Impact of the 2007 US financialcrisis on the emerging equity

marketsM. Shabri Abd Majid and Salina Hj Kassim

Department of Economics, Kulliyyah of Economics and Management Sciences,International Islamic University Malaysia, Kuala Lumpur, Malaysia

Abstract

Purpose – The purpose of this paper is to explore empirically the effects of the current financial crisison the integration and co-movements of selected stock markets of the emerging economies, namelyIndonesia and Malaysia.

Design/methodology/approach – The paper employs the standard time series technique andvector autoregressive framework.

Findings – The results of this paper support the general view that stock markets tend to showgreater degree of integration or increased co-movements during the crisis period, resulting in lesserbenefit of diversification that can be gained by investors participating in these markets.

Research limitations/implications – This paper only focuses on emerging equity markets ofMalaysia and Indonesia.

Practical implications – This paper reveals that unlike during the pre-crisis period, the long-rundiversification benefits that can be earned by investors across the emerging equity markets ofIndonesia and Malaysia during the crisis period tend to diminish.

Originality/value – By dividing the study periods into the pre-crisis period and during the crisisperiod, it enables us to explore whether the cross-market linkages between these markets change dueto the crisis.

Keywords Indonesia, Malaysia, Equity capital, Stock markets, Recession, Globalization

Paper type Research paper

1. IntroductionThe subprime crisis that began in August 2007 in the USA has been labeled as theworst financial crisis since the Great Depression by many including George Soros,Joseph Stiglitz, and the International Monetary Fund (IMF) (Jaffee, 2008; Tong and Wei,2008). The crisis has developed into the largest financial shock, inflicting heavy damageon markets and institutions at the core of the global financial system (IMF, 2008). Thecrisis has not only been affecting the financial markets and the economy of the USA, butit has also been spreading over the other countries’ financial markets worldwide, andthe emerging financial markets are no exception. For example, since started in July 25,2007 until December 31, 2008, the global financial crisis has severely affected the USstock market as indicated by a decline in the S&P500 index by 40.50 percent. Otherstock markets in the advanced and emerging economies have also been affected such asthe FTSE100 index of the UK stock market plunged by 31.30 percent, Nikkei225 indexof Japan fell by 50.39 percent, KLSE index of Malaysia decreased by 36.45 percent andJakarta composite index (JCI) of Indonesia declined by 43.39 percent in thecorresponding period (Bloomberg Database, 2008).

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/1746-8809.htm

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International Journal of EmergingMarkets

Vol. 4 No. 4, 2009pp. 341-357

q Emerald Group Publishing Limited1746-8809

DOI 10.1108/17468800910991241

There have been generally two different views on the impact of the slowdown in theUS economy on Asian emerging markets that focus on international linkages andspill-over, namely the decoupling versus recoupling views. The slowdown of the USeconomy and the continued strength of growth in emerging Asia have set off theso-called “decoupling” debate; that is, whether emerging Asia is decoupling from theglobal business cycle. The main argument behind the decoupling theory is that stronggrowth and rising purchasing power will increase emerging Asia’s own final demand,which would then help the region to weather the adverse consequences of a USslowdown and ease the impact of a global downturn. In contrast, the coupling viewfocuses more on global linkages of Asian economies. Although intra-regional exportsare fast increasing, this is mostly due to trade in intermediate goods. Moreover, underthe recent trend of strengthening linkages of global trade and increasing role of globalproduction networks, import demand from the USA, Euro area, and Japan is assumedto be more important for the region than ever before. Kim et al. (2009) concluded thatthe rapid economic integration within Asia is tightly linked to global integration.Rather than decoupling, emerging Asia, the USA, UK, and Japanese economies have infact been recoupling.

Studies on the impact of current global crisis on integration and co-movementsamong stock markets have practical important information on the potentialinternational diversification opportunities to the investors and financial stability of acountry (Ibrahim, 2005). Investing in integrated stock markets provide a limiteddiversification benefits to the investors since these stock markets are highly correlatedwith each other. Additionally, stock markets which are highly integrated tend to movetogether and have stable long run relationship. Stock markets in two countries could bemoving together due to strong economic and financial ties between the two countries.For instance, a strong trade relationship between the countries could result in thepredictability of the economic performance of one country to another (Masih andMasih, 1999; Kearney and Lucey, 2004). Stock markets of two countries could also behighly correlated if there are similarities in macroeconomic policy implementationsbetween the countries. For instance, countries that pursue macroeconomic policyharmonization could find that their stock markets tend to move together.

