INTERNATIONAL EQUITY
MARKETS
2. Practical Issues
Topics I’m interested
• Diversification: Going International
- Stylized Facts and Correlations
- Home Bias
• Country Analysis – Country Risk
- Emerging Markets
- Risk Indicators
• Factors affecting International Stock Markets
• International Stock Markets: Links
- Crash October ’87
- High Volatility, High Correlations
Why Go International?
• Diversification
If it is good to diversify in domestic markets, it is even better to
diversify internationally.
Q: Why does the frontier move in the NW direction?
A: Low Correlations! Low correlations are the key to achieve lower risk.
• Empirical Fact #1: Low Correlations
The correlations across national markets are lower than the correlations
across securities in most domestic markets.
• Return correlations are moderate.
- Average for developed markets: 0.42.
• Common economic policies matter:
- Average intra-European correlation: .57
- Average intra-Asian correlation: .42
• There is a regional (neighborhood) effect:
- Correlations between the US and Canada is .75.
- Correlations between the US and Japan is .35.
• Emerging Markets tend to have lower correlations.
-Average correlation with Canada: 0.507
-Average correlation with Brazil: 0.375
-Average correlation with Russia: 0.426
-Average correlation with India: 0.431
-Average correlation with China: 0.414
• Empirical fact 2: Correlations are time-varying
Correlations change over time.
General finding: During bad global times, correlations go up
=> when you need diversification, you tend not to have it!
1
0.5
Jan-12
Jan-10
Jan-08
Jan-06
Jan-04
Jan-02
Jan-00
Jan-98
Jan-96
Jan-94
Jan-92
Jan-90
Jan-88
Jan-86
Jan-84
Jan-82
Jan-80
Jan-78
Jan-76
-0.5
Jan-74
0
Jan-72
2-year Rolling Correl
Correlation: USA-Japan
2-yr Rolling Correl
Jan-12
Jan-10
Jan-08
Jan-06
Jan-04
Jan-02
Jan-00
Jan-98
Jan-96
Jan-94
Jan-92
Jan-90
Jan-88
Jan-86
Jan-84
Jan-82
Jan-80
Jan-78
Jan-76
Jan-74
Jan-72
1.2
1
0.8
0.6
0.4
0.2
0
-0.2
Ja
n-9
Ja 0
n-9
Ja 1
n-9
Ja 2
n-9
Ja 3
n-9
Ja 4
n-9
Ja 5
n-9
Ja 6
n-9
Ja 7
n-9
Ja 8
n-9
Ja 9
n-0
Ja 0
n-0
Ja 1
n-0
Ja 2
n-0
Ja 3
n-0
Ja 4
n-0
Ja 5
n-0
Ja 6
n-0
Ja 7
n-0
Ja 8
n-0
Ja 9
n-1
Ja 0
n-1
Ja 1
n-1
2
2-yr Rolling Correl
• Empirical fact 2: Correlations are time-varying
Correlations have increased over the last 10 years.
- Germany and France have become the same asset!
Return Correlation: France and Germany
Return Correlation: Germany and EM
1.0
0.8
0.6
0.4
0.2
0.0
• Empirical fact 2: Correlations are time-varying
It also true at the domestic level. JPMorgan: “Correlation Bubble”
• Empirical fact 2: Correlations are time-varying
A “correlation bubble” is bad news for international (and domestic)
investors: High correlations => more volatile portfolios.
• In addition, higher volatility => higher option premiums (higher
insurance cost!).
• Investors like diversification. They look for low correlated assets:
treasury bonds, commodities (gold, oil, etc.), real estate.
• But, diversification can work with highly correlated assets.
Example: The correlation between the U.S. and Canadian markets is .75.
The RVAR of the U.S. market from 1970-2011 is .15, while the RVAR of
a 50-50 portfolio with Canada is .18.
• Empirical Fact 3: Risk Reduction
Past 12 stocks, the risk in a portfolio levels off, around 27%. For
international stocks, the risk levels off at 12%
• Empirical Fact 4: Returns Increase
Portfolios with international stocks have outperformed domestic
portfolios in the past years. About 1% difference (1978-1993).
Q: Free lunch?
A: In the equity markets: Yes! Higher return (1% more), lower risks (2%
less).
Example:. The U.S. market return and volatility from 1970-2011 were
7.71% and 15.62%, respectively (RVAR=.15). A portfolio with a 25%
weight with Japan would have produced a market return and volatility of
8.32% and 14.53%, respectively. (RVAR=.23).
