STOCK MARKET INTEGRATION BETWEEN MALAYSIA AND ITS MAJOR TRADING PARTNERS ( ) KARIM, Mohd Zaini * GEE, Chan Sok

Transcription

1 Karim, M.Z.A. and Gee, C.S. Stock Markets Integration Between Malaysia and Trade Partners STOCK MARKET INTEGRATION BETWEEN MALAYSIA AND ITS MAJOR TRADING PARTNERS ( ) KARIM, Mohd Zaini * GEE, Chan Sok Abstract: The issue of interdependence between international asset pricing had become an important topic in modern finance literature. It had received tremendous attention due to the increasing role of globalisation of market place. This is because globalisation had reduced the barriers to capital transactions among various countries and increased the linkages between stock markets movement in various countries. It is argued that trade linkages is one of the factors that increase the linkages of stock market movement between countries. This study employs cointegration and causality techniques in investigating the relationship between Malaysian and its major trading partners stock market before and after the 1997 Asian financial crisis. The results of the bivariate cointegration test on countries stock indices indicate the existence of a long run relationship between Malaysian and the Philippines stock markets as well as between Malaysian and the United States stock markets for period before the financial crisis. Before the 1997 financial crisis, the daily price movement of Malaysian stock market is found to lead the daily price movement in Indonesia, China in the short-run, and the Philippines in the long run. In addition, there is a bi-directional relationship between Malaysia and the stock markets in Hong Kong and Thailand. The short-run causal relationship between the Malaysian stock market and the stock markets of its major trading partners started to weaken after the financial crisis. Such finding is highly attributable to the fact that Malaysia s imposition of capital control in September 1998 in their attempt to curb speculative attacks had been relatively successful in shutting out foreign influences. Keywords: Stock market, Cointegration, Malaysia, financial crisis JEL classification: G Introduction The issue of interdependence between international asset pricing had become an important topic in modern finance literature. It had received tremendous attention due to the increasing role of globalisation of market place. Globalisation is argued to have reduced the barriers to capital transactions among various countries and increased the linkages between stock markets movement in various countries (Darbar and Deb, 1997). The advances in communications technology (e.g. implementation of computerized trading system) and capital mobility (e.g. relaxation of capital control movement) had reduced the international market imperfections over the years by lowering the cost of cross-border information flows and financial transactions (Koch and Koch, 1991). As a result, more markets tend to move together and the adjustments toward equilibrium might be shorter. In addition, economic conditions reflecting global financial condition due to lower interest rates and decreased inflation may also contribute to the existence of long * Mohd Zaini Abd Karim, PhD Associate Professor, Faculty of Economics, Universiti Utara Malaysia, Sintok, Kedah, Malaysia, a zaini500@uum.edu.my nd Chan Sok Gee, Faculty of Accountancy and Management, Universiti Tunku Abdul Rahman 203

2 Applied Econometrics and International Development Vol.6-3(2006) run relationships among different regional stock indices because this factor serves as an incentive for investors to borrow funds from domestic banks and investing them in stock markets due to lower cost of funding. Apart from that, the existence of long run relationships among different regional stock indices might also be due to the strong economic ties, policy coordination, and trade among the relevant regions (Ratanapakorn and Sharma, 2002). As such, it is argued that the search for countries with different policy and trade coordination is vital in portfolio diversification across countries. If this is true, than the stock market between two countries that have strong trade relation should have stronger relationship compare to otherwise. This paper examines the short-term and long-term dynamic causal linkages between Malaysian and its major trading partners stock markets and analyze whether this relationship has changed after the Asian financial crisis. The analysis of stock markets linkages among different countries is believed to contribute to the risk diversification process by international investors. Hence, evaluating the relationship between Malaysian and its major trading partners stock market is important for investors (the volume of bilateral trade are in Table 1). If these markets are found not to be cointegrated, they present a good avenue for portfolio diversification. If there are lead and lags between these markets, the markets can offer arbitrage opportunities that can be exploited by investors. In addition, the imposition of capital control by the Malaysian authorities is argued to alienate the Kuala Lumpur Stock Exchange from the region after the financial crisis. Among the restriction is twelve-month holding period for repatriation of portfolio capital aimed at preventing heavy capital outflows by residents and non-residents. However, the restriction were relaxed somewhat on February 15, 1999, when a graduated system of exit levies on repatriation of the principal of capital investments replaced the twelve-months holding period requirement for repatriation of portfolio capital. The organization of the paper is as follows; Section 2 discusses the development of the Malaysian stock market and equity investment between Malaysia and its major trading partners; Section 3 reviews the literature; Section 4 explain the data and methodology; Section 5 provides the empirical results; and Section 6 concludes. 2. Development of the Malaysian Stock Market and Equity Investment between Malaysia and its Major Trading Partners. The equity market provides the avenue for corporations to raise funds by issuing stocks and shares. The secondary market trading in stocks and shares in Malaysia are the Kuala Lumpur Stock Exchange (KLSE) and the Malaysian Exchange of Securities Dealing and Automated Quotation (MESDAQ). The Malayan Stock Exchange was established in March 1960 and public trading of stocks and shares commenced in May 1960 in the clearinghouse of Bank Negara Malaysia (BNM) (BNM, 1999). In 1968, the Capital Issues Committee (CIC) was established. In 1973, the Malayan Stock Exchange was separated into the Kuala Lumpur Stock Exchange (KLSE) and the Singapore Stock Exchange (SES) due to the termination of currency interchangeability with Singapore and the floating of the Malaysian Ringgit. The development of the stock market in Malaysia can be classified into three distinct periods (BNM, 1999). The period between 1988 until 1990 saw the modernisation process taking place on the future developments in the stock market and stockbroking industry.the second period of development, which occurred during 1993 was known as the superbull run. During this period, the stock market was fuelled by substantial inflows of short-term capital. Besides that, efforts on institution 204