As a result of the 2007 US subprime crisis, there is a renewed interest in exploringthe consequences of financial market crisis on the stock markets. Earlier studies in thisarea tend to show some general findings particularly on the international transmissionof the financial shocks across markets throughout the globe. The study by Cha andSekyung (2000) and Jeon and von (1990) found empirical supports on greaterco-movements among major stock markets after the October stock market crash in theUSA. Similarly, Baig and Goldfajn (1998) and Jang and Sul (2002) for example, findevidence of greater co-movements between the stock markets in the Asian regionfollowing the Asian financial crisis 1997.

There are voluminous studies focusing on the issue of stock market integration.Most of these studies, however, focus on the stock markets in the developed countries.For instance, Taylor and Tonk (1989) study the relationship between the stock marketsof the USA, UK, Germany, The Netherlands, and Japan, and find that these markets aregetting increasingly cointegrated. Campbell and Hamao (1992) focus on the world’s twomajor stock markets, namely the USA and Japan and document greater integration dueto multi-factor asset pricing. Other studies include Fischer and Palasvirta (1990),

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Kasa (1992), Longin and Solnik (1995), and Bracker et al. (1999). There are alsoincreasing bodies of literature on stock market integration in the emerging countriessuch as in Asia. This includes Ibrahim (2002, 2005), Yusof and Majid (2006), and Majidet al. (2008, 2009).

In view of the increasing interest for information on the degree of stock marketsintegration particularly in the aftermath of the US financial crisis 2007, the objective ofthis study is to empirically compare the nature of stock market integration among theUS stock market and two emerging economies stock market, namely Indonesia andMalaysia. The study also considers two other major stock markets, namely the UK andJapan as a way of comparison and to arrive at richer findings. In particular, the studyaims to empirically examine the effect of the US 2007 sub-prime mortgage and creditcrunch crisis on Malaysia and Indonesia by comparing the co-movement of these stockmarkets in the pre-crisis period and during the 2007 US crisis period. It also attempts toempirically explore the existence of a common trend in these markets before andduring the crisis. Finally, by dividing the study periods into pre- and during 2007crisis, the study empirically examines whether the cross-market linkages betweenthese markets change due to the crisis. To achieve these objectives, time seriestechniques of cointegration, impulse response functions (IRFs) and variancedecompositions (VDCs) are used.

An aspect of novelty of this study is that it takes into account the current financialsituation in the global economy which is being affected by the US crisis. In particular,this study compares empirically the co-movements between the stock markets for theperiod before and during 2007 global financial crisis. An accurate assessment of thedegree of co-movement among the stock markets is important for several reasons. Forinvestors, the design of a well-diversified portfolio crucially depends on a correctunderstanding of how closely international stock market returns are correlated.Changes in international correlation patterns call for an adjustment of portfolios. Policymakers are interested in correlations among equity markets because of theirimplications for the stability of the global financial system. Monetary policy strategy isalso influenced by international stock market developments due to the internationalpropagation of shocks via equity markets, wealth channel, and confidence effects. Theglobal trend towards a greater role of the stock market in the economy has made thistype of spillover more important.

The rest of this study is organized as follows. The next section provides theliterature review on the performance of the stock markets during financial crises, andSection 3 discusses the empirical framework and methods undertaken in this study.Section 4 describes the data employed, and Section 5 presents the empirical results anddiscussions. Section 6 draws several implications from the findings, and finally,Section 6 concludes.

2. Empirical frameworkThe empirical approach adopted in this study is based on standard time series methodsof cointegration and vector autoregressive (VAR) framework. The study adopts thisapproach for various reasons. First, the method is simple where one does not have toworry about making a priori distinction between exogenous and endogenous variables.According to Sims (1980), the distinction is often subjective and therefore it is wise totreat them on an equal footing. Second, this technique sets no restrictions on the

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structural relationships of the economic variables and hence, misspecificationproblems may be avoided. Finally, the variance decomposition and IRFs derived fromVAR allow us to assess the strength and direction of variables in the system, thusenabling a more detailed and rich discussion on the topic of interest.

Specifically, the empirical framework of this study involved various steps. First, byusing the augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) tests (Perron, 1988;Phillips and Perron, 1988), each series is tested for unit roots. Since the methodology oftesting unit roots is well known, the details are omitted in this study. Next, to test forcointegration among the stock markets, the maximum likelihood approach of Johansen(1988) and Johansen and Juselius (1990) (JJ) cointegration approach, is adopted. Finally,to empirically assess their short-run causal nexus, IRFs, and VDCs are used.

2.1 Cointegration testEssentially, the JJ is based on a VAR model as follows:

Yt ¼ dþPiYt21 þ · · · þPkDYt2k þ 1t ð1Þ

where Yt is an n £ 1 vector of non-stationary variables integrated of the same order,d is an n £ 1 vector of intercept terms, Pi is an n £ n matrix of coefficients, 1t is ann £ 1 vector of white noise error term assumed to be white noise and k is the order ofautoregression. As our study investigates market integration among the five stockmarkets, n ¼ 5.

