Transcript US Risk in a Global Setting

WHU Campus for Finance
“Rationality of Stock Markets and Empirical Finance”
January 2003
Rational International Investment
Campbell R. Harvey, Ph.D.,
Professor,
Duke University
http://www.duke.edu/~charvey
1
The Plan
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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
2
The International Track Record
International Performance
13.0%
Wilshire Mid Cap
Return
(May 1986 to June 2002)
12.0%
Thirty Year Treasury STRIP
Twenty Year Treasury STRIP
Wilshire Large Cap
11.0%
Wilshire 5000
Ten Year Treasury STRIP
10.0%
EAFE X-Japan
9.0%
Seven Year Treasury STRIP
Credit
MBS
Five Year Treasury STRIP
Aggregate
Government
Three Year Treasury STRIP
Two Year STRIP
8.0%
7.0%
Wilshire Small Cap
EAFE
Germany
One Year Treasury STRIP
6.0%
0%
5%
Source: Erb and Harvey (2002)
10%
15%
Volatility
(May 1986 to June 2002)
20%
25%
3
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A
Returns and Diversification
Average Annual Returns During U.S. Business Cycle Phases
30
20
10
0
-10
-20
-30
Expansion geometric mean
Data from MSCI
Recession geometric mean
4
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Ve Tu and
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Comb uel
m abw a
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Returns and Diversification
Average Returns During U.S. Business Cycle Phases
Annual
Return
U.S. $ 20
30
10
0
-10
-20
-30
Expansion geometric mean
Data from IFC
Recession geometric mean
5
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or W S
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ex ld
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FE
A
Returns and Diversification
Average Annual Volatility During U.S. Business Cycle Phases
60
50
40
30
20
10
0
Expansion std.dev.
Data from MSCI
Recession std.dev.
6
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it z de
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W
or W S
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FE
A
Returns and Diversification
Correlations During U.S. Business Cycle Phases
1
0.8
0.6
0.4
0.2
0
-0.2
Expansion correlation with US
Data from MSCI
Recession correlation with US
7
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or
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U
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U
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or W S
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ex ld
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A
Returns and Diversification
Covariances During U.S. Business Cycle Phases
45
40
35
30
25
20
15
10
5
0
Expansion covariance with US
Data from MSCI
Recession covariance with US
8
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A
Returns and Diversification
Average Returns During U.S. Up and Down Markets
60
40
20
0
-20
-40
-60
US+ geometric mean
Data from MSCI
US- geometric mean
9
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Comb uel
m abw a
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Returns and Diversification
Average Returns During U.S. Up and Down Markets
Annual
Return
U.S. $ 40
60
20
0
-20
-40
-60
US+ geometric mean
Data from IFC
US- geometric mean
10
US Business Cycle is Predictable
US Yield Curve Inverts Before Last Six US Recessions
Annual
GDP growth
or Yield Curve
(5-year US Treasury bond - 3-month US Treasury bill)
8
% Real annual GDP growth
6
4
2
0
Yield curve
-2
Recession
Correct
-4 Recession
Correct 2 Recessions
Correct
Recession
Correct
Yield curve accurate
in recent forecast
Data though 1/12/03
M
ar
-6
9
M
ar
-7
1
M
ar
-7
3
M
ar
-7
5
M
ar
-7
7
M
ar
-7
9
M
ar
-8
1
M
ar
-8
3
M
ar
-8
5
M
ar
-8
7
M
ar
-8
9
M
ar
-9
1
M
ar
-9
3
M
ar
-9
5
M
ar
-9
7
M
ar
-9
9
M
ar
-0
1
-6
11
Returns and Diversification
Evolution of Correlation with U.S.
1
0.8
0.6
0.4
0.2
Corr(WorldXUS, US)
Data from IFC and MSCI
20
02
20
00
19
98
19
96
19
94
19
92
19
90
19
88
19
86
19
84
19
82
19
80
19
78
19
76
19
74
19
72
19
70
0
Corr(IFC,US)
12
Returns and Diversification
Acrobat Document
Source: Goetzmann, Li and Rouwenhorst (2002)
13
Returns and Diversification
60
Number of Countries
50
40
30
Acrobat Document
20
10
0
1860
1880
1900
1920
Core Markets
1940
Total
Source: Goetzmann, Li and Rouwenhorst (2002)
1960
1980
2000
Available Markets
14
ly
Ja
pa
n
Ita
Data from Dimson, Marsh and Stauton (2002)
U.
