US Risk in a Global Setting
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Transcript US Risk in a Global Setting
RISK IN EMERGING CAPITAL
MARKETS
…from a Global Tactical Asset Allocation Perspective.
1
Emerging Capital Markets: Definition
The IFC Definition: Income less than $9,000…
21% of World GDP
Share of World Population, 1996
Dev eloped
16%
Emerging
84%
Emerging
19%
85% of the World Population
Developed
81%
Share of World Equity market Capitalization
Emerging
9%
11% of the World Equity Market
Capitalization
Dev eloped
91%
Emerging Markets: Performance
Returns
Return per Year (1995-2005)
20%
15%
15%
9%
10%
7%
6%
4%
5%
-4%
0%
-5%
ASIA
East
Europe
Latin
Middle
All
America East and Emerging
Africa
Markets
USA
Emerging Markets
Volatility
Standard Deviation of Returns per Year (1995-2005)
45%
40%
40%
35%
30%
30%
25%
25%
20%
23%
20%
16%
15%
10%
5%
0%
ASIA
East
Europe
Latin
America
Middle
East and
Africa
All
Emerging
Markets
USA
Emerging Markets
Bullish and Bearish Months
Number of Months with Positive and Negative Returns
(1995-2005)
90
78
80
70
68
81
76
81
78
64
54
60
56
51
54
51
50
40
30
20
10
0
ASIA
East
Europe
Latin
America
Middle
East and
Africa
All
Emerging
Markets
USA
Emerging Markets
Bullish and Bearish Local Returns
Annual Returns during Bullish and Bearish Markets
(1995-2005)
150%
100%
100%
66%
58%
67%
61%
31%
50%
0%
-50%
-36%
-61%
-69%
-100%
-67%
-95%
-108%
-100%
-150%
ASIA
East
Europe
Latin
America
Middle
All
East and Emerging
Africa
Markets
USA
A
rg
en
B tin
ah a
ra
B in
ra
C zil
C
h
ze C C ile
h
ch ol i
on
R ma
ep b
ub ia
E lic
g
G yp
H re t
u n ec
ga e
In I ry
do nd
ne ia
s
Is ia
r
Jo ae
rd l
a
M Ko n
al re
a a
M ysi
M ex a
or ic
o o
N cc
ig o
e
O ria
Pa m
ki an
Ph sta
ili P n
p p er
u
Po ine
Sa la s
ud R nd
i A uss
i
So Sl rab a
o
ut v ia
h ak
Sr Af ia
i L ric
a
T an
k
a
T iw a
ha a
ila n
V Tu n d
e r
Z nez key
im u
C b el
om ab a
po we
si
te
us
tr
A alia
u
B stri
el a
g
C ium
an
D a
en da
m
Fi ark
nl
Fr and
G an
H erm ce
on a
g ny
K
Ir ong
el
an
d
It
a
N J ly
e
N t he apa
ew rl n
a
Z nd
ea s
N lan
or d
Po wa
rt y
ug
Sp al
S a
Sw w i n
e
it de
ze n
rl
an
d
U
K
U
W
or W S
ld or
ex ld
-U
E S
A
FE
A
Emerging Markets
Bullish and Bearish US Returns
Average Returns During U.S. Up and Down Markets
60
40
20
0
-20
-40
-60
A nnual
Return
U.S. $
40
60
Average Returns During U.S. Up and Down Markets
US+ geometric mean
US+ geometric mean
US- geometric mean
20
0
-20
-40
-60
US- geometric mean
N
M
A
A
M
D
IU
A
ve
r
SA
.