To assess the cointegration among the stock markets, equation (1) can beequivalently written in matrix form as follows:

DMY

DID

DJP

DUK

DUS

266666664

377777775¼

d0

d1

d2

d3

d6

2666666664

3777777775þ

Xk

i¼1Gi

DMY

DID

DJP

DUK

DUS

266666664

377777775t2k

þP

MY

ID

JP

UK

US

266666664

377777775t21

þ

1t0

1t1

1t2

1t3

1t4

2666666664

3777777775

ð2Þ

where MY, ID, JP, UK, and US indicate the stock indices of Malaysia, Indonesia, Japan,the UK and the USA.

Since our model considers the possibility of the past level of parameters to have aneffect on current changes in other parameters, the lagged values have to beincorporated in the models. In this study, the Akaike (1974) information criterion (AIC)is used to determine the lag length incorporation in all the tests of this study.

The existence of a long-run relationship among stock markets is tested based on therank of an n £ n matrix coefficients of lagged level variables, P in equation (2). Thelong-run information matrix P in this equation is the key to Johansen’s cointegrationtest because its rank r determines the number of cointegrating vectors. If rank (P) ¼ 0,equation (2) returns to a VAR model in the first differences and the components in Yt

are not cointegrated. On the other hand, if P is a full rank n, all component in Yt arestationary. In a more general case when 1 , rank (P) , n, the number ofcointegrating vectors is equal to r, the rank of matrix P. Since the rank of a matrix isequal to the number of eigenvalues li (or characteristic unit roots) that are significantly

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different from zero, Johansen proposed two statistics to test the rank of the long-runinformation P, namely:

ltraceðrÞ ¼ 2TXn

i¼rþ1

lnð1 2 l̂iÞ ð3Þ

lmaxðr; r þ 1Þ ¼ 2Tlnð1 2 l̂rþ1Þ ð4Þ

where li are estimated eigenvalues (characteristic roots) ranked from largest tosmallest. The ltrace in the equation (3) is called the Trace statistics, which is alikelihood ratio test statistics for the hypotheses that are at most r cointegratingvectors. The lmax in the equation (4) is called the maximal eigenvalue statistic thattests the hypothesis of r cointegrating vectors against the hypothesis of r 2 1cointegrating vectors. The rank of P is equal to the number of eigenvalues that aredifferent from zero. If eigenvalues li’s are all zero, then the ltrace and lmax will be zero.To test for the number of cointegrating vectors, this study employs Johansen andJuselius’s (1990) and Osterwald-Lenum’s (1992) ltrace and lmax statistics that areadjusted for the degree of freedom.

Additionally, an important requirement for implementing the JJ cointegration test isthat the variables are non-stationary integrated of the same order. Accordingly, prior tothe JJ test, the standard ADF and PP unit root tests are conducted to determine theorder of integration for each national stock price.

2.2 VDCs and IRFsConventionally, VAR studies such as Sims (1980) employ variables in log level. Theproblem is that the results from such a specification may be spurious and misleading iflog level variables are non-stationary. Transforming the variables into first differencesto render the variables stationary before running VAR, however, introducesmisspecification problem in the case that the variables under consideration arecointegrated. For proper specification of the VAR model so as to avoid spuriousregression or misspecification problems, integration and cointegration tests outlined inthe previous step are necessary. In particular, the findings that the variables arenon-stationary and are not cointegrated suggest the use of VAR model in firstdifferences. However, if they are cointegrated, a vector error correction model or a levelVAR can be used (Engle and Granger, 1987). This study therefore uses the VAR modelin first differences and level, respectively, for cointegrated and non-cointegrated stockmarkets in its IRFs and VDCs analyses.

The IRFs analysis is used to assess the dynamic interactions among the stockmarkets. The innovation in one market may be contemporaneously correlated toother markets. This means that shocks in one stock market may work through thecontemporaneous correlation with innovations in other markets. Since isolatedshocks to individual market cannot be identified due to contemporaneous correlation,the responses of a stock market to innovations in another market cannot beadequately represented (Lutkepohl, 1991). The common approach in solving thisidentification problem is to employ Sims’ (1980) empirical strategy by orthogonalizingthe innovations using the Cholesky factorization. The approach, however, requires apre-specified causal ordering of the markets which turn out to be its majordisadvantage. Namely, the results from the IRF analysis may be sensitive to the

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ordering of the markets particularly when contemporaneous correlations of errorterms in the VAR are high. To overcome this shortcoming, this study adopts thegeneralized IRFs developed by Pesaran and Shin (1998). As noted by Pesaran andShin (1998), the generalized IRFs fully account for the historical patterns ofcorrelations among the different shocks. Accordingly, they are unique and invariantto alternative orderings of the stock markets. Another advantage of the generalizedIRFs is that, since the error structure is not orthogonalized, the initial impactresponse of a variable to various shocks can be examined. As highlighted by Ewinget al. (2003), this feature of the generalized IRFs is particularly useful for studies ofequity markets, which are generally characterized by quick price transmissions andadjustments.

