group b9_co-movement of various global stockmarket indices couses and implications

7/28/2019 Group B9_Co-Movement of Various Global Stockmarket Indices Couses and Implications

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Co-Movement of Global

Capital Markets

Group No: 9, Section B

Ankit Mangla 11P123

Dipesh Kaien 11P134

Prakash Kumar 11P154

Varun Garg 11P179

Vishal Gupta 11P180


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ContentsCO-MOVEMENT OF GLOBAL CAPITAL MARKETS .......................................................................... 2

Introduction.............................................................................................................................................. 2

Definition.............................................................................................................................................. 3

Motivation ............................................................................................................................................ 3

Global Stock Market Integration and the factors affecting Co-movements............................................. 4

Bilateral Trade relationships ................................................................................................................. 7

Macro-economic factors & Financial markets Integration ................................................................... 8

Other Factors ........................................................................................................................................ 9

Implications ........................................................................................................................................... 10

Research Methodology ............................................................................................................................... 12

Index Description.................................................................................................................................. 13Results ......................................................................................................................................................... 15

Analysis of results obtained ........................................................................................................................ 16

Additional Research .................................................................................................................................... 18

References ................................................................................................................................................ 20


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CO-MOVEMENT OF GLOBAL CAPITAL MARKETS

Introduction

In this world of globalization, companies and individuals are more and more affected by

what is happening in the world as compared to earlier times. Companies operate in tens

of countries and sell products around the globe. Liberalizations of capital flows and

financial innovations supported by the improvements in information and communication

technologies enabled such rapid international growth of businesses.

In this article, we will talk about the co-movements of the global capital markets. We

often see that any event happening in any country affects the markets in that country

immediately. But most of the times, depending upon the event, we see the cascading

effects on other major markets of the world. Sometimes the impact is huge which the

whole world notices while in other cases, it is minor and goes without attracting much

public attention.

The most recent financial crisis of 2008-09 during which nearly all world stock markets

experienced severe downturns, may fill us with feeling that there is just one big

integrated marketplace. However, to assess the actual degree of co-movements

between the international stock markets empirical investigation over longer period on a

day to day basis is necessary.

Knowing the inter dependence on different markets can help the community in different

ways:

Advantage of international diversification of portfolio

Development in other markets and its influence on value of stocks in our industry

Correlation patterns between the national stock markets and their implications for

the stability of the financial system


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Definition

1. Co-movement

Refers to the tendency of two or more stock markets to move simultaneously

together, so their price movements are positively correlated

2. Spillover

Effects of an activity which have spread further than were originally intended or any

type of impact on other countries financial markets

3. Contagion

It refers to the significant increase in cross market linkages during crisis

Motivation

Earlier the only motivation to study co-movements of markets was for portfolio

construction purposes. But crisis that have happened at different points in history could

not be explained by contemporary knowledge and theories. Some examples are:

Crash of 1987: Began in Hong Kong, spread throughout Europe and finally hit

US. The stock markets around the world (e.g. Australia, New Zealand, Spain,

United Kingdom, Germany, Japan and Canada) fell by tens of per cent by the

end of October

Asian crisis of 1997: Started in Thailand as a currency crisis. Spread to East Asia

and Russia and subsequently to Brazil.

Events like these forced the world to turn their attention towards possible reasons for

the spread of such crisis form their host country to other parts of the world. The issue of

ripple co-movement among stock markets has become an important substance in the

modern finance. The degree of linkages, co-movements or interdependencies among

the stock markets provides important implications on potential benefits of international

portfolio diversification and on financial stability of a country. The emerging markets are

also found to be more closely integrated with markets in the rest of the world, although

their integration progress has been far less than the industrial countries. This further


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implies that the potentialities of portfolio diversification benefits across the world stock

markets in the long run tend to diminish. In addition, an escalating integration among

the national stock markets further implies that international financial instabilities are

easily transmitted to domestic financial markets, a phenomenon called as financial

contagion.