ag
e
U
.K
Since 1980
U
FI R K
N
L
A
N
FR D
A
G NC
E
R E
M
H
O AN
N
G Y
K
O
I R NG
E
L
A
N
D
IT
A
L
Y
N JA
P
E
TH A
N
E
R
L
N ND
O
N RW
W
A
Y
Z
E
A
SI LN
N
G D
A
PO
R
E
SP
A
SW IN
ED
E
N
SW
IS
S
E
IA
R
IA
L
A
G
N
L
C
A
B
E
ST
R
A
U
ST
A
U
D
A
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
-0.1
K
or
M ea
al
ay
si
a
M
ex
ic
o
N
ig
er
Pa ia
k
Ph ista
ili n
pp
in
e
Po s
rt
ug
a
T l
ai
w
T an
ha
ila
nd
T
ur
V key
en
ez
u
Z el
im a
ba
bw
A e
ve
ra
ge
C
hi
l
ol e
om
bi
a
G
re
ec
e
In
In dia
do
ne
si
a
Jo
rd
an
il
na
ra
z
C
B
A
rg
en
ti
Emerging Markets
Correlations with World Returns
Since 1990
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
-0.1
International Stock and Country Selection
A critical component of stock valuation in international context is
knowing the appropriate “required rate of return”.
Value
Cash Flow
–
–
–
Currency
Translation
Accounting
Adjustments
Taxes
Timing
–
–
Liquidity
Repatriation
Limits
Return Risk
–
–
–
–
Systematic
Currency
Information
Sovereign/
Credit Risk
Traditional Risk Decomposition
Return:
Risk:
Rit – rft
= ai +
bi[Rmt – rft]
+ eit
s 2i
= 0+
b2 s2m
+ s2ei
Total Risk
Variability
Market Risk
•Beta Risk
b 2 s 2m
s 2i
Specific Risk
s2ei
Extramarket Risk
Unique Risk Firm
Macro Risk
Oil Price, G7 inflation,
FX to $, Spreads, G7
industrial production
“Micro” Risk
•Local Beta
•Size (Market Cap)
•Value Vs Growth
Common Factor Risk
Country Risk
Political, economic,
financial risk
Specific Risk
Emerging Markets Risks
World Beta?
Returns and Beta from 1990 through 1998:03
Average returns
0.4
0.3
R2 = 0.1064
0.2
0.1
0
-0.5
-0.1 0
0.5
1
1.5
-0.2
Beta
Incorporating the Asian crisis makes the model look even worse.
2
Emerging Markets Risks
Local Beta?
Countries
(HML-Beta)
(HML-Beta-down)
(HML-Beta-up)
All countries
-0.0023***
-0.0156***
0.0209***
Colombia
-0.0354**
-0.0558***
0.014
Egypt
0.0137
-0.042***
0.0619***
Israel
0.0003
-0.0197***
0.031***
Korea
-0.0062***
-0.0175***
0.014***
Malaysia
-0.0132***
-0.0355***
0.0258***
Morocco
-0.0107***
-0.0116***
0.0099**
Peru
-0.0197***
-0.0302***
0.0187**
Philippines
-0.0093***
-0.0157***
0.0177***
Poland
-0.0005
-0.0156***
0.0167***
Taiwan
-0.0067***
-0.0187***
0.0116***
-0.001
-0.0099***
0.0252***
Thailand
Emerging Markets Risks
Size, Value, Investability, liquidity Risks
Size (x $1,000)
Price-to-book
Investability
Turnover
Inv.
N-inv.
Inv.
N-inv.
Inv.
N-inv.
817.03
140.80
1.42
1.07
0.78
0.00
0.46
2.36
Brazil
1,490.95
505.89
1.15
1.01
0.72
0.00
0.52
0.10
China
2,086.73
489.70
2.00
12.94
0.79
0.00
1.27
1.39
Egypt
2,135.99
396.30
18.45
9.02
0.64
0.00
0.29
0.29
India
28,053.19
5,839.61
37.51
21.29
0.29
0.00
1.48
0.51
Korea
856.36
176.31
1.79
1.27
0.69
0.00
2.50
1.78
Malaysia
687.16
245.33
3.54
5.43
0.68
0.00
0.43
0.51
4,018.64
1,649.39
3.66
0.70
0.54
0.00
0.34
0.14
Thailand
569.21
240.25
67.07
29.41
0.36
0.00
0.71
1.92
Turkey
677.87
278.59
12.64
4.61
0.57
0.00
1.62
3.70
1,921.26
450.52
7.69
4.85
0.66
0.00
0.64
0.79
Argentina
Russia
All Markets
Inv.
N-inv.