3 Karim, M.Z.A. and Gee, C.S. Stock Markets Integration Between Malaysia and Trade Partners building were implemented following the establishment of the Securities Commission in 1993.The third period of stock market development was seen during the financial crisis in July The financial crisis led measures being taken by the stock market authorities to improve the operations of the equity market over the medium-term. The Capital Market Masterplan was implemented to govern the future development of the equity market in Malaysia. In addition, the Malaysian stock market faced challenges due to the disclosurebased regulatory regime, globalisation, the advancement in information technology and the increased in the role of Malaysian Exchange of Securities Dealing and Automated Quotation (MESDAQ).Over the years, there was a significant expansion in the Kuala Lumpur Stock Exchange (KLSE) not only in terms of number of companies listed but also the market capitalization (Table 2 in the Annex). The number of companies listed in the main board of the KLSE increased significantly from 271 in 1990 to 562 in Market capitalization increased from RM billion in 1990 to RM billion in The financial crisis significantly affected the performance of the KLSE when the stock market capitalization decreased to RM375.8billion in 1997 and further dropped to RM billion in However, the stock market in Malaysia started to rebound to RM billion at the end of Table 3 shows the percentage of equity investment by all of Malaysia s major trading partners. It can be observed that all the major trading partners under this study accounted for more than 40 percent of equity investment inside Malaysia except for 1998, when the equity investment in Malaysia dropped to percent as a result of the Asian Financial Crisis. However, equity investment by the trading partners increased gradually from 1999 to 2001 due to the investors confidence towards the Malaysian financial markets. Table 3: Percentage of Equity Investment in Malaysia by its Major Trading Partners Year Thailand China Indonesia Philippines Hong Kong United States Japan Total (%) Source: Statistical Monthly Bulletin of Bank Negara Malaysia (July2003) Table 4: Percentage of Equity Investment by Malaysia with its Major Trading Partners Year Japan Thailand Indonesia China United States Hong Kong Philippines Total (%) Source: Statistical Monthly Bulletin of Bank Negara Malaysia (July2003) 205

4 Applied Econometrics and International Development Vol.6-3(2006) On the other hand, Table 4 presents the equity investment that Malaysia placed in the country of its major trading partners. It can be seen that Malaysia placed more than 35 percent in equity investment with its major trading partners. There was an increasing trend in the equity investment in the United States except during 1999, where the percentage of equity investment in the United States dropped to This might be due to the impact of Asian Financial Crisis. The equity investment in the United States continues to grow after 1999 and accounted for more than 20 percent of the investment that Malaysia placed with the world. 3. Review of Literature There are quite a number of studies that focus on long-run relationships between stock markets after a shock by testing for changes in the cointegrating relationship between markets. Arshanapalli and Doukas (1993) examined the linkages among stock prices in major stock exchanges namely, the Dow Jones Industrial Average of New York, FAZ General Price Index of Frankfurt, FTSE 100 Price Index of London, Nikkei Stock Average 225 of Japan and CAC General Price Index of Paris using the daily closing price indices from January 1980 until May The results of their study highlighted that the degree of international co-movements in stock price indices changed significantly for the period after the stock market crash of October 1987, except for the Nikkei Index. In addition, the stock markets of the France, Germany and United Kingdom stock markets were not related to the United States market before the crash period in October However, the stock markets of France, Germany and United Kingdom are strongly linked to the United States market during the post-crash period. Using multivariate cointegration technique and Vector Error Correction model, Hassan and Naka (1996) analyzed both short-run and long-run dynamic linkages among international stock markets. The result of the study indicates that there is a long run cointegrating relationships among the United States, United Kingdom, Japan, and Germany stock market indices for the entire, pre and post crash periods. In addition, the result also highlighted that the United States played a vital role in influencing the other stock markets during the entire period as well as in the pre and post October 1987 stock market crash period. Furthermore, there is a significant short-run feedback relationship between these two groups of four stock market indices existed for the entire period, the pre-crash and post-crash period. Chan, Gup and Pan (1997) did a study on integration of international stock markets in 18 countries using Johansen s (1988 and 1991) cointegration tests. They employed data from January 1961 to December 1992 and further divided the data into three sub-periods namely the 1960s, 1970s and after The result of the analysis showed that a small number of stock markets appeared to be integrated with each other. However, the number of significant cointegrating vectors was higher before the October 1987 stock market crash. The results of their analysis were in contrast with Arshanapalli and Doukas (1993) study.roca, Selvanathan, and Shepherd (1998) examined the extend and structure of price linkages among five Association of Southeast Asian Nations markets using cointegration tests based on the Johansen (1988) procedure, Granger causality, variance decomposition and impulse response analyses. The results of their study indicate that these markets are not significantly linked to each other in the long run. In the short-run, all the ASEAN markets are significantly linked with each other except for the Indonesia. Malaysia appeared to be the most influential market while Singapore and Thailand were the markets with most linkages with other markets. The results also found that there is a bi-directional causality between Malaysia and Singapore, Singapore and Thailand, and Malaysia and Thailand as 206

