36540894 Foreign Exchange Markets in India

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Integration and Efficiency of Stock and Foreign Exchange Markets in India Dr. Alok Kumar Mishra* & Dr. M. Thomas Paul**

Abstract This article attempts to examine the integration and efficiency of Indian stock and foreign exchange markets. The study employed Time series ordinary least square regression, Unit Root test, Grangers causality test, Vector Auto Regression techniques on monthly data of stock return and exchange rate return forthe period spanning from February 1995 to March 2005.The major finding of this study are as follows. Both the stock indices return (Rsensex and Rnifty) are near

normal whereas exchange rate return is not normal and more peak. The stock return and exchange rate return are positively related. The policy implication of this above result of the positive relation between stock return and exchange ratereturn for the foreign investors in India should be further studied. From the Grangers causality test, it is found that there is no causality for the return series of stock indices and exchange rate except return Nifty and return exchange rate. Weak form of market efficiency hypothesis is also corroborated for stock and

foreign exchange markets.JEL: G15, C32 Keywords: Weak form of market efficiency, stock return, exchange rate return, Buy-Hold strategy, Convex trading strategy, Grangers causality test,

Vector Auto Regression.* is Manager, at the Evaluesrve.Com Pvt. Ltd, 2nd Floor, Unitch World-Cyber Park, Jharsa, Sector-39, Gurgaon-122002, Haryana and ** is Professor , at the National Institute Of Bank Management , NIBM P. O , Kondhwe Khurd, Pune- 411048, India., and ** was also formerly Professor of Financial Economics and Macroeconomics, Department of Economics, University Of Botswana, Botswana, and was also formerly Reserve Bank Of India Chair Professor, Monetary Economics, at the Institute For social and Economic Change Bangalore., India. Email: of (1) * [email protected] of (2) ** [email protected]

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1.0 Introduction Global investors choose to diversify their funds across the financial markets to reduce the portfolio risk on the assumption that the returns in various financial markets may not be highly correlated. Another related issueis how far the return in one market will enable to predict the return in the other financial market. From the informational efficiency criteria, any past information even if that information may be pertaining to the return in one financialmarket, it should not enable to predict the future changes in the return in theother financial market. But at the same time, from the rational expectation point of view, all the informations including the returns from any other financial markets should be factored into the return of the financial markets. For example,

how far the return in the stock market influences the return in the foreign exchange market and vice versa. In order to study the aforementioned research problems, we have used the time series techniques viz, unit root test, OLS regression, Grangers causality and Vector Auto Regression techniques. Our data points are based on the monthly data of stock price and exchange rate, where the sample period spanning from February 1995 to March 2005, forming around 121 observations. Against this background, the present study empirically examined the integration and efficiency of stock and foreign exchange markets in India. One basic issue which has been confronting the practitioners in financial industry is about the pr

obability distribution of the returns in financial markets because it has investing and trading implications .In this context, we have investigated the normality of the return distribution of the respective financial markets. In section 2.0, we discuss the theoretical interlink ages between stock and foreign exchange markets in India. Section 3.0 and 4.0 presents the empirical literature and empirical methodology respectively. Section 5.0 presents the variables description and nature of the data points. Section 6.0 reports the empirical results followedby the conclusion in Section 7.0.

2.0 Interlink ages between stock and Foreign Exchange Markets in India: Theoretical Underpinnings The linkages between stock market performance and exchange rate behavior has long been debated in the economic literature. The arguments for the linkage have been made at both micro and macro economic levels. At the macroeconomic level, the discussion has

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been centered around the relationship between aggregate stock price and floatingvalue of exchange rates. This link is seen by models that focus on the current

account (Flow Oriented Models, e.g. Dornbusch & Fisher, 1980) as well as those that focus on the asset market (Stock Oriented Models, e.g. Branson & Frankel, 1983), though in different ways. Flow Oriented models [Dornbusch & Fisher (1980)] of

exchange rate determination focus on the current account or the trade balance.This model posits that currency movements affect international competitiveness and balance of trade positions, and, consequently, the real output of the country, which in turn affects the current and future expected cash flows of firms andtheir stock prices. The detailed logical deduction of this relationship is likethis. Changes in exchange rates affect the competitiveness of a firm as fluctuations in exchange rates affect the value of the earnings and cost of its funds because many companies borrow in foreign currencies to fund their operations and hence its stock prices. But this will affect in either way depending upon whether

that firm is an exporting unit or a heavy user of imported inputs. In the caseof an exporting firm, a depreciation of the local currency makes exporting goods

more attractive and this leads to an increase in foreign demand for export of goods and services. As a result, the revenue of the firm and its value will increase which will in turn increase stock prices. On the other hand, an appreciation

of local currency decreases profits of an exporting firm because of decrease inforeign demand of its products. Hence the stock price will decrease. This is exactly opposite to the case of an importing firm as exchange rate changes.

Stock Oriented models [Branson & Frankel (1983)] of exchange rates or portfolio balance approach gives emphasis on capital account as the major determinant of exchange rate dynamics. The essence of the portfolio balance model is based on thenotion that agents should allocate their entire wealth among domestic and foreign assets including currencies in their portfolio. Hence, exchange rate plays the

role of balancing the demand for and supply of assets. Now the logical deduction of negative effects of stock prices on exchange rates is as follows: An increase in domestic stock prices leads individuals to demand more domestic assets. To

buy more domestic assets, they need to

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sell foreign assets as these are now relatively less attractive. As a result ofwhich, there is an appreciation of local currency due to more demand for domestic assets.