Rethinking Risk in Emerging Markets
Return Distribution
High Serial Correlations in Short-run (Basis for
Momentum strategies)
Long-term Mean Reversion (Basis for Value
strategies)
Positive Skewness and Kurtosis (Fat Tails, high
probability for large surprises)
Returns with positive skewness are characterized by
many small losses with a few extremely large
gains—i.e., Investors prefer small losses with
extremely large gains.
Positive excess kurtosis shows a greater chance for
an investor to receive a very large positive or
negative return —i.e., investors would gladly trade
a 100% loss on one investment for a potential 300%
gain
Returns, variance and kurtosis…
12.5
2
Expected Return 10
7.5
5
1
0
0
5
- 1
Variance
or Kurtosis
Source: Harvey and Siddique (2000)
10
15
- 2
Skewness
Data from MSCI
rg
e
B nti
ah na
r
B ain
ra
C zil
h
C
ze C Ch ile
o
ch l in
R om a
ep b
ub ia
Eg lic
G yp
H ree t
un c
ga e
In In ry
do di
ne a
s
Is ia
r
Jo ae
rd l
M Ko an
al re
a a
M ysi
M ex a
or ic
o o
N cc
ig o
er
PaOm i a
ki an
Ph sta
ili P n
pp eru
i
Po nes
Sa la
ud Ru nd
i A ss
i
So S rab a
l
o
ut v ia
h ak
Sr Af i a
i L ric
a
Ta ank
Th iw a
ai an
la
T
V ur nd
e k
Zi nez ey
m
C b uel
om ab a
po w e
sit
e
A
us
tr
A ali
u a
B str
el ia
g
C ium
D ana
en d
ma
Fi ark
nl
Fr and
G an
H erm ce
on
g any
K
o
Ir ng
el
an
It d
N aly
e J
N th ap
ew er an
l
Z and
ea s
N lan
or d
Po wa
rt y
ug
Sp al
S
Sw w ain
e
it de
ze n
rl
an
d
U
K
W
U
or W S
ld o
ex rld
-U
E S
A
FE
A
Developed versus Emerging markets: Skewness
Average Skewness in Developed Markets
1
0.5
0
-0.5
-1
-1.5
-2
Average Skewness in Emerging Markets
1
0.5
0
-0.5
-1
-1.5
-2
Data from MSCI
rg
e
B nti
ah na
r
B ain
ra
z
C il
hi
C
ze C C le
ch olo hin
R m a
ep bi
ub a
Eg lic
G yp
H ree t
un c
ga e
In In ry
do d
ne ia
s
Is ia
r
Jo ae
rd l
M Ko an
al re
a a
M ysi
M ex a
or ic
o o
N cco
ig
e
O ri
Pa m a
ki an
Ph sta
ili Pe n
pp ru
i
Po nes
Sa la
ud Ru nd
i A ss
i
So S rab a
ut lov ia
h ak
Sr Af i a
i L ric
a a
Ta nk
Th iw a
ai an
T la
V ur nd
e k
Zi nez ey
m
C b uel
om ab a
po we
sit
e
A
us
tr
A ali
us a
B tri
el a
g
C iu
m
a
D na
en d
ma
Fi ark
nl
Fr and
G an
H erm ce
on
g any
K
o
Ir n g
el
an
I d
N taly
e J
N th ap
ew er an
l
Z and
ea s
l
N an
or d
Po wa
rt y
ug
Sp al
S
Sw w ain
itz ede
er n
la
nd
U
K
W
U
or W S
ld or
ex ld
-U
E S
A
FE
A
Developed versus Emerging markets: Kurtosis
Average Excess Kurtosis in Developed Markets
6
5
4
3
2
1
0
-1
Average Excess Kurtosis in Emerging Markets
6
5
4
3
2
1
0
-1
Sources of excess Variance, Skewness and Kurtosis
in Emerging Markets…
• Openness to foreign entry can be limited
• Securities are thinly traded and illiquid
• Insider trading laws, accounting standards and reporting, and contracts
enforcement differentials.
• Frequent government interventions in the economy and financial
markets—i.e., expropriation, nationalizations and capital freeze.
• Financial institutions can have political influences; concentrated
banking and financial activities in few major institutions “moral
hazard” is frequent.
