CHAPTER VI INTEGRATION OF INDIAN STOCK MARKETS WITH MAJOR WORLD STOCK MARKETS

Transcription

1 CHAPTER VI INTEGRATION OF INDIAN STOCK MARKETS WITH MAJOR WORLD STOCK MARKETS 6.1 Introduction Over the past few years, financial markets have become increasingly global. This process began with the relaxation of controls on capital movements in 1960's and was followed, especially during the past two decades by the formal relaxation of exchange controls. This has been further enhanced by the major advancements in technology and the development of financial techniques and hedging instruments that facilitate domestic and cross-border trading in marketable financial instruments. Financial integration in the context of India s financial liberalization is important because the country has become a crucial player in the world economy with its phased liberalization and financial reform programme since However, only with an empirical analysis, we would be able to evaluate exactly the effect of these financial liberalization processes on integration of domestic stock market with global stock markets. Thus, this chapter mainly focused on the integration of the stock market of India with the developed countries stock markets, namely, US, UK, Australia, France, Germany and Japan, especially after the initiation of economic and financial reforms. This chapter has the following sub parts. First part deals with the concept and effects of financial integration. The second part deals with the literature review on the impact of financial integration on economic growth and various factors influencing the process of integration of domestic financial markets with global markets. The third part examines the data and methodology of empirical analysis of integration of Indian stock market with selected developed countries stock markets. The fourth part deals with the results and their interpretation and the final part concludes the chapter. 174

2 6.2.1 Concept and effects of financial market integration Financial market particularly capital market integration is defined as the inter linkage and unimpeded access to capital markets across countries. Integration of financial markets domestically as well as internationally can be measured in terms of equalization of returns on similar financial assets or it can be seen as the co-movement of similar kinds of financial assets. However, measuring capital market integration empirically is difficult. Due to the increasing interdependence of major financial markets all over the world, the transmission of stock return movements among the major national markets has become a much researched topic and is commonly termed as international stock market integration (Bekaert and Hodrick,1992). The integration of financial markets across boundaries had been initiated by the capital market integration in developed countries. As a consequence of gradual liberalization of India s financial sector, India too has become a part of the world-wide integrated financial system. Also, revolution in Information Technology has been playing a crucial role for connecting financial activities across countries. Conventionally, firms depended solely on banks for external financing, but the development of the capital market and the worldwide linkage of the financial sector have opened up an alternative possibility firms can now raise funds either by issuing equity or bonds, domestically as well as internationally (Bora et al, 2009). Financial integration has become an important policy issue because it helps in efficient transmission of different monetary policy effects and provides an opportunity to diversify investment, thereby pooling risk and channelizing liquidity across markets. On the contrary, it might lead to the collapse of an entire economy following the downfall of a few financial institutions. In the post-liberalization era, the worldwide integrated capital market has opened up the possibility of a crisis spreading out from the domestic periphery of the country in which it originates. Any shock in one country might cause the flight of capital from other integrated countries, affecting the asset value of corporate entities and reducing the creditworthiness of firms. As a consequence, banks could lose 175

3 confidence and become reluctant to lend money, which might create a credit crunch, bring down production and employment, and so on. Besides, some other effects could operate through reduction of the size of the export market and a fall in foreign exchange earnings. The trade-off could be viewed from three major perspectives of inter linkage one, among domestic financial market segments; two, among financial markets across borders; and three, between the financial sector and the real sector. There might be little doubt about the positive effect of integration among the domestic segments of a financial market as it leads to the operational efficiency of intermediaries through proper allocation of resources, in turn contributing to financial stability. But cross-country financial linkages, newer and newer forms of financial instruments and immense securitization of debts add to the existing debate on international flow of capital by posing a threat to the stability of financial system. People are more prone to invest in securities to earn huge returns in a short period of time, making financial systems more volatile. Hence, it is a very important policy decision to retain a more liquid and integrated capital market system without disturbing the stability of its economy (Marashdeh, 2005). The Indian capital market has witnessed a major transformation and structural change from the past two decades as a result of economic and financial sector reforms initiated by the Government of India since Along with various measures, opening up of the home market for the foreign investors is one of the important steps taken by the Indian Government that has lead the Indian stock market to be strongly integrated with the stock market of the rest of the world. There are mainly two different aspects in the field of stock market integration one is how the degree of integration among the markets varies over time, and the second is what are the main factors or the forces behind such process. Early research focused exclusively on how two national equity markets are interrelated and how the degree of integration varies over a different periods of time with a special emphasis on the impact of some special events, such as stock market crisis, on the co-movement of prices internationally. But, to make a comprehensive study on international stock market integration, one should focus on both the degree of integration over different periods of time and the possible factors or the 176