3. DataTo provide robust and updated results, this study uses daily closing data of fiveselected stock markets, namely Malaysia, Indonesia, Japan, the UK and the USA,covering the period from February 15, 2006 to December 31, 2008. All the indices aredenominated in local currency units, extracted from the Bloomberg Database. In thisstudy, the conventional stock returns for these markets are calculated from thefollowing indices:

. Kuala Lumpur composite index for Malaysia.

. JCI for Indonesia.

. Nikkei225 Index for Japan.

. FTSE100 for the UK.

. S&P500 for the USA.

In order to empirically explore changes in the cross-market linkages among the stockmarkets, the study divides the period of analysis into two periods, namely thepre-crisis and during 2007 global crisis periods. Since the US sub-prime mortgagecrisis started in July 26, 2008 (Dungey et al., 2008), this study therefore divides theperiod of study into two periods, namely the pre-crisis period spanning from February15, 2006 to July 25, 2007, and during crisis period starting from July 26, 2007 toDecember 31, 2008.The groupings of data into the two sub-periods would shed somelights as to whether the cross-market linkages among the stock markets have changeddue to crisis.

Commonly, two problems arise in examining integration of different stock markets.The first problem lies in the missing observations due to different stock marketholidays. Since the study extensively incorporates lags in the regressions, missing datais particularly troublesome. Thus, it is desirable to fill in estimate-based informationfrom an adjacent day. Rather than using a sophisticated interpolation, this studyfollows the studies of Jeon and von (1990) and Hirayama and Tsutsui (1998) byadopting the method of Occam’s razor (by just filling in the previous day’s price). Thesecond one is the differences in the trading hours among the international stockmarkets. For the purpose of this study, we adjust for the different trading hours. Forexample, we analyze today’s stock indices of Malaysia, Indonesia, Japan withyesterday’s (lag ¼ 1) index of the USA.

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4. Results and discussionThis section discusses the findings of this study. First, the summary statistics of thestock returns are discussed, followed by the discussion on the correlation coefficients ofstock returns and the unit root tests. Next, the results of the econometric analyses arepresented starting with the cointegration analysis, followed by the IRFs analysis, andVDCs analysis.

4.1 Summary of statistics of the stock returnsTable I provides the summary statistics of the stock returns (i.e. stock prices in firstdifference) for the selected stock markets over the pre- and during-the 2007 globalfinancial crisis. It is interesting to note that in the period before the crisis, all stockmarkets recorded positive average daily returns, while in the period during the crisis,all the stock markets witnessed negative average daily returns. Specifically, in thepre-crisis period, the Indonesian market recorded the highest average daily returns at12.6 percent, followed by Malaysia 7.6 percent, the USA 3.2 percent, Japan 2.2 percentand the UK 2.1 percent, while in the period during the crisis, the UK market has thelowest average daily losses at 26.6 percent, followed by Malaysia 28.7 percent, theUSA 29.5 percent, Indonesia 210.6 percent and Japan 213.2 percent.

In terms of volatility as reflected by the standard deviations, as expected, all thestock markets recorded greater volatility in the period during the crisis compared tobefore the crisis. Of the investigated markets in this study, the Indonesian marketsappeared to be the most volatile market in the pre-crisis period. However, in terms ofmagnitude of change in the volatility in the post-crisis period compared to the pre-crisisperiod, the developed stock markets seem to record greater changes in volatilitycompared to that of the emerging markets.

4.2 Correlation of coefficients of the stock returnsTo highlight the short-run relations between the movements of the selected stockmarkets, the results from standard correlation of coefficient tests are reported inTable II. The correlation of coefficient is used to measure the extent of association

Period Variables MY ID JP UK US

Pre-crisis Mean 0.076 0.126 0.022 0.021 0.032Maximum 2.601 5.322 3.301 2.605 2.134Minimum 24.746 26.515 24.230 22.963 23.534SD 0.617 1.021 0.897 0.659 0.558Skewness 21.365 21.056 20.310 20.491 20.513Kurtosis 14.201 11.734 5.842 6.271 8.322