Thus,
Both conditioning information (or risk) and higher moments matter and
are related…to the marginal information associated with:
• Trading Risk
• Investable Risk
• Political, economic and financial Risks
Emerging Markets Risks
Trading Risk
High transaction costs:
over 5% for a round trip.
Many trades may fail to
settle.
Cost of a Round Trip -- Purchase and
Later Sale of an Individual Stock
Stamp Taxes
Bid/Offer
Spread
Country
Commission
Total
Argentina
1.00%
0.48%
1.25%
2.73%
Illiquidity: cannot sell
your position without
taking substantial price
cut.
Brazil
1.00
0.14
2.48
3.62
Indonesia
1.30
0.30
1.50
3.10
Korea
0.80
0.50
2.25
3.55
Malaysia
1.20
0.10
1.09
2.39
Thailand
1.30
-
1.89
3.19
Germany
0.50
-
0.49
0.99
Short-sales may not be
allowed in EMs
Japan
0.40
0.30
0.75
1.45
United States
0.13
-
0.27
0.40
Source: Morgan Stanley International Portfolio Desk and Authors'
Estimates.
Emerging Markets Risks
Trading Risk (Information content of intraday
trading…)
Girard and Biswas (2006)
Volatility
persistence
Developed
Emerging
Developed
Emerging
0.866
0.794
Volatility
persistence
Expected
Volume
Unexpected
Volume
0.665
0.634
0.026
-0.173
0.273
0.498
Emerging Markets Risks
Trading Risk: It has evolved– Cairo and
Alexandria Stock Exchange
Period:
01/01/98 to 05/31/01
Volatility
persistence
Average
0.6255
Average
Period:
06/01/01 to 05/23/05
Average
0.5183
Average
Girard and Omran (2006)
Volatility
persistence
Expected
Volume
-0.3916
Expected
Volume
Unexpected
Volume
0.7290
Unexpected
Volume
0.7839
0.5128
0.1808
1.4099
Emerging Markets Risks
Trading Risk: Istanbul Stock Exchange
Girard and Kilmaz (2006)
1987-1993
Average
Average
2000-2005
Average
Average
Volatility
persistence
Expected
Volume
Unexpected
Volume
0.7679
0.7949
-0.1067
0.3691
Volatility
persistence
Expected
Volume
Unexpected
Volume
0.8905
0.8879
0.0264
0.0846
Emerging Markets Risks
Investable Risk: Foreign Ownership control
Foreign ownership limits are
often imposed in EM
Market integration has a
fundamental influence on asset
prices:
Permitting cross-border
ownership of equity increases
market value by 3.3% (Henry,
2000), and 10.4% for firms
eligible to be purchased by
foreigners, (Chari and Henry
2002).
Because risk premia are
reduced, large capital inflows,
relaxed financing constraints,
reduced FX volatility.
Investability
Inv.
N-inv.
Argentina
0.78
0.00
Brazil
0.72
0.00
China
0.79
0.00
Egypt
0.64
0.00
India
0.29
0.00
Korea
0.69
0.00
Malaysia
0.68
0.00
Russia
0.54
0.00
Thailand
0.36
0.00
Turkey
0.57
0.00
All Markets
0.66
0.00
The Effect of Liberalization
Asset Prices and Market Integration
Prices
Segmented
Integrated
PI
PS
Return to Integration
Time
High Expected Announcement
Returns
of Liberalization
Implementation
Low Expected
Returns
Evidence: Stock Markets Returns After
Liberalization
Average Annual Geometric Returns
0.60
Pre
Post
0.50
0.40
0.30
0.20
0.10
0.00
-0.10
a azil hile bia ece dia sia an rea sia ico er ia tan nes gal an nd ey ela w e ge
n
i
nt Br C lom Gr e In one Jord Ko alay ex Nig akis ippi ortu aiw aila Tur k ezu bab vera
e
M
T Th
n m A
g
d
P hil P
M
Co
In
Ar
Ve Zi
P
Stock Markets Volatility After Liberalization
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
Stock Markets Correlation After Liberalization
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
a azil hile bia ece dia sia an rea sia ico er ia tan nes gal an nd ey ela w e ge
n
i
nt Br C lom Gr e In one Jord Ko alay ex Nig akis ippi ortu aiw aila Tur k ezu bab vera
e
M
T Th
n m A
g
d
P hil P
M
Co
In
Ar
Ve Zi
P
Emerging Markets Risks
Investable Risk and Investable Premium
Girard (2006)
Countries
Stocks
Inv.