4 driving forces behind such international integration process. Identifying the possible forces behind the interdependence of emerging stock markets all over the world can add value both for international investors and for policy makers. International investors, with the knowledge of the significant forces, can have an idea of the potential risk and rewards of global diversification. At the same time, the policy makers need to understand whether such interdependence is just due to contagion, or there are some fundamental factors that can explain such process. Stock market interdependence simply due to contagion may cause for irrational capital outflows and may reduce the benefits of financial liberalization(agarwal, 2001) The effect of financial integration on financial development Financial integration should increase the supply of finance in the less financially developed countries of the integrating area. This may occur either because it brings more efficient intermediaries closer to the firms in backward areas (by facilitating their entry) or because it enables these same firms to access more distant financial markets. In either case, firms in less financially developed countries will face easier and cheaper access to external finance in either the local market or in the broader, integrated one, and this should spur capital accumulation and economic growth. Financial integration is likely to spur the efficiency of the financial intermediaries and markets of less financially developed countries. To the extent that greater efficiency stimulates the demand for funds and for financial services, this should also translate into an increased size of domestic financial markets. The main channel through which this effect should operate is the increased competition with more sophisticated and cheaper foreign intermediaries, associated with financial integration. Competitive pressure from these intermediaries should reduce the cost of financial services to the firms and households of countries with less developed financial systems, and thus expand the quantity of the local financial markets. (Arshanapalli and Dukas 1993). 177

5 As financial integration proceeds, the most financially developed countries will share the services provided by their financial system with the other integrating countries. The economies of scale and the external economies involved in financial intermediation can be a powerful fuel for the expansion of the established intermediaries and markets of the more developed markets. As these become more integrated, firms of less financially developed countries can access more easily major financial centres by listing their shares on foreign stock exchanges. (Arshanapalli and Dukas 1993). 6.3 Literature Review on financial market (or stock market) integration Integration of financial markets domestically as well as internationally can be measured in terms of equalization of returns on similar financial assets or it can be seen as the co-movement of similar kinds of financial assets. Graham et al(2012) examines the integration of 22 emerging stock markets, located in America, Asia, Middle East/Africa, with the US market between 2001 to 2009 using the three dimensional analysis of wavelet coherency. The results of the study find a high degree of co-movement at relatively lower frequencies between the U.S. and the 22 individual emerging markets. However, the strength of co-movement, however, differs by country. A high degree of co-movement was observed between the US and Brazil, Mexico and Korea, and low co-movement were observed with US and Egypt and Morocco. The study also documents a general change in the pattern of the market relationship after 2006, where it detected co-movements at relatively higher frequencies. The findings of the study imply that investing selectively in emerging markets may provide significant diversification benefits which, invariably, depend on the investment horizon. Zulkefly and Bakri (2008) examines the stock market integration among Malaysia and its major trading partners, namely, United States, Japan, Singapore and China by employing cointegration tests and VECM approach in investigating the dynamic linkages between markets using weekly data for the period from 1998 to

6 The findings of the study indicate that Malaysia stock market is significantly influenced by the stock market development from the major trading partners. The empirical findings of the study are consistent with the view that stronger the bilateral trade ties between two countries, the higher the degree of co-movements. Since the markets move towards a greater integration, there are no opportunities for international portfolio diversification. In addition, any development in the stock market from major trading partners cannot be ignored and should be taken into consideration by the Malaysian government in designing an appropriate policy in the domestic stock market. Phylaktis and Fabiola(2004) examines stock market linkages of a group of Pacific-Basin countries with U.S. and Japan for the period from 1980 to 1998 using the multivariate cointegration model in both the autoregressive and moving average forms. The paper attempts to identify how the financial links have evolved during the 1980 s and 1990 s and whether they bear any relationship to the existence of foreign exchange restrictions and whether alternative financial vehicles, such as Country Funds, provide a channel through which international investors access capital markets. The results of the study indicate that the stock markets were not linked during the 1980s and 1990s indicating that the relaxation of foreign ownership restrictions was not sufficient to attract foreign investors' attention and that other factors must have affected the portfolio diversification decision. The results of the 1990 s suggest that the relaxation of the restrictions might have strengthened international market interrelations and Country Funds have provided access to highly regulated capital markets. Bora et al(2009) examines the emerging market indices of Brazil, Russia, India, China, and Argentina (BRICA) and investigates the linkages among the stock markets of the BRICA countries and their relations with the US market for the period from 2002 to The study uses the vector auto regression (VAR) techniques to model the interdependencies and Granger causality test to find evidence of a short-run relationship between these markets and the Impulse Response test to evaluate the persistence of shocks by using daily data. The findings of the study show that the US market has a significant effect on all BRICA countries in the same trading day. The most integrated 179