5 Karim, M.Z.A. and Gee, C.S. Stock Markets Integration Between Malaysia and Trade Partners well as a uni-directional causality between the Philippines and Singapore. Cha and Oh (2000) in their study seek to determine the size of impact, the speed of transmission, and whether the Japanese or the United States markets had greater influence on Asian financial markets using the Vector Autoregression method with proper control for heteroscedasticity in analysing the relationships between all the markets under investigation. The results from their study indicated that the degree of association between the developed markets and the Asian emerging markets began to change after the October 1987 crash and the relationship had been significantly intensified since the outbreak of the Asian financial crisis in July Besides, the United States market began to have a more significant influence on the Hong Kong and Singapore markets since the crash in October However, the United States influences on the Korean and Taiwanese markets remained unchanged. The Japanese equity market did not have much impact on the four emerging markets in Asian until the recent financial crisis. Furthermore, the impact of both developed markets on the four markets increased dramatically since the outbreak of the crisis. Moon (2001) investigated the impact of 1997 Asian currency crisis on the stock market integration in East Asia and compared this with the European experienced of the European crisis. The result from his study suggests that the currency crisis in Asia and Europe had a contrasting effect on Asian and European markets. Moreover, market integration began to emerge in Asian after the currency crisis, whereas in Europe, the stock markets linkages appeared to be a temporary effect after the crisis. In addition to that, the integration of Asian markets with the United States market increased significantly after the currency crisis in both the long run and short run. Nevertheless, the integration between the European markets and the United States markets remain very limited.the analysis of inter-linkages among the Asian stock markets continued with Hashmi and Liu (2001) study on the integration among Southeast Asian, Tokyo and New York stock market returns before and after the Asian currency crisis. The results of their analysis found that the New York market exerted a strong influence on the region but is not much affected by it. The Tokyo market was found to be unrelated to the region, whereas Singapore emerged, as a leader in the region and its influences is stronger in the post-crisis period. The Kuala Lumpur Stock Exchange was found to be alienated from the region after the financial crisis due to the capital control measures implemented by the Malaysian government. On the other hand, the Bangkok Stock Exchange and the Jakarta Stock Exchange appeared to lead the region after the financial crisis, while Manila did not have much influence on other markets.meanwhile, Yang (2002) also studied the cointegration effects using a sample of East Asian countries namely, Hong Kong, Indonesia, Korea, Malaysia, Thailand, the Philippines, Singapore and Taiwan during the 1997 to 1998 financial crisis by employing the Vector Autoregression model, bivariate test and Granger causality. He found no long-term comovement among the East Asian stock markets. Besides, the result also suggests that there is a substantial increased in the degree of interdependence after the 1997 crisis. The result also indicates that Taiwan is a very independent market. Finally, Daly (2003) studied the static and dynamic interdependence of the stock markets in Indonesia, Malaysia, the Philippines, Singapore, Thailand, and the advanced stock markets such as Australia, Germany, and the United States using daily closing price from April 1990 until October 2001 by employing the correlation analysis as well as the Johansen bivariate and multivariate cointegration tests in his study. He found that all the stock markets were cointegrated in October 1997 financial crisis. Besides, correlation coefficient between all 207

6 Applied Econometrics and International Development Vol.6-3(2006) the stock market returns in the study increased significantly after the financial crisis except for Malaysia and Singapore. In addition, the average correlation between Australian stock market index, Dow Jones Industrial Averages index and German DAX with the combined market indices also increased significantly after the financial crisis. Finally, the stock markets became more integrated after the crisis in October 1997.In conclusion most of the studies found that the United States market is the most influential market in the world. Besides that, the countries with severe restrictions on international trade and investment seem to be alienated from the other stock markets in the region under investigation. Finally, the regional aspect does play a major role in the stock markets integration among the countries in the same region. 4. Data and Methodology This section outlines the data and methods used in measuring the integration between the Malaysian and its major trading partners stock market. Data. We employed data on major stock indices from the Philippines, Indonesia, Thailand, Hong Kong, Japan, China and the United States in analysing the integration of Malaysian stock market with all these countries. Table 5 in the Annex lists the countries major stock indices. The data required for the study were obtained from Thomson Datastream. The daily closing prices for all the stock indices are employed from January to December The sample is divided into three-time periods based on the study of Moon (2001) on currency crisis and stock market integration. The first period starts from January 4, 1994 to May 30, 1997, which represents the pre-crisis period. The second period starts from June 1, 1997 to February 26, 1999 in which the financial tensions are very high in June 1997 and the effects of financial turmoil became greater in 1998 due to the financial instability in Russia. The financial turmoil was eliminated in March Thus, the post-crisis period starts from March 1, 1999 until December 31, All the stock indices were converted to natural logarithm before any tests are performed. The numbers of lags employed were determined using Akaike Information Criterion (AIC) and Schwarz Criterion (SC). The trading hours of the United States market take place one calendar day before the other markets in this study. Therefore, we will lag the United States stock prices, namely S&P 500 by one day in performing the cointegration tests and causality tests between the United States and other markets following Huang, Yang, and Hu (2000). Methodology. Empirical tests for cointegration can only proceed if the time series are non-stationary. In this analysis, we will test all the series of indices for unit root properties using two commonly used unit root tests, namely Augmented Dickey-Fuller (ADF) test and Phillips-Perron (1988) test. For the ADF test, the null hypothesis of a single unit root is tested against the alternative of stationarity using the model stated in Equation 1. Y it 3 = α + βi + φ Y u (1) lt j= 1 j i, t j + Where: (Y it-j ) = Y i,t-j Y i, t-j-1, p = number of lagged values of first differences (Y it ), three lags will be included to account for serial correlation in the error term µ it. The Augmented Dickey-Fuller (ADF) test is conducted by including lagged values of (Y it ) (p 1) to ensure that the residual µ it is white noise. The number of lags included to account for serial correlation in the error term µ it will be determined using Akaike info 208 it