Stocks
N-inv.
Return
(Inv.)
Vol.
Return
(N-Inv.)
Vol.
Inv.
premium
Argentina
41
17
0.0033
0.12
-0.0075
0.12
0.0108
Brazil
112
31
0.0080
0.10
0.0067
0.11
0.0013
China
73
235
0.0007
0.11
-0.0013
0.08
0.0024
Egypt
42
67
0.0050
0.08
-0.0097
0.05
0.0147
Korea
145
31
-0.0063
0.11
-0.0141
0.11
0.0078
Malaysia
127
46
0.0003
0.10
-0.0001
0.11
0.0004
Mexico
122
40
0.0181
0.10
0.0100
0.09
0.0081
Peru
36
35
0.0012
0.08
0.0002
0.08
0.0014
Philippines
65
51
-0.0043
0.08
-0.0052
0.08
0.0009
Russia
38
24
0.0227
0.17
0.0024
0.12
0.0203
Turkey
75
27
0.0016
0.15
-0.0006
0.14
0.0022
1,768
1,235
0.0051
0.12
0.0001
0.10
0.5%
All countries
Emerging Markets Risks
Determinants of investable risk…
Girard (2006)
Local Factors
Investment Social
Corruption
profile Tensions
rating
rating
rating
Conflicts
rating
Investable
Premium
-0.019***
-0.005***
-0.005***
Law and Debt
Order
Service
rating
rating
-0.004***
-0.002
0.001
Global Factors
Market
Premium
Value
Premium
Size
Premium
Mom.
Premium
Investable
Premium
Intercept
-0.0028***
-0.0051***
-0.0083***
0.0109***
-0.0007
World
Premium
0.0882
-0.0366
-0.0734
0.0152
0.1411***
World
Value Premium
0.0161
0.0276
0.1158
0.0356
-0.0869**
Emerging Markets Risks
Investable Risk: it is priced!
Girard (2006)
Independent
variables
Standardized
coefficients
t-statistic
Market factor
0.519
9.85***
1988-2004
Value factor
0.029
4.28***
1768 Stocks
Size factor
0.083
5.61***
Momentum factor
-0.009
-1.66*
Investability factor
0.351
7.59***
Period
Adj.R2
0.287
Emerging Markets Risks
Country Risk
– Political Risk: risk of loss when investing in a given country
caused by changes in a country's political structure or policies,
such as tax laws, tariffs, expropriation of assets, or restriction
in repatriation of profits.
– Economic Risk
– Financial Risk
Risk Category
Score Range
Very High Risk
0.0-49.5
High Risk
50.0-59.5
Moderate Risk
60.0-69.5
Low Risk
70.0-84.5
Very Low Risk
85.0-100.0
Inflation expectations for 1997
Emerging Markets Risks
Country Risk Ratings predict inflation
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0
20
40
60
Composite Rating
80
100
Emerging Markets Risks
Country Risk Ratings are correlated with wealth
Per capita real GDP
$25,000
$20,000
$15,000
$10,000
$5,000
$0
0
20
40
60
80
Composite ratings for 74 countries
100
Emerging Markets Risks
Country Risk Ratings predict volatility
70%
Annualized Volatility
60%
R2 = 0.5033
50%
40%
30%
20%
10%
0%
0
20
40
60
80
Composite Country Credit Rating
100
Emerging Markets Risks
Country Risk Ratings predict correlation
100%
R2 = 0.6809
Correlation with MSCI AC World
80%
60%
40%
20%
0%
0
20
40
60
80
-20%
Institutional Investor Countyr Credit Rating
100
Emerging Markets Risks
Country Risk Ratings explain returns
50%
Average returns
40%
R2 = 0.2976
30%
20%
10%
0%
0
10
20
30
40
50
60
-10%
Composite Rating
70
80
90
100
Country risk, stock selection, country
allocation: 4 examples…
Turkey: Too culturally different or financially,
economically and politically too immature?