• Q: How to take advantage of facts 2 and 3?
A: True diversification: invest internationally.
Example: Higher Returns - The Case of Emerging Markets (EM)
Example: Lower Risk/Higher Returns!
Taken from H. Markowitz’s “A Random Walk Down Wall Street.”
Example: Lower Risk/Higher Returns II -The Case of EM
• Empirical Fact 5: Investors do not diversify enough
Latest report by UBS (2002) on the proportion of foreign bonds and
foreign equities in the total equity and bond portfolio of local residents
for several OECD countries:
- Most internationally diversified investors: Netherlands (62%), Japan
(27%) and the U.K. (25%). U.S. ranks at the bottom of list: only 11%.
This empirical fact is called the Home Bias.
Proposed explanations for home bias and low correlations:
(1) Currency risk.
(2) Information costs.
(3) Controls to the free flow of capital.
(4) Country or political risk.
(5) Cognitive bias.
• Why do we have a separate market segment: Emerging Markets?
- Information problem problem is big. It involves financial, product, and
labor markets.
- Distortionary regulation and/or inefficient regulation
- Judicial system not reliable (contracts enforcement a question mark)
• Labor markets
- Problems
- Lack of educational institutions to train people
- No certification and screening
- Labor regulation that limits layoffs
- Solutions
- Groups provide training programs (group specific)
- Internal labor markets
• Why do we have a separate market segment: Emerging Markets?
• Regulation
- Problems
- Too many regulations or unequal enforcement
- Solution
- Intermediation between government and individual
companies. Lobbying & educating politicians.
• Judicial system - Problems
- Contracts not enforceable
- Solution
- International arbitration clauses
- Reputation for honest dealings
Related Question: What should be your international exposure?
- GDP weighted?
Related Question: What should be your international exposure?
- GDP weighted?
- Market capitalization weighted?
Country Analysis
• Active allocation strategy requires the forecast of changes in economic
variables: currencies, interest rates, and stock markets.
Key variable: Choice of a country (currency).
• Q: How do we select a country?
We perform country analysis.
Economists monitor a large number of variables such as:
- real growth (probably, the major influence on a national market.)
- monetary and fiscal policy
- wage and employment rigidities
- social and political situations
• Q: What are the main factors affecting the performance of a national
stock market?
A: Many. But, in general, we find that growing economies have a
growing national stock market.
• Many growing economies have significant risks:
- Information problems (accounting standards, communication culture)
- Government issues (corruption, regulations, inefficiencies.)
- Political environment (state intervention culture)
Emerging Markets
• Where are they emerging from?
- Investing in the developing world is not a new trend. The search for
higher yields has always existed: Colonization of America in 1500s, UK
building and financing railroads in 1800s, MNCs in 1900, etc.
- But trend is accelerating: In 2009, 43% of global FDIs went to EM.
• Very good economic growth:
- Between 1965 and 2010, the EM economies grew 1.8% faster IM
economies.
- In its 2011 World economic outlook, the IMF expects EM to grow at a
6.5% in the 2011-2012 period, while IM are expected to grow at 2.5%.
• Spectacular stock market growth:
- 1983: EM market cap: USD 70 billion. Malaysia had the largest EM
stock market: USD 22.8 billion. Second was Brazil: USD 15.1 billion.
- 2010: EM market cap: USD 16.5 trillion. The Chinese, Brazilian and
Indian stock markets were among the 10 largest markets in the world.
- Growth in trading volume: 1,400 times from the 1980 level.
- High Returns: 1988-2011 annualized USD return of the MSCI EM nd
2011 was 28.5%, which is bigger than the annualized return of 7% for
the S&P 500 Index over the same time period.
• Keep in mind: High returns, high volatility
From 1988 to 2011, the MSCI Latin American Index had an annualized
return of 22.62% and a SD of 31.46%. For the S&P 500, the same
numbers were 8.37% and 14.95%. ¶
• Why this growth in market cap?:
(1) More market-oriented policies in EM .
(2) More economic sectors open to competition and foreign investments
(3) Restructuring of the corporate sector and changes in laws and
regulations, making numerous EM companies more competitive and
responsive to markets and shareholders.
(4) The privatization of state-owned enterprises (SOEs). In the 1990s,
following the UK, many EM adopted wholesale privatization programs.