7 markets to the BRICA countries are Russia and Brazil; the least integrated ones are China and Argentina. The Granger causality test supports the VAR calculations and shows that Russia influences all other countries and Brazil affects Argentina, Russia and India. China only affects Argentina and Russia. The Impulse response test shows that all countries respond to an anticipated shock immediately and recover in nearly five or six days. Surianor et al(2011) examines the linkages of stock prices and benefits of diversification between the Malaysian equity market and the developed equity markets, namely, United States, Japan, the United Kingdom, China, France, Hong Kong, Germany, Canada, Switzerland, Australia and Spain for the period from 1996 to 2007 using the standard cointegration analysis, Unit root Test and Granger Causality Test. The study also analyses the influence of financial crisis. The findings imply that Malaysian investors would have little scope to include stock of US, Japan or Hong Kong as it has minimal benefits of diversification, as the markets move towards a greater integration. For policy making, any sensations in the United States, Japan and Hong Kong equity markets should be taken into consideration by the Malaysian authorities in designing Malaysian policies. Agarwal(2001) examines the impact of financial integration in India on its capital market in terms of growth, volatility and market efficiency. The results of the study show that the Indian stock market is still poorly integrated with the developed international capital markets. The primary stock market has grown significantly since the beginning of capital market reforms in The secondary capital market has also grown in terms of size and liquidity. The annual volatility in stock prices is found to have declined and the Industry-wise volatility, as measured by beta, is found to be greater than unity after reforms mainly in metals and metal products, and finance and investment industries. The regression results do not support the random walk model of market efficiency. 180

8 Azman-Saini et al(2002) attempted to empirically investigate the existence of long-run relationships among the ASEAN-5 equity markets, namely, Indonesia, Malaysia, Philippines, Singapore and Thailand using weekly data for the period from 1988 to 1999 using Unit root tests involving both Augmented Dickey Fuller(ADF) and Phillips and Perron (PP) tests, cointegration test and the Johansen and Juselius (JJ) maximum likelihood procedure. The results of the study show that the Singapore equity market was not affected by other markets except by the Philippines in the long run. Also, the result shows that there exist opportunities for beneficial international portfolio diversification within the context of the Asean-5 equity markets. Raj et al(2010) examines the integration of European equity markets for the period from 1988 to 2002 using Dynamic Eigenvalue Analysis, The Haldane and Hall Kalman Filter Procedure and Time Varying Cointegration Analysis. The results show that there is a the long run integrative relationships governing the European markets began to strengthen only in the late 1990 s and in particular since This evidence showed that despite several years of political willingness by European leaders to integrate economies, the importance of yielding power (the Treaty of Amsterdam) and yielding policy instruments (the establishment of the ECB) emerged as the only clear, important and credible signals of European integration as reflected in equity market behaviour. Alagidede et al(2011) attempted to investigate the extent of integration between African stock markets and the rest of the world using parametric and non-parametric test(long-run correlation estimator and Johansen trace test and the Breitung and Taylor non-parametric test for cointegration. The study finds that there are few long-run relationships between African markets, and also between Africa and the rest of the world which implied that international stock market shocks have little effect on African stock markets in the time series sense. Park(2010) attempted to investigate the linkages between equity markets of 11 Asian countries, including Thailand, Malaysia, Indonesia, Singapore, the Philippines, 181

9 Korea, Japan, China, Hong Kong, Taiwan, and India to the U.S. equity market for the period from 2005 to The study found high correlation coefficients across the Asian markets, reflecting strong co-movement of the Asian markets. Among those, the countries with more developed financial systems, namely, Japan, Singapore, and Hong Kong, exhibited stronger linkages to the rest of the Asian markets. China, conversely, evidenced the lowest correlation with other Asian markets. The linkages were stronger for the East Asian markets than for the ASEAN markets. A comparison of the results between the first ( ) and second ( ) sub-periods reveals a recent strengthening of the Asian markets. Additionally, the study found a significant mean spillover effect from the U.S. equity market to all 11 of the Asian markets. Also, it was seen that the stock markets of the Philippines and Japan were the most sensitive to daily changes in U.S. market returns, and the Hong Kong, Korea, Indonesia, Singapore, Taiwan, and India markets are next in respective order in terms of U.S. influence. The influence of the U.S. on the stock markets of Thailand, Malaysia, and China is relatively weak. The mean spillover effect has increased significantly from the first period ( ) to the second period ( ) for most Asian countries, with the exception of Thailand, Indonesia, the Philippines, and Taiwan, where the U.S. market influence is slightly reduced. Sundaram and Lamba(1998) examined the linkages between the stock markets in the Pacific-Basin region during the period from 1988 to 96 using a vector autoregression model. The results of the study showed that during the period under consideration the US market influences all other Australasian markets, except Indonesia, and none of these markets exerted a significant influence on the US market. An analysis excluding the US market reveals persistent linkages between these markets which are traced to the indirect influences of the US market. Finally, markets that are geographically and economically close and/or with large numbers of cross-border listings exert significant influence over each other, with markets closing earlier in the day exerting greater influence over markets closing later in the day. 182