S.
W
or
W
ld
or
ld
X
-U
S
UK
he
r
So land
ut
s
h
Af
r ic
a
Sp
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Sw
ed
en
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iu
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De a
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ar
k
Fr
an
ce
Ge
rm
an
Ir e
la
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Be
lg
Au
str
a
The Long Horizon
100 Years of Real Equity Returns
9
8
7
6
5
4
3
2
1
0
15
The Long Horizon
100 Years of Real Equity Returns
20
15
10
5
0
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
-5
U.S. equity
World X-US equity
Data from Dimson, Marsh and Stauton (2002)
16
The Long Horizon
100 Years of Real Bond Returns
3
2.5
2
1.5
1
0.5
U.
S.
W
or
W
ld
or
ld
X
-U
S
UK
he
r
So land
ut
s
h
Af
r ic
a
Sp
ain
Sw
ed
en
ly
Ja
pa
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Ne
t
-1
Ita
Au
str
a
-0.5
lia
Be
lig
um
Ca
na
d
De a
nm
ar
k
Fr
an
ce
Ge
rm
an
Ir e
la
nd
0
-1.5
-2
-2.5
Data from Dimson, Marsh and Stauton (2002)
17
The Long Horizon
100 Years of Real Bond Returns
10
5
0
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
-5
-10
U.S.
World X-US
Data from Dimson, Marsh and Stauton (2002)
18
What to Expect
Dividend Yield
Dividend Yields Correlated With Future Returns
8
7
6
5
4
3
2
1
0
m
ce
ny
rk
lia
da
nd
u
n
a
a
a
a
a
i
l
a
r
n
g
m
t
e
a
nm
el
Fr
Ir
er
us
e
C
B
A
G
D
ly
a
It
1900 Yield
Data from Dimson, Marsh and Stauton (2002)
an
ap
J
N
l
er
h
et
ds
n
a
h
ut
o
S
A
a
ic
r
f
n
ai
p
S
en
ed
Sw
U
K
U
S
2000 Yield
19
What to Expect
Price Earnings Ratios
50
40
30
PE ratio
20
10
0
a
k
m
ce
-10 alia
ny
r
d
nd
u
n
a
a
a
a
i
l
a
r
g
m
t
e
an
nm
el
Fr
Ir
er
us
e
C
-20
B
A
G
D
ly
tI a
-30
an
p
a
J
N
rl
e
h
et
ds
n
a
h
ut
o
S
A
a
ic
r
f
n
ai
p
S
en
d
e
Sw
U
K
U
S
-40
Dec-99
Data from MSCI. Japan divided by 10.
Dec-02
20
What to Expect
Price to Trailing Peak Earnings vs 5 Year Average CPI
(overlapping annual data)
(1920- August 2002)
35
Price to Trailing Peak Earnings
30
1996 -2001
25
20
Current environment:
Inflation: 2.3%
P/E: 24.7x January 2003
15
.