(5) The re-emergence of state-directed capitalism. In the 2000s, many
EM countries changed management for SOEs: from bureaucrats and
cronies to professional managers. The SOEs act more like a private
companies. SOEs account for 80% of the value of China’s market cap.
SOEs are attractive to international investors: 30% of FDI in 2003-10.
(6) The list of stock markets in the developing countries in which an
international investor might invest is growing. As stock markets are
being created in countries where they had not
Country Risk
Definition: Country Risk
Country risk (CR) represents the risk attached to a borrower/investor by
virtue of its location in a particular country.
Q: Why do we care about CR?
- MNCs make decisions on DFI projects on the basis of NPVs.
- MNCs use discount rates to establish NPV for projects
(the higher the discount rate, the lower the chances of a project to
have a NPV>0).
Q: Where do discount rates come from?
A: For projects abroad, a key element is Country risk (CR)
Note: CR is different than FX risk. CR risk can be zero and FX can be
huge for a given country. The reverse, though unusual, can also happen.
CR reflects the (potentially) negative impact of a country’s economic and
political situation on an MNC’s or an investor’s cash flows.
• Situations that can affect MNC’s Cash flows
- Nationalization of subsidiaries or joint ventures.
- Labor strike in an industry.
- A political scandal that introduces new laws or regulations.
- New trade restrictions, limiting imports or exports.
Q: Does country risk analysis matter?
A: Look at companies investing in Libya in 2011! Value of Libyan assets
went down significantly. Global investors, MNCs, bondholders realize
the relevance of country risk analysis.
• Measures to reduce country risk:
- A cap on the total amount invested in a particular country.
- Diversification.
• Basic Idea
There are many factors that can influence a country’s economic policies:
political, economic, social, etc.
We want to create a global indicator that assesses the likelihood of a
(negative) change in a given country’s economic policy.
This indicator, reported as a single number, is called country risk (CR).
• Similar to credit risk ratings, CR is usually measured (and reported) as
a letter (A=excellent, C=bad) => Letter = Grade
• Credit and Interest Rate Risk for Bonds: Brief Review
Bonds are subject to two types of risk:
1) interest rate risk (risk associated to changes in interest rates)
2) credit/default risk (risk associated to the probability of default
combined with the probability of not receiving principal and interest
in arrears after default)
Credit rating agencies describe (measure) the risk with a credit rating (a
letter grade).
Rule: The higher the grade, the lower the yield of the bond (measured as
a spread over risk-free rate). (For us, the risk-free rate is the yield of
government bonds).
• General Idea
From a big data set (with a lot of economic, socioeconomic and political
variables and observations), we come up with a single measure (a letter).
• Two approaches to measure CR (and get a grade)
(1) Qualitative – collect data, get an opinion from “experts,” form a
“consensus” grade.
(2) Quantitative – collect data, process the data with a computer model,
get a grade.
(1) Qualitative Approach: Talk to experts (politicians, union members,
economists, etc) to form a consensus opinion about the risk of a country.
The consensus opinion becomes the grade.
(2) Quantitative Approach: Start with some quantifiable factors that
affect CR. Use a formula to determine numerical scores for each factor.
Calculate a weighted average of the factors’ numerical scores. This
weighted average determines the final grade.
(1) Qualitative Approach is considered “subjective.”
(2) Quantitative Approach is considered (or seems more) “objective.”
We will emphasize the Quantitative Approach.
• Pros
- It is simple
- It allows cross-country and across time comparison.
• Cons
- It is too simple.
- In practice, ratings tend to converge (herding).
- Not a lot of predictive power.
Note: Ideally, rating companies are independent. But, they have
incentives to accommodate clients (countries).
• Practical use of CR
• We will associate CR to the spread over a base, risk-free rate, say U.S.
T-bills. That is, CR influences the interest on the debt issued by a
government of a country (and the discount rate on foreign projects!).
Example: Setting yields for Mexico (actually, the Mexican government)
Yield on Mexican government debt = US Treasuries + spread (risk
premium, a function of CR)
Mexico’s grade: BBB -a spread of 140 bps (1.40%) over US Treasuries
US Treasuries yield 4%
=> YieldMex = 4% + 1.40% = 5.40%
If we have a project in Mexico, to calculate the discount rate, the
YieldMex becomes the risk-free reference rate. That is,
Discount Rate ProjectMex = YieldMex + project’s risk premium. ¶
 What explains the difference between the yields in Germany and Italy?