10 Marashdeh and Shrestha(2010) empirically examines the extent of stock market integration among the GCC countries and the integration between the GCC stock markets and developed markets represented by the US and Europe using autoregressive distributed lag (ARDL) approach to cointegration for the period from 2002 to The results of the empirical tests suggested that the GCC stock markets are not fully integrated and there still exist arbitrage opportunities between some of the markets in the region. Also, the results showed no evidence of cointegration between the GCC stock markets and developed markets, which implied that international investors can diversify their portfolio and obtain long-run gains by investing in the GCC markets. Marashdeh (2005) attempted to examine the financial integration among four emerging stock markets in the Middle East and North African (MENA) region and the integration between these markets and developed markets represented by the US, UK and Germany for the period from 1994 to The study utilizes the newly proposed autoregressive distributed lag (ARDL) approach to cointegration. The results showed evidence of the existence of integration among stock markets in the MENA region, but not between the MENA markets and developed markets. The result suggested that there are opportunities for international investors to obtain long-run gains through portfolio diversification in the MENA region, while for regional investors; these opportunities are limited in the long run. Kamaralzaman et al(2011) examined the linkages of stock prices and benefits of diversification between the Malaysian equity market and the developed equity markets using standard cointegration analysis for the period from 1996 to 2007, thereby taking into account the pre-crisis, crisis and post crisis period. The findings of the study show that Malaysian equity market and the equity markets in the developed markets are cointegrated during the entire period, pre-crisis, crisis and post-crisis periods. The findings imply that Malaysian investors would have little scope to include stock of US, Japan or Hong Kong as it has minimal benefits of diversification, as the markets move towards a greater integration. 183

11 6.4 Openness of Indian Economy and stock market integration Openness of Indian economy with the selected developed economies is represented by the export and import of Indian economy with the selected countries. The Table:-6.1 and Table:-6.2 show respectively the value of export of India and import to India from various countries and the percentage share of exports/imports of each country to the total exports/imports of India for each corresponding year. It can be clearly seen that though the exports to the major developed countries have increased over the period of 20 years, the actual share of exports to each country as a percent to total exports have decreased over the period of years. Also, the imports from the above mentioned countries have increased over the period of 20 years, it is seen that the share of imports from Australia is higher as compared to the other countries. The share of imports from USA and UK as compared to India s total imports has reduced considerably over the years. Table:- 6.3 and Table:- 6.4 shows the annual average growth rate of Exports/Imports to/from India during the post liberalization period. Figure :-6.1 and Figure 6:-2 shows the graphical representation of the annual average rate of Export/Imports from selected developed countries. It is observed that the growth rate had risen during the initial periods. Subsequently, there was a fall in the rates and major fluctuations were observed after

12 Table:-6.1 Export from India to Selected Developed countries(rs. Crore) Year US UK Japan France Germany Australia (16.35) (6.48) (10.29) (2.38) (7.11) 4.99 (1.13) (18.97) (5.70) 41.6 (10.65) (2.54) (6.92) 6.47 (1.20) (17.98) (5.79) (9.87) (2.27) (6.64) 7.69 (1.10) (19.07) (6.53) (9.33) (2.21) (6.22) (1.32) (17.36) (6.37) (9.24) (2.35) (5.66) (1.18) (19.59) (6.55) (7.75) (2.14) 67.2 (5.50) (1.15) (19.43) (6.20) (7.83) (2.17) 71.5 (5.57) (1.25) (21.67) (6.43) 69.5 (7.70) (2.50) (4.72) 16.3 (1.17) (22.80) (6.12) (6.97) (2.44) (4.28) (1.10) (20.88) (6.12) (5.99) 46.6 (2.29) (4.08) (0.91) (19.43) (5.59) (5.42) (2.16) (4.00) (0.95) (20.67) (5.53) (4.97) (2.04) (3.99) 24.4 (0.92) (18.00) (5.16) (4.58) (2.01) (3.38) (0.86) (16.48) (4.93) (4.03) (2.01) (3.48) (0.80) (16.83) (4.74) (3.45) (2.02) (3.15) (0.73) (14.93) (4.74) (3.54) (1.66) (3.14) (0.71) (12.71) (4.11) (2.68) (1.59) (3.47) 46.3 (0.82) (11.47) (3.61) (2.55) (1.64) (3.03) (0.71) (10.93) (3.49) (2.41) (2.13) (2.69) (0.78) (10.08) (2.91) (2.27) (2.07) (2.60) (0.68) (11.27) (2.82) (2.09) (1.51) (2.61) (0.82) Source: RBI, Handbook of Statistics on Indian Economy, Various Issues, Mumbai. Note: Figures in the brackets show the percentage to total export from India 185