Russia: Potentials…by watch Putin
Brazil: surprisingly robust market
Venezuela: How to do bad when everything goes
well?
The Case of Turkey: Cultural
Differences or Financially, Politically
and Economically too unstable?
1.0
0.8
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
2000
2001
RET_CZEC H
RET_ESTONIA
RET_E UROP E
RET_HUNGARY
RET_LATVIA
2002
2003
RET_LITHUANIA
RE T_P OLA ND
RET_SLOVA KIA
RET_SLOVE NIA
RE T_TURK E Y
Fundamentals (Beta, size, P/B)?
9
8
2800
1.2
2400
1.0
7
2000
6
5
1600
4
1200
0.8
0.6
0.4
3
800
2
0.2
400
1
0.0
0
0
2000
2001
PB_CZECH
PB_ESTONIA
PB_EUROPE
PB_HUNGARY
PB_LATVIA
2002
2003
PB_LITHUANIA
PB_POLAND
PB_SLOVAKIA
PB_SLOVENIA
PB_TURKEY
2000
2001
SIZE_CZECH
SIZE_ESTONIA
SIZE_EUROPE
SIZE_HUNGARY
SIZE_LATVIA
2002
2003
SIZE_LITHUANIA
SIZE_POLAND
SIZE_SLOVAKIA
SIZE_SLOVENIA
SIZE_TURKEY
2000
2001
MKTBETA_CZECH
MKTBETA_ESTONIA
MKTBETA_EUROPE
MKTBETA_HUNGARY
MKTBETA_LATVIA
2002
2003
MKTBETA_LITHUANIA
MKTBETA_POLAND
MKTBETA_SLOVAKIA
MKTBETA_SLOVENIA
MKTBETA_TURKEY
Or country specific (Economic,
Financial, Political)?
2
1
2
2
1
1
0
0
-1
-1
-2
-2
0
-1
-2
-3
-4
-3
2000
2001
ECONRZ_CZECH
ECONRZ_ESTONIA
ECONRZ_EUROPE
ECONRZ_HUNGARY
ECONRZ_LATVIA
2002
2003
ECONRZ_LITHUANIA
ECONRZ_POLAND
ECONRZ_SLOVAKIA
ECONRZ_SLOVENIA
ECONRZ_TURKEY
-3
2000
2001
FINRZ_CZECH
FINRZ_ESTONIA
FINRZ_EUROPE
FINRZ_HUNGARY
FINRZ_LATVIA
2002
2003
FINRZ_LITHUANIA
FINRZ_POLAND
FINRZ_SLOVAKIA
FINRZ_SLOVENIA
FINRZ_TURKEY
2000
2001
POLRZ_CZECH
POLRZ_ESTONIA
POLRZ_EUROPE
POLRZ_HUNGARY
POLRZ_LATVIA
2002
2003
POLRZ_LITHUANIA
POLRZ_POLAND
POLRZ_SLOVAKIA
POLRZ_SLOVENIA
POLRZ_TURKEY
Indeed…
DRETURN2
Intercept
Coefficient
t-Statistic
Prob.
DBeta
0.02818
-0.09001
0.29
-0.48
0.7737
0.6327
DPTBV
DSIZE
DECONRISK
DFINRISK
-0.92828
0.02150
-0.04038
-0.09044
-1.06
1.59
-2.04
-4.17
0.2947
0.1185
0.0474 b
0.0001 a
DPOLRISK
-0.06276
-1.90
0.065 c
Adjusted R-squared
0.331113
Russia
Mikhail Khodorkovsky, Oligarch.