Country Risk.
 Risk Rating Method (Check list)
• Weighted average of grades for four major aspects of a country:
- Economic Indicators
(financial condition)
- Debt management
(ability to repay debt)
- Political factors
(political stability)
- Structural factors
(socioeconomic conditions)
The grades (between 0 and 100) for each factor are a function of
“fundamental data.” For example, the economic indicator’s grade
depends on GDP per capita, GDP growth, inflation, interest rates, etc.
A specific formula is used to compute the grades. For example,
Score(EI) = α0 + α1 GDP growth + α2 Inflation + α3 Productivity + ....
Regressions and experience will determine the coefficients (α0, α1, α2,...).
 Risk Rating Method (Check list)
We expect better GDP growth and lower inflation to have a positive and
negative coefficient, respectively.
• The final score –i.e., the CR letter- will be determined by a weighted
average:
Final Score = wEI Score(EI) + wDM Score(DM) + wPF Score(PF) + wSF Score(SF)
Note: The weights should be positive and should up to 1 –i.e., wEI + wDM
+ wPF + wSF = 1.
Q: Where are the weights and the formulae for the grades coming from?
A: This method seems more “objective,” because it is based on hard
economic data, but weights and formula for grades might be
“subjective.” It’s more an art, than a science.
 The model can deliver different forecasts: Short-term, Medium-term,
and Long-term.
=> The weights and grades can change depending on your horizon.
For example:
(a) Short-term: more weight to debt management and political factors.
(b) Long-term: more weight to economic indicators and structural
factor.
 Each grade is associated with a spread in basis points (bps) over base
rate, usually a risk free rate.
• If a country is rated as A, its bond will trade at base rate plus a (80-130)
bps spread.
Note I: A rating of BBB or better is considered “investment grade.”
Note II: A rating of BB or less is considered “junk.” In the U.S., the usual
spread of junk debt is between 400 to 600 bps over 1-yr T-bills. Range is
very wide: Spreads can go over 2600 bps.
Example: Spread on government eurobonds: July 21. 2011.
Higher risk (PIIGS), higher spread! ¶
Example: Bertoni Bank evaluates the country risk of country DX.
Short-term Horizon
Factor
Weight Grade
Economic
.3
80
Debt managt
.3
90
Political
.3
67
Structural
.1
75
Total
Short-term ranking: A
Medium-term ranking: BBB
Medium-term Horizon
Weight Grade
24
27
20.1
7.5
78.6
.3
.2
.2
.3
70
70
50
60
21
14
15
12
63
That is, the short-term debt of country DX will get a spread in the 80-130
bps range, say 93 bps over US Treasuries; while the medium-term debt
will get a higher spread, say 128 bps.
Suppose the short-term US Treasuries yield 4% (s.a.). Then, the shortterm debt of country DX yields 4% (s.a.) + 0.93% (s.a.) = 4.93% (s.a.) ¶
Example: Country Risk in Practice
Euromoney produces semi-annual country risk analysis of 185 countries
using a panel of a experts. Euromoney rates nine categories with a score
(0 to 100).
• Categories and weights:
Economic performance: GDP growth
Political Risk
Debt indicators: Debt/GDP
Debt in default or rescheduled
Credit rating: Moody ’s or S&P’s or Fitch IBCA’s rating
Short-term credit market access
Acces to bank finance: Commercial bank credit
Access to Capital markets
Discount default factor: Spread over US Treasury bills:
- 25% weight
- 25% weight
-10%weight
-10%weight
-10%weight
- 5% weight
- 5% weight
- 5% weight
- 5% weight
Example: Country Risk in Practice
Euromoney’s experts evaluate each category for each country and grade
them from 0 to 100. For example, they look at the category: Debt
Indicator (10% weight) and grade it:
Example: Euromoney, World Country Risk Jan 30, 2012
World Country Risk weighted average: 44.50 (B rating or Tier 4)
Example: World Composite Risk 1986
Example: World Composite Risk 1997
Example: World Composite Risk 2007
Example: Country Risk in Practice
• Euromoney CR ratings
- Congo
2011: 28.89 (World ranking: 139. In 2001, Congo ranked 180th.)
- Romania
2011: 49.09 (World ranking: 72. In 2001, Romania ranked 89th.)