Global Stock Market Integration and the factors affecting Co-movements

The movement towards a synchronized stock market landscape has gained momentum

during the past two decades, where tighter economical and financial linkages among

developed economies have grown stronger. However, the rises of many important

emerging markets, which have been a major driver of global growth the past decades,have opened up additional sources for cross-border relations. Other causes behind the

rapid increase in world trade, capital movements, and foreign investments between

world economies are due to market liberalization/deregulation, technological advances

and removals of statutory controls. Many of these factors have contributed to more

interlinked economies, which in turn, are said to have given rise to a higher degree of

stock market synchronization, especially in volatile time periods, e.g. eruption of a

financial crisis, war, or political instability (Mobarek,2011). The impact of 2008 financial

crisis, have opened up a tremendous interest for determining the underlying factors that

might explain how stock markets are correlated with one and other for better

understanding their causes. To investigate the intensity of one country to be affected by

global shocks have enormous value for preventing future crises. The extent of financial

and economical integration between a country-pair may indeed be reflected by the

degree of stock markets co-movement that they exhibit. In fact, the macro-economic

structures of international economies have clearly intensified the complexity behind

stock market performances. As countries become more economically interlinked,

explaining the formation of price co-movement between stock markets on an

international level is significant for better understanding this higher interdependency and

integration. However, the contemporary research in stock market integration has not

sufficiently focused on determining the driving forces behind co-movement although this


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information would be most effective for policy-makers and investors that are keen to

know how economic linkages may influence the countries financial stability,

diversification possibilities and what types of common and specific shocks stock

markets are most vulnerable against (Mobarek,2011).

Greater degree of co-movements in stock prices is seen as a reflection of greater stock

market integration. Research till date indicate that a reasonably clear time trend is

identified, where the extent of contemporaneous co-movement across markets has

intensified over time, especially for emerging countries, which consequently suggests

that greater market efficiency is being fostered at the international level. There are also

evidences that some markets are more likely to lead other markets. These alterations

might be due to possible changes in a countrys economy and market conditions, but

also the stability of global markets. Nevertheless, the highly sophisticated market of the

US and the emerging markets of Brazil and Russia appear to affect other rather than be

affected. Some of the research works focused on trying to identifying the

explanatory variables affecting the stock market co-movements include import

dependence, stock markets size differential and their relative size, difference in

annual GDP growth rate as well as the time trend (Mobarek,2011).

A few research works conclude that the degree of interdependence among the Asian-

Pacific markets increased substantially after the 1987 & 1997 stock market crash and

where the U.S market possesses an influential role affecting these markets. In addition,

the risk reduction benefits of international portfolio diversification have been reduced

due to the higher interdependence that has been observed in these markets. However,

Longin & Solnik (1995) examined the correlation for seven major European countries

over the period 1960-90 indicating that not only is the international covariance and

correlation matrices unstable over time, but that correlation rises in periods when the

conditional volatility of markets is large. Karolyi & Stulz (1996) explores the co-

movements between the Japanese and U.S stock markets from 1988-1999, showing

that correlation and covariance are high when markets move a lot, hence demonstrating

the shortcomings of international diversification in times of high volatility which is when it


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is most needed. In light of the benefits of international portfolio diversification ( Solnik,

1995), there is a range of studies that deals with emerging stock markets, which are

said to have lower exposure to world factors, thus having lower levels of integration and

therefore may offer greater opportunities for risk diversification across countries.

Moreover, Ampomah (2008) presents evidence that African stock markets are still

segmented from global markets offering strong diversification benefits. Another type of

studies has provided evidence on which markets dictates over other markets. An early

study by Eun & Shim (1989) highlights the influence and power that the U.S stock

market has on the stock markets of eight other developed countries. Findings

indicate that a substantial amount of interdependence exists, where the U.S stock

market represents the most influential world economy having by far a dominant position

when it comes to producing valuable information that affects world stock markets.

Empirically they found that innovations in the US stock market were rapidly transmitted

to the rest of the world, whereas innovations in other markets did not have much effect

on the US market. Thus US market domination in co-movements of other markets is

obvious.