7 Karim, M.Z.A. and Gee, C.S. Stock Markets Integration Between Malaysia and Trade Partners criterion (AIC) and Schwarz criterion (SC). If the null hypothesis of unit roots is rejected, then the level of the series is I (1). In addition to the ADF test, we employ Phillips-Peron (PP) unit root test in testing the properties of unit root in all the variables used in this research. The PP test is used because it will make a correction to the t-statistic of the coefficient from the AR (1) regression to account for the serial correlation (Phillips and Perron, 1988). The bivariate cointegration test is carried out between the Malaysian stock market (KLSE CI) and the stock indices from the Philippines, Indonesia, Thailand, Singapore, Hong Kong, Japan, China, and the Unites States in order to gain an insight into the nature of the cointegration relationship between the Malaysian stock market and its major trading partners. The bivariate cointegration test employed in this study is based on Gregory and Hansen cointegration model. It is used to determine the presence of any long run relationship between two markets.the bivariate Vector Autorgression model (VAR) and Vector Error-Correction Models (VECM) is used to tests for the short and long run relationship between the Malaysian stock market and its major trading partners. The Vector Autoregression (VAR) model is employed in testing the lead lag relationship between Malaysia and its major trading partners stock markets in the absence of longterm equilibrium. The Granger (1969) model based on the bivariate VAR model shown in Equation 2 is used to test for the lead lag relationship between two price index series. y k k 1t = α 0 + α1i y1t i + α 2i y 2t i i= 1 i= 1 k k 2t = β0 + β1i y1t i + β2i y 2t i i= 1 i= 1 + ε y + ε (2) In this context, y 1t and y 2t denote stock prices indices of two different sectors or countries, and ε 1t and ε 2t are assumed to be serially uncorrelated with zero mean and finite covariance matrix. Failing to reject the null hypothesis H 0 : α 11 = α 21 =0 implies that y 2t does not Granger cause y 1t. On the other hand, failing to reject the null hypothesis H 0 : β 11 = β 21=0 implies that y 1t does not Granger cause y 2t. Engle and Ganger (1987) pointed out that in the presence of cointegration, there always exists a corresponding error-correction representation. This means that the change in the dependent variable is a function of the level of disequilibrium in the cointegrating relationship. The cointegrating relationship is captured by the error-correction term and changes in other explanatory variables. This idea is being exploited in the studies of stock markets integration in which there may exist comovement among a set of time series and possibilities that they will tend to move together in finding stable long run equilibrium. Thus, this study is used the Ganger representation theorem in testing the relationship of the cointegrating variables using Vector Error-Correction Models (VECM) for both bivariate and multivariate. Equation 3 presents the bivariate error-correction model. y k k 1t = α 0 + δ1(y1t 1 y 2t 1 ) + α1i y1t i + α 2i y 2t i i= 1 i= 1 k k 2t = β0 + δ 2 (y1t 1 y 2t 1 ) + β1i y1t i + β2i y 2t i i= 1 i= 1 1t 2t + ε y + ε (3) The δ 1 and δ 2 represent the speeds of adjustment to equilibrium. According to Engle and Granger (1987), the existence of the cointegration implies causality among the set of variables as manifested by δ + δ 0. Failing to reject the null hypothesis H 0 : α 11 = 1 2 > 1t 2t 209

8 Applied Econometrics and International Development Vol.6-3(2006) α 21 =0 implies that y 2t does not Granger cause y 1t. On the other hand, failing to reject the null hypothesis H 0 : β 11 = β 21=0 implies that y 1t does not Granger cause y 2t. According to Masih and Masih (1999), the used of F and t-tests in Vector autoregressions are meant for within-sample causality tests. Hence, impulse response function and variance decomposition is conducted for further analysis into the degree of cointegration among the indices. The impulse response function is used to trace the effects of a shock to an endogenous variable on the variables in the VAR. On the other hand, variance decomposition is employed in decomposing variation in an endogenous variable into the component shocks to the endogenous variables in the VAR. It contains crucial information about the relative importance of each random innovation to the variation in the VAR. 5. Empirical Results Table 6 in the Annex illustrates the results of unit root tests for both Augmented Dickey- Fuller test and Phillips-Perron test in levels and first-differences for each of the sample country s stock indices employed in this research using daily data from January 1994 until December The results indicate that we cannot reject the null hypothesis of unit root at the 1% critical value for each of the country s stock indices in levels. When we difference the series and test for unit root, the null hypothesis is rejected at the 1% critical value. Hence, each of the countries stock indices follow I (1) process based on the results obtained from ADF and Phillips-Perron (1988) test. It is possible that the combinations of the share prices series have cointegration property. Hence, we will proceed with the cointegration tests in testing for the cointegration between the stock prices, which are non-stationary in levels but stationary in first-differences. The bivariate cointegration test is carried out between the KLSE CI and the stock indices of Malaysia s major trading partners in order to gain more understanding into the nature of the cointegration relationship between the stock prices between these countries. It is used to determine the presence of any long run relationship between two markets. These markets are said to exhibit long run causal relationship if we reject the null hypothesis of no cointegration between the stock markets in this study. Table 7 in the Annex presents the results for bivariate cointegration test between the Malaysian stock index and its major trading partners stock indices for the full sample period, pre-crisis period, during crisis period and post crisis period. The results shown in Table 7 indicate that the null hypothesis of no cointegration cannot be rejected for full sample period for all the stock markets indices. However, long run relationship exists between the Malaysian and the Philippines stock market as well as between the Malaysian and the United States stock market at the 1% and 5% significance level respectively during the pre-crisis period. The results also indicate that there is no cointegration relationship between the daily stock indices from various countries during the crisis period. For the post-crisis period, the Malaysian and the Thai stock index are cointegrated at the 5% significance level. In addition, the Malaysian stock index is found to be cointegrated at the 1% significance level with the stock index in Indonesia and China. The causality test is used to examine the short-term and long-term dynamic causal linkages between Malaysia and its major trading partners stock markets. The bivariate causality tests employed in this study are bivariate VAR and ECM based on Equation 2 and 3 in testing for the short-run and long run causality respectively among Malaysia and its major trading partners stock price 210