- China
2011: 63.55 (World ranking: 40. In 2001, China ranked 45th.)
- Taiwan
2011: 80.04 (World ranking: 18. In 2001, Taiwan ranked 28th.)
- Singapore
2011: 87.48 (World ranking: 6. In 2001, Singapore ranked 14th.)
• As expected, there is a wide dispersion of CR across countries. Ratings,
however, tend to be persistent over time.
 Other Country Risk Indicators
• Given the lack of predictive power of CR, a single indicator may not be
enough. There are other indexes that may be also signal the true riskiness
of a country –i.e., they can be correlated with the CR.
• Popular indicators
- A.T. Kearny: Globalizaton Index (it measures a country’s global links) A.T. Kearny: FDI confidence index (survey of MNFs indicating the
likelihood of investment in specific markets).
- World Economic Forum: Global competitiveness index (it uses to
indexes to rate growth environment and opportunities).
- Institute for Management Development World Competitiveness index.
- PWC: Opacity Index (it measures the adverse impact of opacity of
capital -the cost of borrowing funds- in different countries).
- Heritage Foundation: Index of economic freedom (absence of
government obstructions).
 Other Country Risk Indicators
• Popular indicators
- Fraser Institute: Index of Economic Freedom
- UNDP: Human Development Index (HDI is a composite index
measuring average achievement in life expectancy, education, and
standard of living).
- Nord Sud Export (NSE) index (market potential assessment for foreign
investor
 Other Country Risk Indicators
• Popular indicators: Summary
In general, we see countries’ rankings moving in a similar range (say,
Japan is between 9 and 28; UK between 2 and 20); but it is not always
the case. The economic freedom rankings of Brazil and China make huge
intervals for these countries, far away from the others.
Country
Euromoney Global’n
(2011)
(2007)
GCI WEF
(2011)
WCI IMD
(2011)
Opacity
(2009)
Economic
Freedom
(2011)
Brazil
41
67
53
44
28
99
China
40
66
26
19
45
138
Japan
25
28
9
26
16
22
UK
17
12
10
20
2
14
USA
15
7
5
1
6
10
Interesting Research in International
Equity Markets
• What Factors Move International Equities?
• Do MNCs Provide International Diversification Benefits?
• International Capital Market Integration
• Linkages between International Equity Markets
- The Crash of October 1987
- U.S. Market Effects
- Big Price Changes, Big Correlations
International Factors in Stock
Returns
 Q: What kind of factors explain security returns?
(1) International
(2) Domestic
(3) Industrial
Domestic vs. International Factors
• We want to determine the relative importance of factors.
A: Separately correlate each individual stock with:
i. the world sock index
(international factor)
ii. the appropriate industrial sector index
(international factor)
iii.the currency movement
(international factor)
iv. the appropriate national market index
(domestic factor)
Example: We regress each individual stock against each factor and obtain its R2.
Average R2 of Regression on Factors
Single-Factor Model
All Factors
Market
World Indust Curren Domestic
Belgium
.07
.08
.00
.42
.43
Germany
.08
.10
.00
.41
.42
Norway
.17
.28
.00
.84
.85
Spain
.22
.03
.00
.45
.45
Sweden
.19
.06
.01
.42
.43
France
.13
.08
.01
.45
.60
Italy
.05
.03
.00
.35
.35
Netherlands
.12
.07
.01
.34
.31
U.K.
.20
.17
.01
.53
.55
U.S.
.26
.47
.01
.35
.55
Canada
.27
.24
.07
.45
.48
Australia
.24
.26
.01
.72
.72
Hong Kong
.06
.25
.17
.79
.81
Japan
.09
.16
.01
.26
.33
Singapore
.16
.15
.02
.32
.33
All
.18
.23
.01
.42
.46
=> Domestic factors are the most important.
Currency factor almost negligible (hedging adds value?)
Example: Decomposition of variance for different assets, as a function of World,
Market and idiosyncratic factors. Cipriani and Kaminsky (2007)
Valuation of MNCs
• The extent of foreign operations for many MNCs raises the question:
Can a portfolio of MNC stocks achieve true international diversification?
A: No!
 MNCs do not provide all the benefits available from direct
investment in foreign securities.
Example: We examined firms from nine countries.
ri = αi + ßUS rUS + ßNL rNL + ßBEL rBEL + ßGER rGER + ...