A very few studies evidence on the determinants of stock market co-movement

has been presented by Pretorius (2002), which examined ten emerging stock

markets for the period 19952000 by employing a cross-section and a time-series

model. The major findings showed that only bilateral trade and the industrial

production growth differential were significant for explaining the correlation

between two countries on a cross-sectional basis. Similar results were achieved by

the time-series regression. They conclude that the higher levels of market co-movement

during the observed periods are mostly due to interdependence, which depend on the

linkages that economies have with each other. Results show that trade and financial

integration contributes positively to stock market synchronization, while a fixed

exchange rate regime increases co-movements. Other factors such as the

similarity of economic structure across countries, informational asymmetries and

a common language also contribute to stock market synchronization. Morgado &

Tavares (2007) examined the impact of bilateral indicators of economic integration on


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the correlation of stock return of 40 developed and emerging markets for the period

19701990. Results showed that bilateral trade intensity affects the correlation

positively, whereas the asymmetry of output growth, the dissimilarity of export structure

and the real exchange rate volatility have negative effects on stock return correlation. A

few research results indicate that the degree of international integration (measured as

the magnitude of the correlation structure) is positively associated with (1) world market

volatility and (2) trend; while it is negatively related to (3) exchange rate volatility, (4)

term structure differential across markets, (5) real interest rate differential. A few main

empirical results from these studies show that (Bracker et al., 1999) Several

macroeconomic factors are significantly associated with the extent of stock market

integration over time, e.g. trade, geographic distance, the nature and extent of the

bilateral trade relationships, GDP Annual growth rate differential, stock market size

differential, time trend, and real interest differential (Johnson & Soenen, 2002).

Asian stock markets became more integrated with the Japanese stock market over

time, especially since 1994, where increased export share from Asian economies to

Japan and greater foreign direct investment from Japan to other Asian economies

contributes to greater co-movement; (Johnson & Soenen, 2003) indicating that a high

share of trade with the US has a strong positive effect on stock market co-movements

for equity markets of the America, whereas increased bilateral exchange rate volatility

and a higher ratio of stock market capitalization relative to the US contribute to lower co-

movement.

In nutshell following are some of the factors which have been focused upon till date in

the research works considered as the driving forces behind the co-movement of the

stock markets:

Bilateral Trade relationships

The importance of the bilateral trade relationships lies in the relative size of the export of

a country with the other country relative to its total export size in value. Similarly the size


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of the import relative to its total import affects the co-movement of the market index. The

higher export or import dependence on any country will impact the co-movements. If

there is any severe impact affecting the bilateral trade relationships, this will reflect in

the relative returns of the stock-markets. Although the contribution of international trade

in goods is usually recognized as increasing the extent of business cycle

synchronization, its overall effects on co-movements of stock index remain ambiguous

(Walti, 2005). On the demand side, higher aggregate demand in one country will

partially fall on imported goods, thereby raising output and income in trading partners

economies and inducing output co-movements across countries. On the supply side,

however, there are two opposite effects which relate to two different approaches to

modeling international trade. Intra-industry models of trade emphasize economies with

similar production structures and factors. To the extent that trade occurs mostly within

industries, an expansion in some industries will raise output co-movements across

countries. However, trade integration may also lead economies to specialize in the

production of goods for which they have a comparative advantage, hence reducing co-

movements. The net impact of international trade on co-movements is therefore

ambiguous.

Macro-economic factors & Financial markets Integration

The macroeconomic factors include, inflation rate differential, real interest rate

differential and GDP annual growth rate differential, are expected to be negatively

related to the co-movements in a stock markets pair. Indeed, the larger these

differences become, the larger the divergence between the economy linkages of the two

countries and hence the less their stock markets will be influenced by each other (Walti,

2005). The degree of other financial market integration such as money market, debt

market, foreign exchange, credit markets also affects the correlation of the equitymarkets. However, the exact trend of their specific correlation is not clear due to the

complexities involved in the linkages among these markets themselves.


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The nature of the exchange rate regime is likely to have implications for the degree of

covariation between national economies. The argument in favour of floating exchange

rates is that they act as a shock absorber for external disturbances. A greater flexibility

of the exchange rate should therefore reduce the effects coming from the transmission

of country-specific real shocks, thereby delivering lower output co-movements across

countries. Similarly, provided that capital flow mobility is high, maintaining a fixed

exchange rate requires a high degree of coordination of monetary policies, thereby

inducing greater co-movements in economic conditions and consequently greater co-

movement among the index. In the extreme case of a currency union like EU, the

stance of monetary policy would in fact be identical for all participating countries.

Other Factors

The other group of variables affecting the co-movement of the index includes indicators

of the stage of stock markets development, such as stock markets size differential and

relative size. More specifically, the stock market capitalization of a country may be a

measure of the ease or difficulty, in terms of liquidity and costs, of trading on that stock

market. While a large difference in market size for a pair of countries may determine

less co-movements between their respective stock markets, the relative size of the two

markets in the pair have opposite effects.