During-crisis Mean 20.087 20.106 20.132 20.066 20.095Maximum 4.259 7.623 13.235 9.384 10.957Minimum 29.979 210.954 212.111 29.266 29.470SD 1.075 1.896 2.104 1.761 1.885Skewness 21.581 20.717 20.430 0.020 20.181Kurtosis 18.315 9.938 12.001 10.166 11.464

Notes: Pre-crisis period starts from 15 February 2006 to 25 July 2007; during crisis period spans from26 July 2007 to 31 December 2008; MY, ID, JP, UK, and US refer to the stock markets of Malaysia,Indonesia, Japan, the UK and the USA, respectively

Table I.Summary statisticsof the stock returns

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between the stock markets. In the pre-crisis period, the results show that the onlycorrelation of coefficient which is greater than 0.5 was between the US and the UKmarkets. There rests of the markets have correlation of coefficients that are smallerthan 0.5. However, in the post-crisis period, there are increasing number of marketswhich have correlation of coefficients that are greater than 0.5. In particular, the USand the UK market recorded higher degree of correlation (0.528), Malaysia andIndonesia (0.595), and Indonesia-Japan (0.504). In fact, all the stock markets haverelatively higher degree of correlation between each other in the post-crisis periodcompared to the pre-crisis period, except for Malaysia-USA. The increase in thenumber of significant correlation during the crisis is consistent with the contagioneffect. The increase in the correlation coefficients also indicates that there areshort-term co-movements among the markets, suggesting that the benefits ofshort-term diversification are limited within these markets during the crisis period.

4.3 Unit root testsIn order to obtain credible and robust results for any conventional regression analysis,the data to be analyzed must be stationary (Pankratz, 1983; Harvey, 1990; Gujarati,1995). Hence, to test for stationarity, the ADF and PP tests are performed based on themodel with constant and trend. Table III reports the ADF and PP tests statistics thatexamine the presence of unit roots (non-stationary) for all the stock indices.

The results show that all the stock indices contain a unit root, implying that the nullhypothesis of the presence of a unit root at level cannot be rejected at level for all thestock indices. Since the indices are found to be non-stationary at levels (with theexception of the PP test for the UK during the pre-crisis period), the first differences forthe whole models are taken. The same tests are applied to the first differences of theindices and the results show that all the indices become stationary after firstdifferencing. This result indicates that all index levels are integrated of order one, I(1)and, therefore, we can proceed with the cointegration analysis since these indices theyare integrated in the same order. Having identified that all the stock indices arestationary at first difference, we now proceed with the cointegration tests, aiming atinvestigating whether there exist long-run relationships among these stock markets.

Period MY ID JP UK US

Pre-crisis MY –ID 0.465 –JP 0.442 0.462 –UK 0.298 0.271 0.297 –US 0.138 0.028 0.094 0.526 –

During-crisis MY –ID 0.595 –JP 0.476 0.504 –UK 0.357 0.362 0.452 –US 0.069 0.134 0.116 0.528 –

Note: The figures in italic indicate the cases of increased correlations from the pre-crisis to duringcrisis

Table II.Correlation of the stockreturns

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4.4 Cointegration analysisTable IV reports the results of cointegration tests, which indicate the existence of longrun equilibrium relationship among the stock markets under review. Interestingly, inline with the earlier findings, the results show that the stock markets are found to becointegrated only during the crisis period, but not in the pre-crisis period. Both theeigenvalue statistics and trace statistics tests results show that the null hypothesis ofno cointegration is rejected at the 5 percent level of significance, indicating that theirresiduals are in the stationary process. This finding implies that there exists a long-runequilibrium relationship among the stock markets only during the crisis period.

The results clearly show that the stock markets have become increasinglycointegrated during 2007 global financial crisis. These empirical findings, which areconsistent with the contagion effect, suggest that the markets becamemore interdependent during the crisis period, but at the same time, more integratedin the sense that they each reacted not only to local news, but also to news originatingin the other markets, especially when the news were adverse. This concurs well withthe findings of Goldstein and Michael (1993) which find that the international linksboth in the developed and emerging markets have been increasing over the pastdecade. These findings have important implication that the degree of integrationbetween emerging markets tends to change over time, especially around periodsmarked by financial crises. As Bekaert and Harvey (1995) noted, previous researchassumes that stock markets are either perfectly integrated, perfectly segmented, orpartially integrated with the extent of integration constant over time. However, like the

Pre-crisis During-crisisStock Level First-difference Level First-differencemarket ADF PP ADF PP ADF PP ADF PP