Nationality
of MNC
US
GER
Amer. MNF
German MNF
French MNF
Swiss MNF
British MNF
FRA
.94
.24
-.10
-.12
-.10
SWI
-.01
1.18
.18
-.09
-.09
Multiple
Index
UK R2
.02 -.01
.10 -.15
.95 -.22
-.11 1.74
-.09 .07
Single
Index
beta
-.07
-.11
.03
.16
.84
R2
.31
.74
.62
.75
.49
1.02
1.18
1.08
1.39
1.06
.29
.65
.45
.52
.44
Conclusion: MNC stock prices are more affected by domestic factors. ¶
Possible explanations:
- National control
- Management policy
- Government constraints
International Capital Market
Integration
• Integration and The Pricing of Assets
Capital Market Integration: Assets in different currencies or countries
display the same risk-adjusted expected returns.
Segmentation: The risk-return relationship in each national market is
primarily determined by domestic factors.
• Tests for integration:
(1)
Direct: measure barriers to capital movements. (Be careful with
loopholes).
(2)
Indirect: measure stock prices and compare them. (A better
measure).
Q: Why do we care about International Capital Market Integration?
A: (1) Choice of raising capital in two countries.
(2) If segmentation, international portfolios should display
superior risk-adjusted performance.
Country Funds
• Close-end funds (CEF) differ from open-end mutual funds: They
neither issue nor redeem shares after IPO. To buy or sell shares, you
have to go to the market.
• Each CEF provides two market-determined prices:
- The country fund's share price (P) quoted on the domestic market.
- Its NAV determined by prices of the underlying shares traded on the
foreign market.
If P < NAV,  closed-end fund sells at a discount.
If P > NAV,  closed-end fund sells at a premium.
• CEF Puzzle: Domestic closed-end funds, on average, sold at a
substantial discount during the 70's and early '80s.
• Country CEF: Investment company that invests in a portfolio of assets
in a foreign country and issues a fixed number of shares domestically.
=> Restrictions will raise P relative to its NAV by approximately the
amount the marginal domestic investor is willing to pay to avoid them
Example: On January 13, 1989:
The Korea Fund's share sold at a 65% premium.
The Brazil Fund sold at a 35% discount. ¶
• Restricted countries like Korea, Thailand and Taiwan sell at a
premium. Less restricted countries like Germany and U.K. sell at a
discount.
Statistics for Premiums for Closed-End Country Funds (1981-1989)
Fund or Portfolio
Brazil
Mexico
France
Germany
U.K.
Japan
Korea
Malaysia
Taiwan
Thai
Country Funds
Domestic Funds
Mean
-28.82
-13.78
-20.18
-4.32
-21.37
-11.73
44.35
-7.46
40.96
25.46
-4.54
-11.22
SD
9.64
33.72
8.41
5.90
6.74
10.50
20.86
19.75
36.24
12.45
11.88
5.58
ρ1
.92
.97
.92
.77
.72
.96
.93
.97
.96
.93
.89
.97
Example: The announcement of changes in investment restrictions
decreased country fund premiums by an average of 6.8% in recent years.
=> Evidence favors International Market Segmentation: Financial
restrictions to foreign investment work.
Linkages between Stock Markets
• The moderate to low correlation coefficients are a good argument
internationally diversifying portfolios.
• The analysis of correlation coefficients might not be that a correct tool.
Example: Situation:
No movement of capital is allowed between national stock markets.
Common monetary policies induce positive correlations.
In such a case, ex ante, or expected, returns could be very different
across markets, even with highly correlated ex post returns. ¶
The Crash of October 1987
• Q: Why the October 1987 Crash is important?
A: Only month during the 1980's where all the stock markets around the
world moved in the same direction.
• Q: How did the Crash start?
A: The crash started in non-Japanese Asian countries and continued
through European markets, the U.S. and finally Japan.
The following Table reproduces the daily returns during the Pre-Crash
Period, the Crash Period and the Post-Crash Period by Country
Daily Returns (percent/day) by Country
Country
Australia
Hong Kong
Japan
Malaysia
N. Zealand
Singapore
Austria
Belgium
France
Germany
Italy
Netherlands
Spain
Sweden
Switzerland
U.K.
Canada
Mexico
U.S.