9 Karim, M.Z.A. and Gee, C.S. Stock Markets Integration Between Malaysia and Trade Partners indices. The results of the bivariate VAR based on countries daily price indices each of the sample period are presented in Table 8. Table 8: Bivariate VAR for Daily Countries Price Indices Null Hypothesis Full Sample Pre-Crisis During Crisis Post-Crisis F-stat P- F-stat P- F-stat P- F- P- Value Value Value stat Value My not cause Ph 8.98** ** PH not cause MY * 0.03 MY not cause ID ** ID not cause MY 4.71** * MY not cause TH ** TH not cause MY 3.50* * * MY not cause HK ** HK not cause MY ** MY not cause JP JP not cause MY MY not cause CN ** CN not cause MY MY not cause US US cause MY ** Notes: * Indicates significance at 5% level ** Indicates significance at 1% level The null hypothesis of the daily price movement in the Malaysian stock market do not Granger cause the daily price movement in the Philippines stock market is rejected at the 1% significant level during the full sample period. The results also indicate that the Indonesian stock market and the Thai stock market does Granger cause the daily price movement of the Malaysian stock market in the short-run from January 1994 to December When the analysis is divided into three sub-periods, the results show that the Malaysian stock market, namely the KLSE composite index does lead the daily price movement in the Indonesian, Thailand, Hong Kong and China stock markets for the period before the financial crisis at the 1% significance level. Thus, there exist short-run causal relationships in these markets. The leading role of the Malaysian stock market in the Philippines, Indonesia and China can be explained by the relatively big amount of equity investments from Malaysia to these three countries compared to equity investment from these countries to Malaysia (Figure 1). The results are consistent with the study done by Roca et al. (1998) on the interdependence between the ASEAN equity markets in Roca et al. (1998) findings suggest that Malaysian, Thai and the Philippines stock markets have close linkages with each other. The results also indicate that the daily price movement of the Thai, Hong Kong, and the United States stock markets Granger cause the daily price movement in Malaysian stock market for the period before the financial crisis. Hence, there exists a bi-directional short-run relationship between Malaysian stock 211

10 Applied Econometrics and International Development Vol.6-3(2006) market with the daily price movement of the Thai and Hong Kong stock markets. This result is also consistent with Roca et. al. (1998), which found the existence of bidirectional relationship between the Malaysian and Thai stock markets. This can also be explained through the equity investments among these countries. As indicated by Figure 1, there is not much difference between the equity investments from Malaysia to Hong Kong and Thailand compared to investment from Hong Kong and Thailand to Malaysia. Figure 1: The Equity Investment from and to Malaysia During the Pre-Crisis Period RM (Millions) From To United States Indonesia Philippines Thailand China Hong Kong Japan Country Source: Monthly Statistical Bulletin, Bank Negara Malaysia (January 2003 & 2004) Furthermore, Masih & Masih (2001) found that the Hong Kong market is a dominant regional market and generator of influential information in the Asian region due to the reason that this market is characterised by higher liquidity and lower transaction costs. This may be the reason why the Malaysian stock market is being led by the Hong Kong stock market. The United States is found to Granger cause the stock market in Malaysia due to a relatively large amount of equity investments placed by the United States in Malaysia. On the other hand, the daily price movement in the Malaysian stock market seems to Granger cause the price movement in the Philippines stock market during the Asian financial crisis in the short-run. The Indonesian and the Thai stock markets are also found to lead the price movement in the Malaysian stock market during the Asian financial crisis in the short-run. This may be due to the fact that the Financial Crisis in 1997 was initiated in Thailand with the attack on Thai bath. The crisis forced the depreciation of Thai baht, followed by a serious attack on the Indonesian rupiah and then spread to Malaysia (BNM, 1999). The short-run causal relationship between the Malaysian stock market and the stock markets of its major trading partners started to weaken after the financial crisis. The results in Table 7 only suggest that the daily price movement of the Philippines stock market leads daily price movement of the Malaysian stock market after the financial crisis at the 5% significant level. Based on the result obtained from bivariate cointegration test, the bivariate errorcorrection (ECM) test is conducted to examine for the long run relationship between two 212