13 Table:-6.2 Imports to India from Selected Developed countries(rs. Crore) Year US UK Japan France Germany Australia (10.28) (6.19) (7.05) (3.17) (8.03) (3.02) (9.81) (6.48) (6.53) (2.72) (7.57) (3.83) (11.74) ) (6.53) 18.6 (2.54) (7.68) (2.83) (10.14) (5.44) (7.05) (2.15) (7.63) (3.19) (10.53) (5.23) (7.12) (2.29) (8.58) (2.79) (9.42) (5.46) (6.73) (1.96) (7.23) (3.37) (8.96) (5.89) (5.59) (1.92) (6.10) (3.58) (8.59) (6.18) (5.17) (1.70) (5.05) (3.41) (7.17) (5.45) (5.82) (1.45) 79.8 (3.71) (2.18) (5.97) (6.27) (5.11) (1.27) (3.48) (2.10) (6.13) (4.99) (4.17) (1.64) (3.94) (2.54) (7.24) (4.14) (2.99) (1.78) (3.92) (2.18) (6.44) (3.20) (3.41) 50.1 (1.40) (3.73) (3.39) (6.28) (2.63) (2.90) (1.70) (3.60) (3.43) (6.34) (2.25) (2.72) (2.76) (4.04) (3.32) (6.32) (2.25) (2.47) (2.27) (4.06) (3.77) (8.36) (1.97) (2.51) (2.49) (3.93) (3.12) (6.17) (1.95) (2.61) (1.54) (4.00) (3.67) (5.91) (1.55) (2.34) (1.45) (3.58) (4.30) (5.43) (1.46) (2.34) (1.00) (3.22) (2.92) (4.78) (1.55) (2.50) (0.79) (3.21) (3.03) Source: RBI, Handbook of Statistics on Indian Economy, Various Issues, Mumbai. Note: Figures in the brackets show the percentage to total import to 186

14 Table:-6.3 Annual Average Growth Rate of Export from India to selected developed countries(%) Year US UK Japan France Germany Australia Source: RBI, Handbook of Statistics on Indian Economy, Various Issues, Mumbai. 187

15 Table:- 6.4 Annual Average Growth Rate of Importto India to selected developed countries(%) Year US UK Japan France Germany Australia Source: RBI, Handbook of Statistics on Indian Economy, Various Issues, Mumbai. 188

16 Figure:- 6.1 Annual Average Growth Rate of Export from India to selected developed countries(%) US UK Japan France Germany Australia 189

17 Figure:- 6.2 Annual Average Growth Rate of Imports from India to selected developed countries(%) US - UK - Japan - France - Germany - Australia - 190

18 6.5 Data and methodology for empirical analysis The researcher has taken daily BSE Sensitive Index (SENSEX) comprising 30 most sensitive scrips to represent Indian stock market. BSE Sensex is considered as the core barometer of the Indian stock market for a number of reasons, viz., (i) oldest stock exchange in Asia, (ii) it is the premier bourse with the largest listing, (iii) it attracts a major chunk of the Foreign Institutional Investment and (iv) popularity (Hansda and Ray 2002). We have used daily data in order to capture potential interactions, for example, impulse responses, because a month or even a week may be long enough to obscure interactions that may last only a few days. The other markets taken for the integration analysis are USA, UK, Germany, Japan, France, Australia and Japan. All these countries are taken with the objective of regional representation. Dow Jones index represents USA stock market where as UKX index, CAC index, DAX index, NKY index and AS30 index respectively represents the countries of UK, France, Germany, Japan and Australia. Our sample covers the period from to , a total of 3886 observations. We have taken the data for those days where markets were open in all the markets Granger causality To test for Granger causality and cointegration, we use the standard methodology proposed by Granger (1969, 1986) and Engle and Granger as described in Enders (1995). All tests are performed on natural logarithm of the indices time series using OLS estimation procedure. In order to test for Granger causality among stock market I indices Y t, Y f t we estimate the equation (6.1) (6.2) 191