MY 22.136 22.151 25.562 * * 219.089 * * 21.629 21.725 221.809 * * 221.811 * *

ID 21.159 21.144 217.022 * * 222.510 * * 21.753 21.639 220.861 * * 220.870 * *

JP 22.486 22.389 224.567 * * 224.598 * * 22.319 22.205 223.091 * * 223.281 * *

UK 23.106 23.146 * 223.909 * * 223.907 * * 22.177 22.589 29.554 * * 224.841 * *

US 22.798 22.774 26.459 * * 223.643 * * 21.859 22.026 213.117 * * 227.908 * *

Notes: * and * * denote significance at the 1 and 19 percent levels; for the ADF test, the lag lengthsincluded in the models are based on the AIC to whiten the noise process

Table III.Unit root tests

Pre-crisis During crisisNull hypothesis Trace statistic Max-eigen statistic Trace statistic Max-eigen statistic

r # 0 58.472 31.482 93.684 * 9.193 *

r # 1 26.990 13.425 54.491 27.332r # 2 13.565 7.086 27.158 16.380r # 3 6.478 5.499 10.778 7.321r # 4 0.979 0.979 3.457 3.457

Notes: *Denotes significance at the 5 percent level; r denotes the number of cointegrating vectors; theoptimal lag length is determined based on the AIC, since the study utilizes daily data, the maximumlag-length considered in the study is 30, lag ¼ 2

Table IV.Results of cointegration

tests

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two major stock market crises, the 1987 crash and the 1997-1998 emerging stockmarket crisis (Arshanapalli et al., 1995), the 2007 US financial crisis has also beenobserved to strengthen regional integration between emerging Asian stock markets.

Essentially, this finding implies that the international investment diversificationbenefits that can be gained by investors across these markets have diminished due tothe crisis. However, it is importance to note here that the existence of cointegrationamong the markets does not rule out the possibility of arbitrage profits throughdiversifying portfolios across these markets in the short-term, which may last for quitea while (Dwyer and Wallace, 1992; Yang and Siregar, 2001). Thus, because of varyingdegrees of business and financial risks of different securities and various security cashflows co-varying less than perfectly across the markets (and even within the samecountry), the diversification benefits in these markets in the long-term may be reducedbut are not likely to be fully eliminated in practice.

4.5 VDCs and IRFs analysesThe cointegration analysis so far only suggests the long-run associations amongst thestock markets being considered. To examine the relative strength of shocks in the USmarkets in explaining the changes in other stock markets, the study adopts the VARmodel, from which short-run dynamics can be assessed by generating the VDCs andIRFs. The VDCs and IRFs allow us to capture the relative importance of shocks in theUS markets and their influences on other stock markets.

Tables V and VI provide the VDC for the stock markets in the pre- and during-crisisperiods, respectively, over the 30-day horizon. As may be observed from the VDCs, the

Explained by shocks inHorizon MY ID JP UK US

1 100.000 0.000 0.000 0.000 0.0006 85.850 0.054 0.242 6.264 7.589

16 78.745 0.047 1.158 8.958 11.09330 71.175 0.172 3.221 11.570 13.862

1 16.244 83.756 0.000 0.000 0.0006 10.599 74.007 0.347 7.668 7.379

16 9.376 60.732 1.129 19.232 9.53230 8.597 48.770 2.534 28.990 11.108

1 10.525 5.733 83.742 0.000 0.0006 13.179 3.451 63.248 10.946 9.176

16 12.908 1.653 53.938 17.361 14.13930 12.856 1.440 45.588 21.564 18.551

1 7.683 1.407 2.620 88.289 0.0006 7.819 0.337 2.667 82.509 6.668

16 9.006 0.256 2.277 78.070 10.39130 10.470 0.213 1.785 73.523 14.009

1 3.985 0.067 0.413 29.545 65.9906 2.916 0.798 0.386 34.955 60.945

16 3.881 0.621 0.311 37.678 57.50930 5.199 2.617 1.312 39.453 51.419

Note: The pre-2007 global financial crisisTable V.Variance decompositions

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shocks in the US markets caused marked increase variations in the stock marketsduring the crisis compared to before the crisis period. For example, the variations in theMalaysian stock market increased due to the shocks in the US markets from about 0-14percent (pre-crisis period) to 0-22 percent (during-crisis period) of the Malaysianmarket’s forecast error variance. Meanwhile, the variations in the Indonesian stockmarket only increased from about 0-11 percent (pre-crisis period) to 0-17 percent(during-crisis period) of the Indonesian market’s forecast error variance. This indicatesthat, unlike the Malaysian stock market, the Indonesian stock market is found to berelatively less affected by the crisis the short-run. The differences in the countries’external capital controls (Cheung and Mak, 1992), financial deregulation (Chowdhury,1994) and trade bilateral dependencies (Pretorius, 2002) may contribute to thesedifferent empirical findings. Moreover, the stronger the bilateral trade ties between thecountries, the higher of co-movements between them (Masih and Masih, 1999; Brackeret al., 1999; Pretorius, 2002). Since Malaysia is a country that has stronger bilateraltrade ties with the USA, Japan and the UK compared to Indonesia, thus its stockmarket is more affected by the current global crisis.