10
5
Source: Bloomberg, Standard & Poor’s
0
-10.0%
-5.0%
Source: Goldman Sachs (2002)
0.0%
5.0%
5 yr Average CPI
10.0%
15.0%
20.0%
21
What to Expect
• Ten-year risk premium around 3.5% and stable
whereas one-year risk premium quite variable
6
6
5
5
4
4
3
3
2
2
1
1
0
0
6-Jun-00
7-Jun-01
4-Jun-02
7-Sep-00
10-Sep-01
16-Sep-02
4-Dec-00
4-Dec-01
2-Dec-02
12-Mar-01
11-Mar-02
10-year premium
Source: Graham and Harvey (2003)
6-Jun-00
7-Jun-01
4-Jun-02
7-Sep-00
10-Sep-01
16-Sep-02
4-Dec-00
4-Dec-01
2-Dec-02
12-Mar-01
11-Mar-02
1-year premium
22
What to Expect
U.S. Equity and Bond Returns are Positively Correlated
Rolling Five Year S&P 500 Return
40.00%
35.00%
30.00%
y = 0.794x + 0.0791
25.00%
R = 0.167
2
20.00%
15.00%
10.00%
5.00%
0.00%
-5.00%
-10.00%
-15.00%
-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)
Source: Erb and Harvey (2002)
23
What to Expect
World Real Equity and Real Bond Returns are Positively Correlated
40
Ten Year Real Stock Return
30
y = 0.6783x + 4.815
R2 = 0.3984
20
10
0
-10
-20
-30
-40
-30
-20
-10
0
10
20
Ten Year Real Bond Return
Source: Erb and Harvey (2002)
24
What to Expect
Inflation Negatively Related to Real US Bill Returns
15.0%
T-Bill Real Return
10.0%
5.0%
0.0%
-5.0%
-10.0%
-15.0%
y = -0.7078x + 0.0294
R2 = 0.5373
-20.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
10.0%
15.0%
20.0%
Inflation
Source: Erb and Harvey (2002)
25
What to Expect
Inflation Negatively Related to Real US Intermediate Bond Returns
30.0%
Intermediate Bond Real Return
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
-5.0%
-10.0%
-15.0%
-20.0%
-15.0%
y = -0.9873x + 0.0545
2
R = 0.3639
-10.0%
-5.0%
0.0%
5.0%
10.0%
15.0%
20.0%
Inflation
Source: Erb and Harvey (2002)
26
What to Expect
Inflation Negatively Related to Real US Bond Returns
40.0%
Long Bond Real Return
30.0%
20.0%
10.0%
0.0%
-10.0%
-20.0%
y = -1.3027x + 0.0664
2
R = 0.2767
-30.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
10.0%
15.0%
20.0%
Inflation
Source: Erb and Harvey (2002)
27
What to Expect
Inflation Negatively Related to Real US Equity Returns
60.0%
S&P Real Return
40.0%
20.0%
0.0%
-20.0%
y = -1.1054x + 0.1299
2
R = 0.0546
-40.0%
-60.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
10.0%
15.0%
20.0%
Inflation
Source: Erb and Harvey (2002)
28
What to Expect
Inflation Negatively Related to Real International Bill Returns
4
100 Year Real Bill Return
3
2
1
0
-1
-2
y = -0.9226x + 4.7819
-3
R = 0.8021
2
-4
-5
0
1
2
3
4
5
6
7
8
9
10
100 Year Inflation Rate
Source: Erb and Harvey (2002)
29
What to Expect
Inflation Negatively Related to Real International Bill Returns
3
100 Year Real Bond Return
2
1
0
-1
y = -0.6731x + 3.9725
2
R = 0.6097
-2
-3
0
1
2
3
4
5
6
7
8
9
10
100 Year Inflation Rate
Source: Erb and Harvey (2002)
30
What to Expect
Inflation Negatively Related to Real International Equity Returns
8
100 Year Real Equity Return
7
6
5
4
y = -0.6333x + 8.3176
3
R = 0.4935
2
2
1
0
0
1
2
3
4
5
6
7
8
9
10
100 Year Inflation Rate
Source: Erb and Harvey (2002)
31
What to Expect
Inflation Negatively Related to Real International Equity Returns
10
y = -0.6333x + 8.3176
100 Year Real Return
8
R2 = 0.4935
6
4
y = -0.6731x + 3.9725
2
2
R = 0.6097
0
-2
y = -0.9226x + 4.7819
-4
R2 = 0.8021
-6
0
1
2
3
4
5
6
7
8
9
10
100 Year Inflation Rate
Real Bill
Source: Erb and Harvey (2002)
Real Bond
Real Equity
32
Rethinking Risk
• Traditional models maximize expected
returns for some level of volatility
• Is volatility a complete measure of risk?
33
Rethinking Risk
• Much interest in prospect theory, downside
risk, asymmetric volatility, semi-variance,
extreme value analysis, regime-switching,
jump processes, ...
34
Rethinking 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
35
Rethinking 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
36
Rethinking 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:
37
Rethinking 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
38
Rethinking 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?