Lastly, a time trend has been identified in a few research works including the possibility

that stock market inter-dependence has increased over time, due to the advanced

communications technology, the eased flow of information, trade and capital across

borders and the increasing cross-listing of stocks and mergers between stock markets

of different countries (Forbes & Rigobon, 2002).


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Implications

In an era of mounting Liberalization, Privatization and globalization in the emerging

economies, the transmission of movements in international financial markets and assets

are important issues for cross border investments, especially in periods where marketsare highly volatile. The determination of diversification strategies by an international

investor also depends crucially on the nature and magnitude of the relationships (co-

movement) existing between different stock markets especially emerging markets. Thus

it becomes important for international investors to understand the co-movement and

interdependence among the various markets to diversify their portfolio risks and to

derive high return.

Most of the studies on the international capital market are based on the segmented

market approach. According to it, different national capital markets act as separated

entities, hardly related to each other. If this is true, comparable capital assets may differ

in their on different national markets.

Alternately, another theory says that prices of capital assets in the international capital

markets behave as if there is one multinational perfect capital market. According to it,

returns of comparable capital assets must not be substantially different in different

national capital markets.

Thus we see that how markets co-move has significant impact on the returns that

different capital assets may provide. The results of this study have important

implications for the benefits of international portfolio diversification strategies and the

convergence of the cost of capital across countries. Changes in co-movement across

world markets has important implications for the degree of diversification that can be

achieved by including international stocks in portfolios and for the cost-of-capital for

firms seeking to lower their cost of capital by issuing securities in different world

markets.

Knowledge about the co-movement of capital markets can permit verification of the

simultaneous occurrence of booms or crashes in two markets, and the intensity of the

effect. For portfolio managers to carry out their international asset allocation strategies,


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it is important for them to assess the probability of the occurrence of extreme events

with negative repercussion in the markets under consideration

The knowledge about co-movement can also help the investors who believe that the

twenty-first century may well be the time when the balance of power shifts to Brazil,

Russia, India and China, nations collectively referred to as BRICs economies. Foreign

Investors are investing considerably in the emerging economies with mainly two

objectives:

To enhance the portfolio growth

To reduce portfolio risk through efficient international portfolio diversification


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Research Methodology

1. Literature review was done for reasons of co-movement between various stock

indices the reason for that and implications.

2. 9 indexes were selected, which represented countries across the globe.

Countries covered different continents, Developed and developing countries,

some different indices with in the countries

3. Index closing data for these 9 index was collected for past 11 years (2000-11)

4. Data was adjusted for holiday, we considered all the weekdays falling during the

study period

5. Where data was missing for individual indexes we considered last day closing

index level

6. Day wise return was calculated for selected index for the study period considered

7. Pair wise correlation and covariance matrix was constructed for these 9 indexes

for the return data found in previous step

8. The result obtained was analyzed in light of literature review and macroeconomicconditions

Following indices were considered which are described in report also

NIFTY S&P CNX

CAC Index

Nikkei 225

NASDAQ

Brazil Bovespa Index

S&P500 Russell 2000 Index

FTSE Index

DAX Index

The index description is given in the below


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Index Description

Index Representing

Number

of Stocks

Weighting

of Index

Special

CharacteristicsDrawbacks/Comments

Dow Jones

Industrial

Average

U.S. blue chip

companies30

Price-

weighted

The oldest and

most widely

followed U.S.

equity index

30 stocks chosen by

Wall Street Journal

editors; large, mature

blue chip companies

NikkeiStock

Average

Japanese bluechip

companies

225Modifiedprice-

weighted

Originally

formulated by

Dow Jones &Company, using

essentially the

same method as

the DJIA

Also known as the

Nikkei 225. There is a

huge variation in

share price levels of

the componentcompanies, and some

high-priced shares are

weighted at a fraction

of their share price.

Some component

stocks are illiquid.