Additionally, the variations in the stock markets of the UK and Japan have beenlargely increased due to the shocks in the US markets, accounting for about 0-55percent and 0-39 percent after 30 days. These findings imply that the opportunities ofgaining abnormal profit through investment diversification during the crisis period inthese markets are diminishing as the markets going towards a greater integrationamongst them.

Comparing the importance of the three most developed markets in the world, theUSA, the UK and Japan on the emerging markets of Malaysia and Indonesia, the study

Explained by shocks inHorizon MY ID JP UK US

1 100.000 0.000 0.000 0.000 0.0006 84.411 2.062 0.992 6.962 5.574

16 66.679 1.029 2.873 15.230 14.18930 52.146 0.573 3.409 20.982 22.890

1 28.692 71.308 0.000 0.000 0.0006 26.846 65.598 0.939 3.278 3.339

16 25.712 53.086 3.557 7.682 9.96330 25.063 40.079 5.404 12.250 17.203

1 14.712 4.910 80.378 0.000 0.0006 11.756 6.486 49.580 14.046 18.132

16 6.885 3.824 34.174 15.078 40.03830 4.245 2.400 24.338 13.838 55.178

1 9.833 2.601 6.208 81.358 0.0006 7.173 3.249 3.378 74.547 11.653

16 5.965 2.947 2.530 62.659 25.89930 5.396 2.783 2.255 49.772 39.794

1 0.955 1.642 2.047 35.733 59.6226 0.418 2.565 1.538 34.606 60.873

16 0.675 3.226 2.214 27.838 66.04630 1.225 3.588 2.841 22.762 69.585

Note: During the 2007 global financial crisisTable VI.

Variance Decompositions

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finds that during the pre-crisis period both, the stock markets of Indonesia andMalaysia respond more to shocks in the UK and the US markets, respectively. On theother hand, during the 2007 global crisis period, the variations in the stock markets ofMalaysia are affected more by the shocks in the US market. In fact, for all the stockmarkets, shocks in the US market have been contributing to explaining the variationsin these stock markets greater during the crisis period compared to the pre-crisisperiod. This finding contradicts those of Janakiramanan and Asjeet (1998), Brackeret al. (1999) and Pretorius (2002) which state that the geographic distance betweendifferent stock markets is one of important factors contributing to a greater extent ofmarket interdependent. Results of this study re-emphasize the dominance of thetrade-link factor over the geographic distance factor contributing towards marketinterdependent. Additionally, the findings reflect the US market’s persistent dominantrole in the Asian region. This finding is consistent with those of Chowdhury (1994) andHee (2002). They discovered that the US stock market is not only dominant in theASEAN region, but is also the most influential market in the world. The US stockmarket led most of all other markets (Cheung and Mak (1992), while other marketshave little, if any, influence on the US market (Janakiramanan and Asjeet, 1998).

Lastly, we generate the IRFs to complement our analysis based on the VDCs. Ingeneral, the overall results concur well with our earlier findings. As shown in Figure 1,in the pre-crisis period, shocks in the US market are shown to exert immediatelysignificant positive effect on the Malaysian, Indonesian, Japanese, and the UK stockmarkets. The impacts reached their maximum at the two-day horizon and graduallydecline afterwards at the three-day horizon. This finding echoes our earlier finding

Figure 1.Generalized impulseresponses of the stockmarkets to innovations inthe US market during thepre-crisis period

–0.2

–0.1

0.0

0.1

0.2

0.3

0.4

1 2 3 4 5 6 7 8

Response of UK to US

–0.2

–0.1

0.0

0.1

0.2

0.3

0.4

0.5

1 2 3 4 5 6 7 8

1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8

Response of JP to US

–0.2

–0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6Response of ID to US

–0.1

0.0

0.1

0.2

0.3Response of MY to US

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based on the VDCs. More importantly, it further implies that any policies affecting theUS market should at least be noted by the authorities to affect the other stock markets.

As for the during the crisis period (Figure 2), the stock markets react immediatelyand significantly to shocks in the US market during the crisis period. The shock in theUS market affect immediately and positively the other stock markets until about oneand half to two days horizon, and then gradually subside to zero within three days. Ascompared to the pre-crisis period, the shocks in the US market during the crisis periodhave affected more on the other markets. In other words, supportive of the resultsbased on the VDCs, the stock markets are found be more responsive to the shocks inthe US market during the crisis period compared to the pre-crisis period.