11 Karim, M.Z.A. and Gee, C.S. Stock Markets Integration Between Malaysia and Trade Partners countries indices, which are cointegrated. Therefore, we test for the causality by pairing up the Malaysian stock market index with the stock markets indices from related countries. The results for bivariate ECM based on daily countries price indices for the pre-crisis period, and post-crisis period are presented in Table 9 since there is no cointegration relationship found for the full sample and during crisis period. Table 9: Bivariate ECM for Daily Countries Price Indices Pre-Crisis Post-Crisis F-stat ECT t-1 F- ECT t-1 stat C t-stat MY does not cause PH 5.04** ** PH does not cause MY * C t-stat MY does not cause ID ID does not cause MY ** MY does not cause TH TH does not cause MY ** MY does not cause CN * CN does not cause MY Notes: * Indicates significance at 5% level,** significance at 1% level, c= coefficient The results indicate that the daily price movement of Malaysian stock market leads the price movement in the Philippines stock market for period before the financial crisis in the long run. The error-correction term shows that about 4.59% of disequilibrium is corrected negatively each day by changes in the Philippines stock market. Nevertheless, there is no long run causal relationship among the countries stock markets, which are cointegrated with Malaysia stock market for period after the financial crisis. Table 10 and 11 in the Annex summarises the variance decomposition findings of 1-day to 10-day ahead forecasts between the Malaysian stock market and its major trading partners for the time periods of pre-, during-, and post-crisis in analyzing the degree of movement in one market by the others. The discussion focuses on the 10-day ahead forecast results. From the results in Table 10, we can see that the Malaysian stock market is relatively stable and robust to the shock exerted by its major trading partners for all the time periods. This is because the degree of movement in the Malaysian stock market to the innovation by other major trading partners is less than two percent of the forecast error variance. The degree of cointegration between the Malaysian market and its major trading partners stock markets increases substantially during the financial crisis. Nevertheless, the degree of integration started to decrease after the financial crisis. This is consistent with the causality tests results. After the financial crisis, it is found that the United States, Japanese, Chinese and the Philippines stock markets Granger cause the movement in daily price index in Malaysia. However, the degree of cointegration is less than one percent. The results in Table 11 clearly indicate that the price movement in the 213

12 Applied Econometrics and International Development Vol.6-3(2006) Malaysian stock market has a strong influence towards the stock markets in Hong Kong, Indonesia and Thailand. This is consistent with the results that we obtained from the causality tests. With a 10-day horizon, the forecast error variance explained by the Malaysian stock market in other markets ranges from 32.35% for Hong Kong, 21.93% for the Indonesian stock market, and 17.71% for the Thailand stock market before the financial crisis. Nevertheless, the influence of the Malaysian stock market to the stock markets of its major trading partners starts to decrease during the financial crisis and decreased further after the financial crisis. This may be due to the effect of the implementation of selective exchange control measures by the Malaysian government. Figure 2 in the Annex presents the impulse response function of the Malaysian stock market to the shock from its major trading partners stock markets for the time periods of pre-, during-, and post-crisis. The results in Figure 2 indicate that the Malaysian stock market did not respond much towards the shock exerted by the stock markets of its major trading partners. The Malaysian stock market only responds to the shock in day-2 and the adjustment to the original equilibrium happens within three to four day time horizon. Figure 3 in the Annex illustrates the impulse response function of the Malaysia s major trading partners stock markets to the shock from Malaysian stock market for the time periods of pre-, during-, and post-crisis. The results clearly illustrate that all the stock markets of the Malaysia s trading partners respond positively to the shock in the Malaysian stock market during all the three time periods. The Malaysian stock market have a strong influence towards the stock markets in Thailand, Hong Kong and Indonesia for all the three time periods. Besides, all the stock markets adjust itself to the original equilibrium within 3 to 4 days before the financial crisis. The speed of adjustment is faster after the financial crisis with the speed of adjustment of less than 3-day time horizon since the influence of the Malaysian stock market decreases after the financial crisis.from the variance decomposition of the VAR model we found that Malaysian stock market is relatively stable and robust to the shock exerted by its major trading partners for all the time periods. Nevertheless, the influence of the Malaysian stock market on the stock markets of its major trading partners starts to decrease during the financial crisis and decreased further after the financial crisis. This may be due to the effect of the implementation of the selective exchange control measures by the Malaysian government.the results of the impulse response functions suggest that the Malaysian stock market did not respond much towards the shock exerted by the stock markets of its major trading partners. However, the results show that all the stock markets of the Malaysia trading partners respond positively to the shock in the Malaysian stock market in all of the three time periods. The Malaysian stock market seems to have a strong influence on the stock market in Thailand, Hong Kong and Indonesia in all of the three time periods although the influence decreases after the financial crisis. The results of variance decomposition suggest that there are no contagion 1 effect between Malaysia and its major trading partners before and after the financial crisis in July 1997 as the degree of cointegration and the number of stock markets being cointegrated decreased after the financial crisis. 1 According to Forbes and Rigobon (1999) the contagion effect happens when two markets show a moderate degree of comovement during periods of stability and the shock to one market leads to a significant increase in market comovement. 214