S&P TSX

Composite

Broad market

cap stocks

listed on the

Toronto Stock

Exchange

VariesFloat-

weighted

Very

comprehensive

index

Widely used Canadian

equities benchmark

CAC 40

French blue

chip

companies

40Float-

weighted

Chosen from the

100 largest

market cap

stocks on the

Paris Bourse

(Euronext Paris)

DAX 30

German blue

chip

companies

30Float-

weighted

Published by the

Frankfurt Stock

Exchange

Widely used German

equities benchmark

FTSE 100

The 100

largest

publicly

traded stocks

on the London

Stock

Exchange

100Float-

weighted

A large-cap

index,

pronounced

Footsie 100

There are also a FTSE

Mid 250 for mid-cap

stocks and a small-cap

index.


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Russell2000

The smallest

2,000 stocksin the Russell

3000

2,000 on the

day the new

composition

is

determined

Float-weighted

"A small-capindex"

The many U.S. small-

cap index funds

tracking this index and

the consequent

annual reconstitution

costs and possible tax

consequences make

this a relatively high-

cost benchmark

for a U.S. small-cap

index fund.

S&P 500

Predominantly

large-cap

companiesrepresentative

of the U.S.

stock market

500 Float-weighted

Membership

determined by acommittee of

S&P employees

Its popularity with

indexers

causes new

components to earnaverage positive

abnormal returns on

the announcement

that they are joining

the index

(Lynch, 1997) and Malkiel and Radisich (2001)


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Results

Covariance Matrix

Covariance

matrix

NIFTY S&P

CNX

CAC

Index

Nikkei

225

NASDA

Q

Brazil

Bovespa

Index

S&P500

Russell

2000

Index

FTSE

Index

DAX

Index

NIFTY S&P

CNX0.00027 0.00008 0.00008 0.00005 0.00007 0.00004 0.00005 0.00007 0.00007

CAC Index 0.00008 0.00025 0.00007 0.00014 0.00014 0.00012 0.00013 0.00018 0.00022

Nikkei 225 0.00008 0.00007 0.00024 0.00003 0.00005 0.00002 0.00003 0.00006 0.00006

NASDAQ 0.00005 0.00014 0.00003 0.00033 0.00020 0.00022 0.00027 0.00010 0.00016

Brazil

BovespaIndex

0.00007 0.00014 0.00005 0.00020 0.00036 0.00016 0.00019 0.00011 0.00014

S&P500 0.00004 0.00012 0.00002 0.00022 0.00016 0.00019 0.00021 0.00009 0.00013

Russell 2000

Index0.00005 0.00013 0.00003 0.00027 0.00019 0.00021 0.00028 0.00010 0.00014

FTSE Index 0.00007 0.00018 0.00006 0.00010 0.00011 0.00009 0.00010 0.00017 0.00016

DAX Index 0.00007 0.00022 0.00006 0.00016 0.00014 0.00013 0.00014 0.00016 0.00026

Correlationmatrix

NIFTY S&PCNX

CACIndex

Nikkei 225

NASDAQ

BrazilBovespa

Index

S&P500

Russ

ell

2000

Inde

x

FTSEIndex

DAX Index

NIFTY S&P CNX 1.00 0.30 0.32 0.17 0.23 0.19 0.19 0.31 0.28

CAC Index 0.30 1.00 0.29 0.48 0.46 0.56 0.50 0.89 0.87

Nikkei 225 0.32 0.29 1.00 0.11 0.17 0.12 0.10 0.30 0.26

NASDAQ 0.17 0.48 0.11 1.00 0.57 0.88 0.88 0.44 0.53

Brazil

Bovespa

Index

0.23 0.46 0.17 0.57 1.00 0.62 0.59 0.47 0.47

S&P500 0.19 0.56 0.12 0.88 0.62 1.00 0.90 0.53 0.60

Russell 2000

Index0.19 0.50 0.10 0.88 0.59 0.90 1.00 0.47 0.53

FTSE Index 0.31 0.89 0.30 0.44 0.47 0.53 0.47 1.00 0.79

DAX Index 0.28 0.87 0.26 0.53 0.47 0.60 0.53 0.79 1.00


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Analysis of results obtained

We have taken 9 indices covering various countries namely India, USA, Germany, UK,

Brazil. Japan and France. Based on the correlation matrix above, we can conclude to

certain extent the reasons and justifications of co-movements of various markets. There

may be various reasons for two markets two co-move and the extent of co-movement.