19 and perform an F test for joint insignificance of the coefficients. The null hypothesis f I claims that Y t does not Granger cause Y t or vice versa. Therefore, a rejection of the null hypothesis indicates a presence of Granger causality. For each pair of stock market f indices, we perform two Granger causality tests so that we can decide whether Y t I I f Granger causes Y t or Y t Granger causes Y t or both, or none. In order to examine the co-movement between the Indian stock market and the developed markets, we strictly follow the standard methodology available in the literature. We first study the relationship between the Indian stock markets and foreign markets by the simple regression: (6.3) I where the endogenous variable Y t represents the India s stock index; the exogenous f variable Y t is the stock index of the foreign markets; et is the error term. The validity and reliability of the regression relationship require the examination of the trend characteristics of the variables and cointegration test as the presence of unit root processes in the stock indices results in the spurious regression problem. Before testing for cointegration, we need to go for stationary test. In order to do so, we apply the augmented Dickey-Fuller (ADF), Phillips and Perron (PP) and KPSS unit root tests (Details of these tests are given in Chapter I) Cointegration test Cointegration exists for variables means despite variables are individually nonstationary, a linear combination of two or more time series can be stationary and there is a long-run equilibrium relationship between these variables. If the error term in (1) or (2) is stationary while the regressors are individually trending, there may be some transitory correlation between the individual regressors and error term. However, in the long run, the correlation must be zero because of the fact that rending variables must eventually 192

20 diverge from stationary ones. Thus the regression on the level of the variables is meaningful and not spurious. There are two most widely used cointegration tests namely Engle-Granger (1987) two model approaches and the Johansen (1998) and Johansen and Juselius (JJ) (1990) maximum likelihood estimator. Gonzalo (1994) provide empirical evidence to support the Johansen s method is superior over other methods (ordinary least squares, nonlinear least squares, principal components and canonical correlations) for testing the number of so integrating relationship. Therefore, we employ the maximum likelihood method of Johansen (1988 and Johansen (1988) and Johansen and Juselius (1990) to test the cointegration. The JJ test is based on vector autoregressive model: (6.4) Where Y t is an n x 1 vector of non-stationary variables integrated of the same order, α is an n x 1 vector of intercept terms, iπ is an n x n matrix of coefficients and ε t is an n x 1 of error terms. The equation (2) can be expressed by its first different ECM as: (6.5) The existence of a long-run relationship of Indian stock market with other developed stock markets is examined based on the rank of an n x n matrix of coefficients of lagged level variables (Π), in equation (2). If the rank (π) = 0, the variables are not cointegrated. On the other hand, if rank (π) = r, therefore the variables share cointegrating vectors. JJ (1990) develop two test statistic to determine the number of cointegrating vectors namely the trace statistic and the maximal eigenvalue statistic. Since, the cointegration tests are very sensitive to the choice of lag length, Hall (1989) and Johansen (1992), recommend VAR specification that renders the error term serially uncorrelated by including sufficient lags. Therefore, we use the VAR specification to select the number of lags required in the cointegration test Granger Causality Tests Based on VECM Granger (1988) concludes that if there is a cointegration vector among time series, there must be causality among these time series as least one direction. In order to 193

21 examine the short-run dynamic and long-run relation between Indian stock market and its trading partner s stock markets, the vector error correction model (VECM) is employed. According to Granger representation theorem, for cointegrated series CI (1,1), error correction term must be included in the model. Engle and Granger (1987) and Toda and Phillips (1993) specify that failure to incorporate this error correction term in the model leads to model misspecification. Therefore, this model referred to the literature as a VECM: (6.6) where Y it denotes stock price index series for India and other selected countries such as US, UK, Australia, France, Germany and Japan and the ξ Z t-1 contains r cointegrating terms, reflecting the long run equilibrium relationship among these stock markets. The Granger-causality tests are examined by testing whether the coefficients of Y 1,t-1, Y 2,t-1, Y 3,t-1, Y 4,t-1, Y 5,t-1 etc are statistically different from zero based on a standard F-test. The significance of error correction term is tested based on a standard T- test. If the variables are cointegrated, an OLS regression yields super-consistent estimators of the cointegrating parameters (Enders, 1995). Stock (1987) also proves that the OLS estimates of parameters converge faster than in OLS models using stationary variables Variance decomposition and impulse response analysis Impulse responses trace out the responsiveness of the dependent variables in the VAR to shocks to each of the variables. So, for each variable from each equation separately, a unit shock is applied to the error, and the effects upon the VAR system over time are noted. Thus, if there are g variables in a system, a total of g 2 impulse responses could be generated. Provided that the system is stable, the shock should gradually die away. 194