13 Karim, M.Z.A. and Gee, C.S. Stock Markets Integration Between Malaysia and Trade Partners 6. Conclusion In this paper we have examined the stock market linkages between Malaysia and its major trading partners. Our main concern is to see whether there have been any significant changes in the degree of stock market integration between them. The results of the bivariate cointegration test on countries stock indices indicates the existence of a long run relationship between Malaysian and the Philippines stock markets as well as between Malaysian and the United States stock markets for period before the financial crisis. The results also indicate that there is no cointegration relationship between the stock market indices for period of financial crisis. Before the 1997 financial crisis, the daily price movement of Malaysian stock market is found to lead the daily price movement in Indonesia, China in the short-run, and the Philippines in the long run. In addition, there is a bi-directional relationship between Malaysia and the stock markets in Hong Kong and Thailand. Two conclusions can be made from the results of this study. First, with a few exceptions, there are no evidence of monotonous relationship between trade linkages and stock market integration. Second, the short-run causal relationship between the Malaysian stock market and the stock markets of its major trading partners started to weaken after the financial crisis. Such finding is highly attributable to the fact that Malaysia s imposition of capital control in September 1998 in their attempt to curb speculative attacks had been relatively successful in shutting out foreign influences. This result is consistent with Hashmi and Liu (2001) study. In addition, the variance decomposition results of the Malaysian stock market and its major trading partners suggest that the Malaysian stock market is relatively stable and robust to the shock exerted by its major trading partners for all the time periods. This is because the degree of movement in the Malaysian stock market to the innovation by the other major trading partners is less than two percent of the forecast error variance. The degree of cointegration between the Malaysia market and its major trading partners stock markets, which increases substantially during the financial crisis starts to decrease after the financial crisis. This is consistent with the causality tests results. References Arshanapalli, B., & Doukas, J. (1993). International stock market linkages: Evidence from the preand post-october 1987 period. Journal of Banking & Finance, 17, Bank Negara Malaysia (BNM). (1999). The central bank and the financial system in Malaysia (1st edn.). Bank Negara Malaysia, Kuala Lumpur. Bank Negara Malaysia (BNM). (Various Issues). Monthly Statistical Bulletin of Bank Negara Malaysia. Bank Negara Malaysia, Kuala Lumpur. Blackman, S.C., Holden, K., & Thomas, W.A. (1994). Long-term relationships between international share prices. Applied Financial Economics, 4, Byers, J.D., & Peel, D.A. (1993). Some evidence on the interdependence of national stock markets and the gains from international portfolio diversification. Applied Financial Economics,3, Cha, B., & Oh, S. (2000). The relationship between developed equity markets and the Pacific Basin s emerging equity markets. International Review of Economics and Finance, 9, Chan, K.C., Gup, B.E., & Pan, M.S. (1997). International stock market efficiency and integration: A study of eighteen nations. Journal of Business, Finance & Accounting, 24(6), Choudhry, T. (1996). Interdependence of stock markets: evidence from Europe during the 1920s and 1930s. Applied Financial Economics, 6,

14 Applied Econometrics and International Development Vol.6-3(2006) Chowdhury, A.R. (1994). Stock market interdependencies: Evidence from the Asian NIEs. Journal of Macroeconomics, 16(4), Corhay, A., Rad, A.T., & Urbain, J.P. (1995). Long run behaviour of Pacific-Basin stock prices. Applied Financial Economics, 5, Daly, K.J. (2003). Southeast Asian stock market linkages: Evidence from pre- and post- October ASEAN Economic Bulletin, 20(1), Darbar, S.M., & Deb, P. (1997). Co-movements in international equity markets. The Journal of Financial Research, 20(3), Diebold, F.X. (2001). Element of Forecasting (2 nd ed). Ohio: South-Western. Engle, R., & Granger, D.W.J. (1987). Co-integration and error correction: Representation, estimation and testing. Econometrica, 50, Eun, C.S., & Shim, S. (1989). International transmission of stock market movements. Journal of Financial and Quantitative Analysis, 24(2), Forbes, K., & Rigobon, R. (1999). No contagion, only interdependence: Measuring stock market co-movements. Working Paper 7267, NBER. Fűss, R. (2002). The financial characteristics between`emerging and `developed equity markets. Paper presented at Policy Modeling International Conference, Brussels. Ghosh, A., & Johnson, K.H. (1999). Who moves the Asia-Pacific stock markets US or Japan? Empirical evidence based on the theory of cointegration. The Financial Review, 34, Hashmi, A.R., & Liu, X. (2001). Interlinkages among South East Asian stock markets (A comparison between pre- and post-1997-crisis periods. Paper presented at X International "Tor Vergata" Conference on Banking and Finance, University of Rome. Hassan, M.K., & Naka, A. (1996). Short-run and long-run dynamic linkages among international stock markets. International Review of Economics and Finance, 5(4), Huang, B.N, C.W. Yang, and W.S. Hu (2000). Causality and Cointegration of Stock Markets among the United States, Japan, and the South China Growth Triangle. International Review of Financial Analysis, 9(3), pp Johansen, J., & Juselius, K. (1993). Testing structural hypothesis in a multivariate cointegration analysis of PPP and the UIP for UK. Journal of Econometrics,53, Koch, P.D., & Koch, T.W. (1991). Evolution in dynamic linkages across daily national stock indexes. Journal of International Money and Finance, 10, Masih, A.M.M., & Masih, R. (1999). Are Asian stock market fluctuations due mainly to intraregional contagion effects? Evidence based on Asian emerging stock markets. Pacific-Basin Finance Journal, 7, Moon, W.S. (2001). Currency crisis and stock market integration: A comparison of East Asian and European Experiences. Journal of International and Area Studies, 8(1), Phillips, P.C.B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75, Ratanapakorn, O., & Sharma, S. C. (2002). Interrelationships among regional stock indices. Review of Financial Economics, 11, Roca, E.D., Selvanathan, E.A., & Shepherd, W.F. (1998). Are the ASEAN equity market interdependent? ASEAN Economic Bulletin, 15(2), Yang, T. (2002). Crisis, contagion, and East Asian stock markets. Economics and Finance, 1, Online References: Kuala Lumpur Stock Exchange (2003). Industry Profiles. Retrieved August 23, 2003, from Kuala Lumpur Stock Exchange web site: Kuala Lumpur Stock Exchange (2003). Listing Statistics. Retrieved August 23, 2003, from Kuala Lumpur Stock Exchange web site: Annex at the journal website: 216