Nifty (India) does not have a substantially high value of co-relation with any of the

indices. The highest is in range of 0.3-0.32 for France, Japan and UK. This can be

attributed to the fact that India is a developing country and most of the indices in the

table are of developed countries (with the exception of Brazil).

CAC Index (France) is highly co-related and co-moves with the indices of other

European countries like UK (0.89) and Germany (0.87). It may be due to similar

levels of development of economies. Also their geographical proximity results in any

effect in any market to quickly reach the neighboring markets.

CAC is also co-related to US indices (NASDAQ- 0.48, Russell-0.45 and S&P-0.56)due to significant financial market integration such as money market, credit market,

debt and bond market. Since both the US and EU are developed, so we expect

some co-movement among indices of these countries.

Similar characteristics are also shown by other European indices.


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Nikkei (Japan) has highest value of co-relation with Nifty. This may be because of

the fact that both the countries are part of Asian sub continent and thus geographical

location is an important factor. It is also co-related to a similar extent to European

indices. However, it has very low value of co-relation with US indices.

US indices have high co-relation with indices within the country and Brazil (due to

geographical factors). It is also significantly co-related to European indices as both

US and Europe are developed economies and thus markets tend to co-move.

Brazilian index tends to have high co-relation with US indices due to location factors.

Next it has high co-relation values with European indices due to information

integration.


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Additional Research

Efficient Portfolio using Index Funds

An efficient portfolio is one that lies on the efficient frontier.

An efficient portfolio provides the lowest level of risk possible for a given level of

expected return. If a portfolio is efficient, then it is not possible to construct a portfolio

with the same, or a better level, of expected return and a lower volatility.

An efficient portfolio also provides the best returns achievable for a given level of risk. If

a portfolio is efficient it is not possible to construct a portfolio with a higher expected

return and the same or a lower level of volatility with the securities available in the

market, excluding risk free assets. Adding the latter allows one to construct portfolios

that lie on the securities market line.

(moneyterms.co.uk)

We constructed a sample efficient portfolio using Jan 2000 to Mar 2000 data.

Imitations to considering such a short horizon .a short portfolio is constructed due to the

hardware constraint as the hardware that we have was not able to process 10 years f

data


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-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0 0.5 1 1.5 2 2.5

Return(%)

Systematic Risk (Standard Deviation)

Efficient Frontier and Capital Market Line

Efficient Portfolio of Index Funds using Markowitz Optimizer


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References

Douglas W. Blackburn, N. K. Chidambaran (2011) , Is world stock market

comovement changing?

Tamir Agmon, The Relations among Equity Markets: A study of share price co-movements in The Unites States, United Kingdom, Germany and Japan, The

Journal of Finance

Ashwin G. Modi, Bhavesh K. Patel, Nikunj R. Patel, The Study on Co-Movement of

Selected Stock Markets ,International Research Journal of Finance and Economics -

Issue 47 (2010)

Longin, F., Solnik, B. (1995), Is the correlation in international equity returns

constant: 1960-1990?. Journal of International Money and Finance, 14(1), 3-26

Karolyi, G.A., Stulz, R.M., (1996), Why Do Markets Move Together? An Investigation

of U.S.-Japan Stock Return Comovements. The Journal of Finance, 51(3), 951-986. Ampomah, S.A., (2008), An empirical examination of the inter-linkages between

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The Journal of Financial and Quantitative Analysis, 24(2), 241-256.

Pretorious, E. (2002), Economic determinants of emerging Stock Market

Interdependence. Emerging Markets Review, 3, 84-105.

Wlti, S,. (2005) The macroeconomic determinants of stock market synchronization.

Department of Economics, Trinity College Dublin, Dublin 2, Ireland

Forbes, K.J., Rigobon, R., (2002), No contagion, only interdependence: Measuring

stock market comovements, The Journal of Finance, 57(5), 2223-2261

Morgado, P., Tavares, J., (2007), Economic Integration and the Co-Movement of

Stock Returns. CEPR Discussion Paper No. DP6519.

Bracker, K., Docking, D.S., Koch, P.D., (1999), Economic determinants of evolution

in international stock market integration. Journal of Empirical Finance, 6, 1-27.

Johnson, R., Soenen, L., (2009), Equity market risk premium and global integration,

Journal of Centrum Cathedra, 2, 12-22

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100

group b9_co-movement of various global stockmarket indices couses and implications

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