39
Rethinking 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!]
40
Rethinking Risk
12.5
2
Expected Return 10
7.5
5
1
0
0
Skewness
5
-1
Variance
10
15
Source: Harvey and Siddique (2000)
-2
41
us
t
A ralia
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Be stri
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Ca ium
D na
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Fi ark
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Fr and
G a
H erm nce
on a
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N J taly
N et he apa
ew rl n
Ze and
a s
N lan
o d
Po rwa
rtu y
g
Sp al
Sw Swe ai n
it z de
er n
la
n
Ud
K
W
U
or W S
ld or
ex ld
EAUS
FE
A
Rethinking Risk
Average Skewness in Developed Markets
1
0.5
0
-0.5
-1
-1.5
-2
Data from MSCI
42
rg
e
Banti n
hr a
Br a in
a
Chz il
Cz
i
e c Co Chi l e
h lo na
Re m
pu bia
Egbl ic
G yp
H ree t
un c e
ga
In In ry
do di
ne a
Is sia
Jo rae
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M Ko an
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a
M ysi a
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M x
or ic o
o
N cco
ig
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PaOm i a
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Po nes
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i L ica
Ta a nk
Th iw a
a i an
la
T
V ur nd
en ke
Zi ez y
Comba uela
m bw
po e
sit
e
A
Rethinking Risk
Average Skewness in Emerging Markets
1
0.5
0
-0.5
-1
-1.5
-2
Data from IFC
43
us
t
A ralia
us
Be tri
lg a
C iu
D ana m
en da
m
Fi ark
n
Fr land
G an
H erm ce
on a
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K
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N J taly
N et he apa
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a s
N land
o
Po rwa
rtu y
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Sp al
Sw Sw ai n
itz ede
er n
lan
d
U
K
W
U
or W S
ld or
ex ld
EAUS
FE
A
Rethinking Risk
Average Excess Kurtosis in Developed Markets
6
5
4
3
2
1
0
-1
Data from MSCI
44
rg
e
Banti n
hr a
Br a in
az
Ch il
Cz C C il
e c o hi e
h lom na
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In In ry
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M Ko an
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M ysi a
M ex
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N cco
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Pa Om i a
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Ph sta n
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Po nes
Sa R lan
ud u d
i A ssi
So Sl rab a
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S r A fr ki a
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Ta a nk
Th iw a
a i an
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V Tur nd
e k
Zi nez e y
Comba uela
m bw
po e
sit
e
A
Rethinking Risk
Average Excess Kurtosis in Emerging Markets
6
5
4
3
2
1
0
-1
Data from IFC
45
Alternative Vehicles
Alternate Asset Classes Often Involve Implicit or Explicit Options
7
6
5
4
3
2
1
0
-1
-2
-3
-4
S&P 500
Global Macro
1
2
3
Source: Agarwal and Naik (2002)
4
5
46
Alternative Vehicles
Alternate Asset Classes Often Involve Implicit or Explicit Options
8
6
4
2
S&P 500
Trend Followers
0
-2
-4
-6
-8
1
2
3
Source: Agarwal and Naik (2002)
4
5
47
Alternative Vehicles
Alternate Asset Classes Often Involve Implicit or Explicit Options
7
6
5
4
3
2
1
0
-1
-2
-3
-4
S&P 500
FI Arb
1
2
3
Source: Agarwal and Naik (2002)
4
5
48
Alternative Vehicles
Alternate Asset Classes Often Involve Implicit or Explicit Options
2
1.5
1
0.5
Delta(BAA-10yTBond)
x10
FI Arb
0
-0.5
-1
-1.5
-2
1
2
3
Source: Agarwal and Naik (2002)
4
5
49
Alternative Vehicles