15 Karim, M.Z.A. and Gee, C.S. Stock Markets Integration Between Malaysia and Trade Partners Annex Table 1: Malaysian Total Trade with Major Trading partners (RM Billion) US China Hong Japan Philippines Thailand Indonesia Singapore Kong Year Table 2: Number of Companies Listed in the Main Board of KLSE and Market Capitalisation from 1990 to 2002 Year Number of Companies 1 Market Capitalization 2 (RM Billion) Source: 1 Kuala Lumpur Stock Exchange and Web Page: 2 Statistical Monthly Bulletin of Bank Negara Malaysia (July2003) 217

16 Applied Econometrics and International Development Vol.6-3(2006) Table 4: Percentage of Equity Investment by Malaysia with its Major Trading Partners from 1995 to 2001 Year Japan Thailand Indonesia China United States Hong Kong Philippines Total (%) Source: Statistical Monthly Bulletin of Bank Negara Malaysia (July2003) Table 5: The Countries Major Stock Indices in Studying the Integration of Malaysian Stock Market with its Major Trading Partners Countries Major Stock Indices Malaysia Kuala Lumpur Stock Exchange (KLSE) The Philippines Philippines Stock Exchange (PSE) Indonesia Jakarta Stock Exchange (JSE) Thailand Bangkok Stock Exchange (BSE) Hong Kong Hang Seng Composite (HS) Japan Nikkei 225 Stock Average (Nikkei 225) China Shenzhen Se A Share (SSE) United States S&P 500 Composite (S&P 500) Table 6: Unit Root Tests on Levels and First-Differences for All Countries Stock Indices 218

17 Karim, M.Z.A. and Gee, C.S. Stock Markets Integration Between Malaysia and Trade Partners Country Indices ADF Test Phillips-Perron Test Level First-Differences Level First-Differences Constant Constant, Constant Constant, Constant, Constant, Constant, no Constant no trend, trend no trend trend no trend, trend trend, trend Malaysia ** ** ** ** Philippine s ** ** ** ** Indonesia ** ** ** ** Thailand ** ** ** ** Hong Kong ** ** ** ** Japan ** ** ** ** China ** ** ** ** United States ** ** ** ** Notes: * Indicates significance at 5% level** Indicates significance at 1% level Table 7: Bivariate Cointegration Test Between Malaysia Stock Index and Stock Indices of its Major Trading Partners Daily Full Pre- During Post- Null Sample Crisis Crisis Crisis Countries Hypothesis Trace Trace test Trace test Trace test test Malaysia r= ** Phillipines r Malaysia r= ** Indonesia r Malaysia r= * Thailand r Malaysia r= Hong Kong r Malaysia r= Japan r Malaysia r= ** China r * Malaysia r= * United States r Notes: * Indicates significance at 5% level** Indicates significance at 1% level 219

18 Applied Econometrics and International Development Vol.6-3(2006) Table10: Forecast Variance Decomposition Response for the Malaysian Stock Market to the Innovations of its Major Trading Partners Market Horizon By Innovations In Explained (in days) My Th Cn Id Hk Jp Ph US Pre-Crisis My During Crisis My Post-Crisis My

19 Karim, M.Z.A. and Gee, C.S. Stock Markets Integration Between Malaysia and Trade Partners Table 11: Forecast Variance Decomposition Response for Malaysian Major Trading Partners to the Innovations of the Malaysian Stock Market By Horizon Market Explained Innovations (in In days) My Th Cn Id Hk Japan Ph US Pre-Crisis My During Crisis My Post-Crisis My

20 Applied Econometrics and International Development Vol.6-3(2006) Figure 2: Impulse Response Function of the Malaysian Stock Market During Pre-, During-, and Post-Crisis Pre-Crisis Response to One S.D. Innovations ± 2 S.E. Response of D(LNMAL) to D(LNMAL) Response of D(LNMAL) to D(LNTHAI) Response of D(LNMAL) to D(LNCHINA) Response of D(LNMAL) to D(LNINDO Response of D(LNMAL) to D(LNHK) Response of D(LNMAL) to D(LNJAPAN) Response of D(LNMAL) to D(LNPHIL) Response of D(LNMAL) to D(LNUS) During-Crisis Response to One S.D. Innovations ± 2 S.E. Response of D(LNMAL) to D(LNMAL) Response of D(LNMAL) to D(LNTHAI) Response of D(LNMAL) to D(LNCHINA) Response of D(LNMAL) to D(LNINDO) Response of D(LNMAL) to D(LNHK) Response of D(LNMAL) to D(LNJAPAN) Response of D(LNMAL) to D(LNPHIL) Response of D(LNMAL) to D(LNUS)