22 Variance decompositions give the proportion of the movements in the dependent variables that are due to their own shocks, versus shocks to the other variables. A shock to the i th variable will directly affect that variable of course, but it will also be transmitted to all of the other variables in the system through the dynamic structure of the VAR. (Details are given in Chapter I). 6.6 ANALYSIS AND RESULTS The preliminary statistics is reported in Table 6.5 The average return of Indian BSE stock market was 0.07 percent with a volatility of 2 per cent. Compared to other selected stock markets, the average return over the period in Indian stock market is much higher. At the same time, the volatility as represented by standard deviation of the stock market return is lowest in Indian stock market compared to other global well developed stock markets over the period since The negatively skewed distribution of returns shows that the returns are more flat to the left than is the case in the normal distribution and thus, investors are more likely to have frequent small gains and few extreme losses. This again implies that the large negative returns that investors may get are greater but less frequent, than the large positive returns. In Indian stock market, the returns series have a kurtosis that is greater than three. The leptokurtic distribution means that the return distributions are more peaked and have fatter tails; and hence greater risk of extreme outcomes, than is the case in the normal distribution. Consistent with the skewness and kurtosis findings, the Jarque-Bera statistic is highly significant (P=0.000) thereby rejecting the hypothesis that the returns series in Indian BSE market is normally distributed. As compared to Indian stock market, in all other markets, the return series is not normally distributed. Compared to other global stock markets, the Indian market is very close to the Asian stock markets such as Japan. The values of cross correlation as given in the Table 6.6 amply justify this result. Cross correlations provide a preliminary indicator of equity integration, with positive correlation exhibited for the period of analysis. The markets are most closely linked with US equities, although this is weakest for the Indian BSE Sensex, which has relatively a higher links with Japan stock market. However, the Indian stock market return has less significant correlation with other world 195

23 stock markets in general. Also, compared to the link between Asian and European markets, the integration is stronger among various stock market indices within European region. This is evidenced from the higher correlation coefficient between USA, UK, Germany and France. Table:-6.5 Summary Statistics of Returns of Various Stock Markets AUSTRALIA BSE FRANCE GERMANY JAPAN UK USA Mean Median Maximum Minimum Std. Dev Skewness Kurtosis Jarque-Bera Probability Sum Sum Sq. Dev Observations Table:-6.6 Correlation Matrix of Stock Price Index Returns AUSTRALIA BSE FRANCE GERMANY JAPAN UK USA AUSTRALIA BSE FRANCE GERMANY JAPAN UK USA

24 1/07/91 8/28/92 3/01/94 8/09/95 12/20/96 6/10/98 11/04/99 3/19/01 7/22/02 11/17/03 3/31/05 7/26/06 11/06/07 3/05/09 7/07/10 11/04/11 The charts show the co-movement of indices of various stock markets. All selected stock markets witnessed a dip during the first quarter of 2002 and The separate trend line of log values of stock market indices shows that the Indian stock market as represented by the BSE Sensex has divergent trend as compared to other markets. However, the trend in Indian stock market has a little similarity with Asian markets of Japan. Figure:-6.3 to Figure:-6.8 show the co-movement of stock market returns of India with USA, UK, Germany, France, Japan and Australia respectively. Figure:- 6.3 Co-movement of stock market returns between India and USA LOGINDIABSE LOGUSE 197

25 1/07/91 8/28/92 3/01/94 8/09/95 12/20/96 6/10/98 11/04/99 3/19/01 7/22/02 11/17/03 3/31/05 7/26/06 11/06/07 3/05/09 7/07/10 11/04/11 1/07/91 8/28/92 3/01/94 8/09/95 12/20/96 6/10/98 11/04/99 3/19/01 7/22/02 11/17/03 3/31/05 7/26/06 11/06/07 3/05/09 7/07/10 11/04/11 Figure :-6.4 Co-movement of stock market returns between India and UK LOGINDIABSE LOGUK Figure:-6.5 Co-movement of stock market returns between India and Germany LOGINDIABSE LOGGERMANY 198

26 1/07/91 8/28/92 3/01/94 8/09/95 12/20/96 6/10/98 11/04/99 3/19/01 7/22/02 11/17/03 3/31/05 7/26/06 11/06/07 3/05/09 7/07/10 11/04/11 1/07/91 8/28/92 3/01/94 8/09/95 12/20/96 6/10/98 11/04/99 3/19/01 7/22/02 11/17/03 3/31/05 7/26/06 11/06/07 3/05/09 7/07/10 11/04/11 Figure:-6.6 Co-movement of stock market returns between India and France LOGINDIABSE LOGFRANCE Figure :-6.7 Co-movement of stock market returns between India and Japan LOGINDIABSE LOGJAPAN 199