Alternate Asset Classes Often Involve Implicit or Explicit Options
.1
Panel B: PRAM Returns, 1990 - 1998
Risk Arb Return - Risk-free Rate
.08
.06
9002
9811
9602
9504
9706
9011
9410 9704
9107
9010
9004
9304
9607 9411
9407
9712
9310
9311
9312 9308
9710
9402
9801
9804
9610
9006
9606
9105
9101
9508
9201
9207
9604
9301
9408
9611 9005
9208
9306
9106 9807
9608
9701
9303
9409
9605
9507
9404
9509
9505
9812
9203 9702
9412
9405
9506
9502
9806
9112
9802
9210
9307
9708 9206
9501
9603
9512
9510
9205
9209
9202
9511
9612
9109
9108
9805 9104
9810
9003
9609 9705
9711
9110
9302
9103
9211
9305
9707
9403 9406
9212
9309
9401
9204
9503
9709 9102
9001 9703
9007
9601 9803
9111
.04
.02
0
-.02
9008
9012
9809
9808
-.04
-.06
9009
-.08
-.1
-.2
-.16
-.12
-.08
-.04
0
.04
.08
.12
.16
.2
Market Return minus Risk-free Rate
50
Source: Figure 5 from Mitchell & Pulvino (2000)
Alternative Vehicles
Alternate Asset Classes Often Involve Implicit or Explicit Options
6
4
Event Driven Index Returns
2
0
-15
-10
-5
0
5
10
-2
-4
LOWESS fit
-6
-8
Russell 3000 Index Returns
Source: Agarwal and Naik (2002)
51
Rethinking Risk
Skewness has potential to explain one of the
unsolved anomalies in finance: the profitability
of momentum trading
25
Momentum portfolios
Mean
20
15
y = -5.3067x + 24.869
10
2
R = 0.5934
5
0
0
0.5
1
1.5
Skew
2
2.5
3
52
Rethinking Risk
•Harvey, Liechty, Liechty and Müller (2002)
“Portfolio Selection with Higher Moments”
provide a new approach to portfolio selection
which accounts for:
Higher moments
Estimation errors in the inputs
53
The 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
54
Ja
n
Fe -01
b
M -01
ar
A -01
p
M r-01
ay
Ju -01
nJu 01
A l-01
ug
Se -01
p
O -01
c
N t-01
ov
D -01
ec
Ja -01
n
Fe -02
b
M -02
ar
A -02
p
M r-02
ay
Ju -02
nJu 02
A l-02
ug
Se -02
p
O -02
c
N t-02
ov
D -02
ec
Ja -02
n03
The Evolution of World Risk
ICRG
Political Risk
100
95
90
85
80
75
70
65
60
Equally-weighted world
Data from PRS
G-7xUS
Switzerland
United States
55
Ja
n
Fe -01
b
M -01
ar
A -01
p
M r-01
ay
Ju -01
nJu 01
A l-01
ug
Se -01
p
O -01
c
N t-01
ov
D -01
ec
Ja -01
n
Fe -02
b
M -02
ar
A -02
p
M r-02
ay
Ju -02
nJu 02
A l-02
ug
Se -02
p
O -02
c
N t-02
ov
D -02
ec
Ja -02
n03
The Evolution of World Risk
ICRG
Political Risk
100
95
90
85
80
75
70
65
60
Equally-weighted world
Data from PRS
Japan
Switzerland
United States
56
Ja
n
F e - 01
b
M -01
ar
A -01
p
M r-01
ay
Ju -01
nJu 01
A l-01
u
Se g-01
p
O -01
c
N t-01
ov
D -01
ec
Ja -01
n
F e - 02
b
M -02
a
A r-02
p
M r-02
ay
Ju -02
nJu 02
A l-02
ug
Se -02
p
O -02
c
N t-02
ov
D -02
ec
Ja -02
n03
The Evolution of World Risk
ICRG
Political Risk
100
95
90
85
80
75
70
65
60
EW world
Data from PRS
Japan
Germany
Switzerland
United States
57
The Evolution of World Risk
Risk Ratings December 2002
Luxembourg
Finland
Ireland
Switzerland
Iceland
Sweden
Denmark
New Zealand
Austria
Norway
94.5
94.0
92.5
92.5
92.0
91.5
91.0
91.0
90.5
90.0
Netherlands
Singapore
Portugal
Australia
Belgium
Japan
United Kingdom
Malta
Canada
Germany
88.5
88.5
87.5
87.0
87.0
87.0
87.0
86.5
86.0
86.0
Bahamas
Spain
Hungary
France
Italy
Slovenia
Brunei
United States
Bahrain
Poland
84.5
83.0
82.5
81.0
81.0
81.0
80.5
80.0
79.5
79.5
58
Data from PRS
The Evolution of World Risk
Risk Ratings May 2001
Netherlands
Finland
Luxembourg
Denmark
Iceland
Sweden
Switzerland
United Kingdom
Canada
Ireland
New Zealand
Austria
United States
96.5
95.0
95.0
93.5
93.0
93.0
93.0
92.5
91.0
90.5
90.5
90.0
90.0
Portugal
Norway
Singapore
Germany
Japan
Australia
Belgium
Malta
Bahamas
Costa Rica
Italy
Spain
Slovenia
90.0
90.0
89.5
88.0
88.0
87.0
87.0
87.0
84.5
83.5
83.0
82.0
81.5
Chile
Slovak Rep.