Shareholder and former CEO of Yukos oil
company. Sentenced to 8 years in prison
1400
1200
Political
Risk
1000
800
600
Stock
Index
400
200
Oc
t-
05
4
31
-
4
Fe
b-0
De
c-0
31
-
3
27
-
02
Ap
r-0
30
-
01
Ju
n28
-
00
Oc
t-
Au
g31
-
9
31
-
9
De
c-9
31
-
8
Fe
b-9
26
-
97
Ap
r-9
30
-
96
Ju
n30
-
95
Au
g30
-
Oc
t31
-
30
-
De
c-9
4
0
Russia:
Impact of politics on investment policy
Equity market Russia looks attractive
large inflow of oil revenues improves financial position
and stimulates domestic economy
valuation is very cheap, price/earnings = 8
But politics is a major factor—i.e., state is interfering
increasingly and reversing privatizations, also risk for
politically motivated attacks on companies of oligarchs
Consequences for investment policy:
– Small overweight position in Russia
– select stocks with good political relations or low political
profile
Brazil
80
Political risk
70
60
50
40
Luiz Inácio Lula da Silva
President of Brazil
Financial
Risk
30
20
Economic Risk
10
Stock Index
0
19
85
0
19 1
85
1
19 1
86
0
19 9
87
0
19 7
88
0
19 5
89
0
19 3
90
0
19 1
90
1
19 1
91
0
19 9
92
0
19 7
93
0
19 5
94
0
19 3
95
0
19 1
95
1
19 1
96
0
19 9
97
0
19 7
98
0
19 5
99
0
20 3
00
0
20 1
00
1
20 1
01
0
20 9
02
0
20 7
03
0
20 5
04
03
Has improved economy
against expectations. Not directly
implicated in recent corruption
scandal
Brazil:
Impact of politics on investment policy
Corruption scandal has shocked Brazil—i.e., Members
of parliament paid for support, illegal campaign
financing
Though, sound monetary (not fiscal) policy remains
unchanged and elections in 2006 are unlikely to change
this successful policy
improved economic fundamentals, cheap valuation
Consequences for portfolio positions:
– Overweight position in Brazil
– select stocks that benefit from declining interest rates and
high commodity prices
19
85
01
19
85
1
19 1
86
0
19 9
87
07
19
88
0
19 5
89
0
19 3
90
01
19
90
1
19 1
91
0
19 9
92
0
19 7
93
0
19 5
94
03
19
95
0
19 1
95
1
19 1
96
09
19
97
0
19 7
98
0
19 5
99
0
20 3
00
0
20 1
00
11
20
01
0
20 9
02
0
20 7
03
0
20 5
04
03
000
900
80
Chavez is elected
70
800
60
700
600
50
500
0
40
400
30
300
20
200
100
10
0
Venezuela: Watch for
a Nut Case
Conclusion
Evolution of Integration and International Value
Dramatic internationalization of world:
Economic integration through increased trade leading to
current account surpluses, floating exchange rates,
single digit inflation, and lower debt levels
and
Financial integration has also increased through
liberalization of capital markets leading to a broader
selection of company targets, access to growth and
innovation in new markets, reduced taxes in selected
markets, reduced borrowing costs, and reduced risk
(diversification among less correlated markets)
But political, financial and economic policies will remain
important!
GTAA Vs STAA
Asset Allocation Strategies
Constant
weights
Slow evolving
weights
Strategic
Unconditional
Dynamic
weights
Tactical
Conditional
Implication on Portfolio management:
Conditioning Information and Portfolio
Analysis
Er
Add conditioning
information and weights
change through time.
Frontier shifts.
Traditional fixed weight
optimization (contrarian)
in 2-dimensional setting
Vol
• Conditioning information makes a difference Adding conditioning information is
like adding extra assets to an optimization
China
250
75
Political risk
•
9,5% real growth
35% export growth
50% of GDP invested each year
70
200
65
60
150
55
50
Stock Index
Financial
Risk
100
45
40
Economic Risk
50
35
30
0
12
92
10
93
25
08
94
06
95
04
96
02
97
12
97
10
98
08
99
06
00
04
01
02
02
12
02
10
03
China
Tax advantages for foreign direct investments to produce export
products
More roads, more rails, more (air)ports, real estate (since 2002 the
people of China may mortgage their homes)
Securing oil resources home and abroad, increasing electricity
generating capacity
Banks: Huge capital injections, banning local government
involvement and implementation of risk management
People: Favor investments in rural areas, where still 60% of the
people live, improving legal certainty (rights of ownership) and
pensions to increase disposable income
Investment plays based on reform:
Production: Car producers
Infrastructure: Transportation, shipping companies, property
developers
Energy: Oil companies, power producers
Banks: Listed state banks
People: Supermarkets, food producers or processors