1/2/87-10/12/87
.2239 (0.850)
.2218 (1.121)
.1543 (1.274)
.2821 (1.171)
.0291 (1.091)
.2508 (1.075)
-.0202 (0.736)
.0808 (0.814)
.0114
(0.920)
-.0296 (1.251)
-.0338 (1.017)
.0672 (0.993)
.2143 (1.276)
.1272 (1.009)
.0156 (0.917)
.1852 (0.865)
.1143
(0.689)
.9831 (2.509)
.1213 (0.965)
10/12/87-10/30/87
-3.5160
(8.315)
-5.4174
(12.072)
-0.9777
(5.567)
-3.6080
(6.026)
-2.0473
(5.296)
-3.9675
(10.182)
-0.8255
(1.663)
-1.6531
(4.316)
-1.6526
(4.568)
-1.5913
(4.178)
-1.3943
(3.184)
-1.5985
(5.296)
-2.4154
(3.286)
-1.8998
(4.534)
-2.0706
(5.409)
-2.0759
(4.947)
-1.5150
(5.413)
-3.4050
(6.892)
-1.4128
(7.253)
11/2/87-3/31/89
.0475 (1.216)
.1083 (1.353)
.0810 (0.946)
.0128 (2.754)
-.0755 (1.366)
.1004 (1.327)
.0699 (0.557)
.0906 (0.965)
.1018 (1.254)
.0254 (1.292)
.0293 (1.149)
.0633 (1.301)
.0555 (0.927)
.1202 (1.242)
.0025 (1.305)
.0524 (0.962)
.0405 (0.772)
.0128 (2.754)
.0428 (1.094)
Portfolio insurance and computer systems?
Journalist and politicians blamed the Crash on a variety of source
ranging from portfolio insurance to inadequate computer systems.
• Finding: Claims totally unfounded. Many studies have found that
countries with portfolio insurance crashed less that countries without it.
Futures markets?
The argument seems to be that irrational speculators cause instability.
• Finding: Stock markets with related futures markets crashed in the
same way as countries without futures exchanges.
Specific event?
Search for a triggering event:
(1) announcement on October 14 of a worse than expected trade balance.
(2) poor performance of Asian markets in the week before the Crash.
(3) introduction in the U.S. Congress of anti-takeover legislation.
• Finding: Last event is the most persuasive; however, it is difficult to
believe that it had such a extraordinary effect in other markets.
Speculative bubble?
Eugene Fama, from the University of Chicago, says that the most
questionable aspect of 1987 was not the Crash itself, but the incredible
market advance during the previous five years.
This apparent behavior has been attributed to a speculative bubble.
Under this view, the most plausible theory for the Crash is that a
speculative bubble burst in October 1987.
It is difficult to test this hypothesis. Tests are usually based on
autocorrelations.
• Finding: Several studies have dismissed it as a plausible explanation
for the October 1987 Crash.
• Q: Can a Crash be avoided?
• The immediate consequence of the Crash was a couple of reports by
official agencies with recommendations.
The proposed measures include:
1. increase in margin requirements
2. imposition of price limits
3. differential taxing for short and long positions
• Finding: There is no evidence that margin requirements or price limits
have any impact on stock price volatility.
• Summary:
- The Crash was an international event.
- Countries with different regulations, controls, taxes and trading
system.
- All experienced a significant negative shock on October 1987.
U.S. opening effect
Use of daily data has a problem: overlapping trading hours.
Difficult for some markets to distinguish:
Common movement (caused by world factors)
Specific movement (caused by domestic factors)
Example: A positive commovement between NY and London (they
share 2:30 hours of trading) might reflect common information or the
influence of one specific market in the other.
• Finding using intradaily data between NY and London: They only
affect each other around the time New York is opening (9:30 AM, EST).
Big movements, higher correlations
When price changes are big, transaction costs become relatively
unimportant. Transaction costs are a barrier for instantaneous arbitrage.
Big price changes will bring world markets together.
• Finding: Cross-market correlations tend to be positively correlated
with measures of price volatility.
Application: High Volatility, Correlations and Portfolio Choice
• The lower the correlation between the assets, the greater are the
benefits due to diversification.
Empirical Fact: Recall the “Home bias."
• Changes in correlations will affect the composition of optimal
portfolios.
• For the U.S. investor, the benefits of diversification change depending
on the state of the volatility structure.
=> When you really want diversification (high domestic volatility), the
benefits are lower (high overseas volatility).
In Table X.7, the correlations between the U.S. and other major markets
are calculated for two U.S. regimes: high volatility and low volatility.