27 1/07/91 8/28/92 3/01/94 8/09/95 12/20/96 6/10/98 11/04/99 3/19/01 7/22/02 11/17/03 3/31/05 7/26/06 11/06/07 3/05/09 7/07/10 11/04/11 Figure :-6.8 Co-movement of stock market returns between India and Australia LOGINDIABSE LOGAUSTRALIA The Granger causality test result Table:-6.7 Granger Causality Results for BSE Sensex Vs. Selected Eight Stock Indices Variables Causality F-statistics USA USA India * India USA UK UK India * India UK Germany Germany India * India Germany Australia Australia India India Astralia * Japan Japan India India Japan * France France India * India France * shows the test statistics at 5% level of significance The Granger causality test shows the short run relation between various entities. Here the test result shows relationship between India and other selected stock markets. The results of this test are shown in Table 6.7. The results in Table 6.7 show that there is unidirectional causality in all the markets. The unidirectional causality runs from USA, 200

28 UK, Germany and France to Indian stock market. However, the unidirectional causality runs from Indian stock market to Australia and Japan. With respect to Asian stock market, the direction of causality runs from India. It implies that all developed stock markets particularly of European origin affect the Indian market and not vice versa. The results between the US and Indian stock markets are obvious since the US market is the world s foremost securities market and has heavy influence on other stock markets. Hence one may not be surprised that US stock markets Granger cause the Indian stock market in the short run (Table 6.7). More rationally, several macroeconomic factors may give good explanation to the causal relationship between two stock markets. They include economic connection, regulatory structures similarity, exchange rate policy and trade flows. Coincided with the start of the liberalization of the Indian economy, there is a steady improvement in the India-US trade relations during the last decade. US government has identified India as one of the 10 major emerging markets (Wong et al, 2005). The volume of India-US bilateral trade also started growing at a steady pace with the export from India to the US grows from Rs billion in 1990 to Rs billion in On the other hand, the volume of import to India from US has increased from Rs billion to Rs billion. Considering the fact that the US economy is a developed economy, the India-US trade volume still remains a small fraction of US s global trade. While US s export to India account for over 10% of India s non-oil imports and US is the destination of one-fifth of India s exports, US s trade turnover with India constitutes less than 1 % of its global trade. India s percentage share in US imports has remained stable over the last few years; it was 0.9% during In 2010, India s percentage share in US imports increased to 4.4%. The figures show that US economy is very important to Indian economy, though reverse is not true. This seems to be consistent with our result of unidirectional causality from S&P 500 to BSE Sensex. The results in Table 6.7 also reveal the evidence of short-run impact of UK stock market to Indian stock market. It may be noted that after the opening up of the Indian economy since 1991 the bilateral trade between India and UK has been constantly increasing. UK continues to be India s second largest trading partner after US and 201

29 continues to be the largest cumulative investor in India and third largest investor in the post-1991 period. As Indian economy is linked with UK s economy closely, it is not surprising that UK stock market does have an impact on the Indian stock market. Table:- 6.1 shows that exports from India to UK has increased from Rs billion in 1990 to Rs billion in On the other hand, the volume of import to India from US has increased from Rs billion to Rs billion. The direction of trade from India to UK and vice versa is shown in the Table:-6.2 There is no evidence of short-run impact from Japan stock market to Indian stock market can be found from the Table: At the same time, Indian stock market does appear to influence the Japanese market. It may be mentioned that there has been an increase in the volume of trade between India and Japan in absolute term. Table 6 shows that exports from India to Japan have increased from Rs billion in 1990 to Rs billion in The volume of import to India from Japan has increased from Rs billion tors billion. FII investment from Japan has increased, it is a very recent phenomenon and it is too early to make any conclusion in this respect. There is evidence of short-run impact from French stock market to Indian stock market as seen in Table 6.7. At the same time, Indian stock market does appear to influence the French market. It may be mentioned that there has been an increase in the volume of trade between India and France since 1990 s. Table 6.1 shows that exports from India to France have increased from Rs billion in 1990 to Rs billion in The volume of import to India from Japan has increased from Rs billion to Rs billion. With regard to Germany, there is evidence of short run impact from German Stock Market to Indian Stock Market. At the same time, Indian stock market does appear to influence the German Stock Market. It may be mentioned that there has been an increase in the volume of trade between India and Germany since 1990 s. Table:-6.1 shows that exports from India to Germany have increased from Rs billion in 1990 to Rs billion in The volume of import to India from Japan has increased from Rs billion to Rs billion. 202