 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
Returns and DiversificationReturns and Diversification
-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
Returns and DiversificationReturns and Diversification
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
Returns and DiversificationReturns and Diversification
-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
Returns and DiversificationReturns and Diversification
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
Returns and DiversificationReturns and Diversification
-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
Returns and DiversificationReturns and Diversification
-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
Returns and DiversificationReturns and Diversification
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
Returns and DiversificationReturns and Diversification
Source: Goetzmann, Li and Rouwenhorst (2002)
14
Returns and DiversificationReturns and Diversification
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
The Long HorizonThe Long Horizon
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
Data from Dimson, Marsh and Stauton (2002)
17
The Long HorizonThe Long Horizon
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
Data from Dimson, Marsh and Stauton (2002)
18
The Long HorizonThe Long Horizon
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
Data from Dimson, Marsh and Stauton (2002)
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
Data from Dimson, Marsh and Stauton (2002)
20
What to ExpectWhat to Expect
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
What to ExpectWhat to Expect
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
What to ExpectWhat to Expect
• 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
What to ExpectWhat to Expect
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
Source: Erb and Harvey (2002)
24
What to ExpectWhat to Expect
World Real Equity and Real Bond Returns are Positively Correlated
Source: Erb and Harvey (2002)
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
What to ExpectWhat to Expect
Inflation Negatively Related to Real US Bill Returns
Source: Erb and Harvey (2002)
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
What to ExpectWhat to Expect
Inflation Negatively Related to Real US Intermediate Bond Returns
Source: Erb and Harvey (2002)
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
What to ExpectWhat to Expect
Inflation Negatively Related to Real US Bond Returns
Source: Erb and Harvey (2002)
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
What to ExpectWhat to Expect
Inflation Negatively Related to Real US Equity Returns
Source: Erb and Harvey (2002)
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
What to ExpectWhat to Expect
Inflation Negatively Related to Real International Bill Returns
Source: Erb and Harvey (2002)
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
What to ExpectWhat to Expect
Inflation Negatively Related to Real International Bill Returns
Source: Erb and Harvey (2002)
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 Year Inflation Rate
100
Yea
r R
eal B
ond
Ret
urn
31
What to ExpectWhat to Expect
Inflation Negatively Related to Real International Equity Returns
Source: Erb and Harvey (2002)
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 Year Inflation Rate
100
Yea
r R
eal E
qu
ity
Ret
urn
32
What to ExpectWhat to Expect
Inflation Negatively Related to Real International Equity Returns
Source: Erb and Harvey (2002)
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 Year Inflation Rate
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
Rethinking RiskRethinking Risk
• Much interest in prospect theory, downside risk, asymmetric volatility, semi-variance, extreme value analysis, regime-switching, jump processes, ...
35
Rethinking RiskRethinking Risk
• 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
Rethinking RiskRethinking Risk
• 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
Rethinking RiskRethinking Risk
• 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
Rethinking RiskRethinking Risk
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
Rethinking RiskRethinking Risk
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
Rethinking RiskRethinking Risk
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
Rethinking RiskRethinking Risk
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
Rethinking RiskRethinking Risk
-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
Rethinking RiskRethinking Risk
-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
Rethinking RiskRethinking Risk
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
Rethinking RiskRethinking Risk
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
Alternative VehiclesAlternative Vehicles
Alternate Asset Classes Often Involve Implicit or Explicit Options
-8
-6
-4
-2
0
2
4
6
8
1 2 3 4 5
S&P 500Trend Followers
Source: Agarwal and Naik (2002)
48
Alternative VehiclesAlternative Vehicles
Alternate Asset Classes Often Involve Implicit or Explicit Options
-4-3-2-101234567
1 2 3 4 5
S&P 500FI Arb
Source: Agarwal and Naik (2002)
49
Alternative VehiclesAlternative Vehicles
Alternate Asset Classes Often Involve Implicit or Explicit Options
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
1 2 3 4 5
Delta(BAA-10yTBond)x10FI Arb
Source: Agarwal and Naik (2002)
50
Alternative VehiclesAlternative Vehicles
Alternate Asset Classes Often Involve Implicit or Explicit Options
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
Alternative VehiclesAlternative Vehicles
Alternate Asset Classes Often Involve Implicit or Explicit Options
-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
Source: Agarwal and Naik (2002)
52
Rethinking RiskRethinking Risk
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
Rethinking RiskRethinking Risk
•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
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 Japan Switzerland United States
57
The Evolution of World RiskThe Evolution of World Risk ICRG Political Risk
Data from PRS
60
65
70
75
80
85
90
95
100
EW world Japan Germany Switzerland United States
58
The Evolution of World RiskThe Evolution of World Risk
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
The Evolution of World RiskThe Evolution of World Risk
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
The Evolution of World RiskThe Evolution of World Risk
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)
The Evolution of World RiskThe Evolution of World Risk
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
Stock Markets and the Real EconomyStock Markets and the Real Economy
64
Stock Markets and the Real EconomyStock Markets and the Real Economy
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
Stock Markets and the Real EconomyStock Markets and the Real Economy
66
-0.10-0.050.000.050.100.150.200.250.300.350.400.45 Pre Post
Correlation with World
Stock Markets and the Real EconomyStock Markets and the Real Economy
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
Stock Markets and the Real EconomyStock Markets and the Real Economy
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
Stock Markets and the Real EconomyStock Markets and the Real Economy
69
Findings
• We control » macroeconomic reforms» financial development» other regulatory reforms
...and effect is intact
Stock Markets and the Real EconomyStock Markets and the Real Economy
70
But is there a cost?
• Foreign speculators• Economic crises• Irrational contagion
Stock Markets and the Real EconomyStock Markets and the Real Economy
71
But is there a cost?
• 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?
Stock Markets and the Real EconomyStock Markets and the Real Economy
72
But is there a cost?
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
Stock Markets and the Real EconomyStock Markets and the Real Economy
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
Stock Markets and the Real EconomyStock Markets and the Real Economy
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