5. Implications of the findingsIn general, the results of this study supports the view that stock markets tend to showgreater degree of integration or increased co-movements during crisis period, resultingin lesser benefit of diversification that can be gained by investors participating in thesemarkets. However, the existence of cointegration among the markets does not rule outthe possibility of arbitrage profits through diversifying portfolios across these marketsin the short-term despite the reduced diversification benefits in these markets in thelong run, they are not fully eliminated in practice. A plausible explanation is that duringthe crisis period, the stock markets were driven by a common international factor, whilecountry-specific factors have become less important than the international factors,leading to the long-run co-movements among the stock markets. With regard to thecurrent “de-coupling versus coupling” debate, this study provides further support for

Figure 2.Generalized impulse

responses of the stockmarkets to innovations in

the US market duringcrisis period

–0.8

–0.4

0.0

0.4

0.8

1.2

1 2 3 4 5 6 7 8

Response of UK to US

–0.4

0.0

0.4

0.8

1.2

1.6

1 2 3 4 5 6 7 8

1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8

Response of JP to US

–0.2

–0.1

0.0

0.1

0.2

0.3

0.4Response of MY to US

–0.4

–0.2

0.0

0.2

0.4

0.6

0.8Response of ID to US

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the coupling view. In particular, the results suggest that during the economic crisis inthe USA, the emerging Asian stock markets tend to be more integrated with the majorstock markets.

Furthermore, our evidence of the level of cointegration among these markets hasimportant implications for the macro stabilization policies for each market. The extentof the effectiveness of the macroeconomic policies of a country in dealing with its stockmarket imbalances will depend crucially on the extent of financial integration of eachstock market with the rest. In particular, since the markets are integrated, then acountry’s economy cannot be insulated from foreign shocks and this reduces the scopefor independent monetary policy. Moreover, effective diversification amonginternational markets cannot be achieved and the integrated markets can beconsidered as one market set by long-term investors. The market integration in thelong-run points to the limitation associated with the pursuit of interdependent policy,especially the financial policy. Rather, as the economies become more integratedglobally, there is a need for policy coordination to mitigate the impact of financialfluctuations, as the stock markets are interdependent. Finally, greater policycoordination, along with the reduction or removal of investment barriers, will beessential if these countries are to exploit the advantages of greater economic andfinancial interdependence.

Similarly, the extent of integration among the markets will have important bearingson the formulation of the financial policies of multinational corporations. For example,while the 2007 global financial crisis was initially the sub-prime mortgage and creditcrunch crisis in the USA, followed by the currency and stock markets, many firms inthe global markets later found themselves in financial distress. It is a well-known factthat stock markets and foreign markets are very much connected. Mundell (2000), the1999 Nobel Laureate, writes that exchange rate volatility is a major threat to globalprosperity that causes unnecessary volatility in capital markets. Therefore, knowingthe co-movement among the stock markets would give an idea of exchange rate riskbetween countries. Such information can, therefore, help managers to mitigateinternational risks and managing economic, transaction, and translation of risks.

6. ConclusionThis study empirically explores the effects of the current global crisis on theintegration and co-movements of selected stock markets using the standard time seriestechnique and VAR framework over the period from February 15, 2006 to December31, 2008. In order to assess changes in the stock markets integration and theirco-movements, this study divides the period of analysis into two periods, namely thepre-crisis period (February 15, 2006-July 25, 2007) and during the crisis period (July 26,2007-December 31, 2008).

Based on rigorous empirical tests, the study finds that the US 2007 crisis hassubstantial impact on the performance of the stock markets. As a result of the crisis, allthe stock markets under review recorded average daily losses in the period during thecrisis compared to average daily gains in the period before the crisis. The correlationtest shows increased degree of correlation between the markets during the crisiscompared to before the crisis period. The cointegration test results suggest that themarkets have a long run equilibrium relationship only during the crisis period, whilethe long run equilibrium relationship was non-existent in the period before the crisis.

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The results from the VDCs and IRFs further highlight the importance of major marketsin influencing the stock markets of the emerging economies, particularly during thecrisis period. Overall, the results of this study support the general view that stockmarkets tend to show greater degree of integration or increased co-movements duringthe crisis period, resulting in lesser benefit of diversification that can be gained byinvestors participating in these markets.

To further add to the existing literature on market integration, further empiricalstudies on the issue can cover broader areas of market integration and explore factorsaccounting for market integration. A further possible extension of the study is toquantify and compare the diversification benefits investors can gain when diversifyingtheir investments across the global markets.

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Corresponding authorM. Shabri Abd Majid can be contacted at: mshabri@iiu.edu.my

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