Uruguay
Brunei
France
Qatar
U.A.E.
Hong Kong
Poland
Botswana
Cyprus
Czech Rep.
Greece
81.0
81.0
81.0
80.5
80.0
80.0
80.0
79.5
79.5
79.0
79.0
79.0
79.0
59
Data from PRS
The Evolution of World Risk
Higher risk means equity investors require a higher rate of return
50%
Average returns
40%
R2 = 0.2976
30%
20%
10%
0%
-10%
0
10
20
30
40
50
60
70
80
90
100
II Rating
60
Risk Ratings from Institutional Investor
The Evolution of World Risk
• 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)
61
Stock Markets and the Real Economy
• 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
62
Stock Markets and the Real Economy
• Market integration has a fundamental
influence on asset prices
63
Stock Markets and the Real Economy
Asset Prices and Market Integration
Prices
Segmented
Integrated
PI
PS
Return to Integration
Time
High Expected Announcement
Returns
of Liberalization
Implementation
Low Expected
Returns
64
Stock Markets and the Real Economy
Average Annual Geometric Returns
0.60
Pre
Post
0.50
0.40
0.30
0.20
0.10
0.00
-0.10
il e ia e a a n a a o a n s l n d y a e e
a
in raz Chil mb r eec Indi esi rda ore aysi exic ger i ista pine tuga iw a ilan r ke zuel abw rag
t
n o K al
o G
en B
M Ni Pak ilip Por Ta Tha Tu ene imb Ave
g
ol
do J
r
M
n
C
I
A
V Z
Ph
65
Stock Markets and the Real Economy
Correlation with World
0.45
0.40
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
-0.05
-0.10
Pre
Post
il e ia e a a n a a o a n s l n d y a e e
a
in raz Chil mb r eec Indi esi rda ore aysi exic ger i ista pine tuga iw a ilan r ke zuel abw rag
t
n o K al
o G
en B
M Ni Pak ilip Por Ta Tha Tu ene imb Ave
g
ol
do J
r
M
n
C
I
A
V Z
Ph
66
Stock Markets and the Real Economy
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
67
Stock Markets and the Real Economy
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
68
Stock Markets and the Real Economy
Findings
• We control
» macroeconomic reforms
» financial development
» other regulatory reforms
...and effect is intact
69
Stock Markets and the Real Economy
But is there a cost?
• Foreign speculators
• Economic crises
• Irrational contagion
70
Stock Markets and the Real Economy
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?
71
Stock Markets and the Real Economy
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
72
Stock Markets
and the Real Economy
Standard Deviation of GDP Growth Rates
1980-2000
0.08
Pre-liberalization
Post-liberalization
0.07
0.05
0.04
0.03
0.02
0.01
LK
A
Av
er
ag
e
JP
N
ES
P
NZ
L
TU
R
PR
T
N
ID
VE
N
L
PH
K
PA
A
NG
YS
M
JO
R
CO
L
ZW
E
TH
A
ZA
F
R
EX
M
KO
D
IN
GR
C
CH
L
BR
A
0
AR
G
Standard deviation
0.06
73
Conclusions
• 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
74
Readings
• 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
75
with Geert Bekaert, and Chris Lundblad