Studies like Aggarwala (1981), Sonnen and Hennigar (1988) establish the relationbetween exchange rates and stock prices. They have pointed out that a change inexchange rates could change the stock prices of multinational firms directly an

d those of domestic firms indirectly. In the case of multinational firms, a change in the exchange rate will change the value of that firms foreign operation, which will be reflected in its balance sheet as profit or loss. Consequently, it contributes current account imbalance. Once the profit or loss is announced, thefirms stock price will change. Further, a general downward movement of the stockmarket will motivate investors to seek better returns elsewhere. This decreasesthe demand for money and pushes interest rate down, thus causing huge outflows of funds, and hence depreciating the currency.

However, in the case of domestic firms, devaluation could either raise or lowera firms stock price depending upon whether that particular firm is an exporting firm or it is a heavy user of imported input. If it is involved in both the activ

ities, then the stock price could move in either direction. Consider the case ofan exporting domestic firm. This firm will directly benefit from devaluation due to increased demand for its output. Since higher sales usually result in higher profit, its stock price will increase, whereas in the case of a user of imported inputs of domestic firm, devaluation will raise its costs and lower its profits. The news of decline in profits may depress the firms stock price.

Bahmani , Oskooe and Sohrabian (1992) offered an alternative explanation for theeffect of stock price on exchange rate. The argument is as follows: Consider th

e resulting increase in the real balance which will result in an increase in interest rate. Thus domestic assets are more attractive, and, as a result, individual investors or firms will adjust their domestic and foreign portfolio by demanding more domestic assets. The portfolio adjustments of firms and individuals will lead to an appreciation of the domestic currency because they require domestic

currency for transaction.

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Further, integration of the US stock market with the Pacific basin countrys markets and world markets, which led to the requirement of establishing the relationship between stock prices and exchange rates. Thus, an increase in internationalstock market causes the local stock market to rise, which in turn increases wealth as well as raises interest rates. Higher interest rate will attract foreign capital and lead to an increase in the real exchange rate. 3.0 Empirical Literature: Some of the early studies like Aggawal (1981), Soenen and Hennigar (1988) simply consider the correlation between the two variables. Aggarwal, using monthly

U.S. stock price data and the effective exchange rate for the period 1974 to 1978, explored the relationship between the changes in the dollar exchange rates and changes in indices of stock prices. He found a significant positive correlation, and finds that the relationship is stronger in the short run than in the long run. However Soenen and Hennigar, employing monthly data on the same variables, for the period 1980 to 1986, found a strong negative relationship. Solnik (1987) employing OLS regression analysis on monthly and quarterly data from 1973 to1983 for eight industrialized countries found a negative relationship between real domestic stock returns and real exchange rate movements. However, for monthly

data over 1979-83, he observed a weak but positive relation between the two variables.

Soenen and Aggarwal (1989) found mixed results among industrial countries. Ma and Kao (1990) tried to attribute these differences to the nature of the countries. They used the asset pricing model on the monthly data from January 1993 to December 1983 on six major industrialized countries and found that domestic currency appreciation negatively affects the domestic stock price movements for an export dominant economy and positively affects an import dominant economy.

Jorion (1998) attempted to analyze and compare the empirical distribution of returns in the U.S. stock market and in the foreign exchange market by using the maximum

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likelihood estimation procedure and ARCH model in daily data of exchange rates and stock returns spanning from June 1973 to December 1985. The study found thatexchange rates display significant jump components, which are more manifest than

in the stock market. The statistical analysis of the study for the foreign exchange market and stock market suggests that there are important differences in the structure of these markets.

Jorion (1990) examined the exposure of U.S. multinationals to foreign currency risk, by employing the time series regression on the rate of return in the U.S. multinational firms common stocks and the rate of change in a trade weighted value

of the U.S. dollar over the period 1971 to 1987. The study found significant cross sectional differences in the relationship between the value of U.S. multinationals and the exchange rate. Given these results, the study focused on the determinants of exchange rate exposure. The co movement between stock returns and the value of the dollar is found to be positively related to the percentage of foreign operations of U.S. multinationals.

Smith, C.E. (1992a) attempted to derive an estimable exchange rate equation by considering the portfolio balance model. The model considered values of equities,

stocks of bonds and money as important determinants of exchange rates, which were then applied to the German Mark vis--vis the US dollar and the Japanese Yen vis--vis the US dollar exchange rate by using a general model of optimal choice over risky assets. He has considered the study period spanning from January 1974 to

March 1988. The study found that equity value has a significant influence on exchange rates but the stock of money and bond has little impact on exchange rates. These results imply not only that equities are an important additional factorto be included in the portfolio balance models of the exchange rate, but also suggest that the impact of equities is more important than the impact of government bonds and money.

Bodnar and Gentry (1993) employed the market model of Capital Asset Pricing (CAPM) model and categorized the industries into traded and non traded goods industries covering the USA, Canada and Japan. to examined the relation between changes

in exchange rate and industry values. The study had considered the data periodfrom January 1979 to

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December 1988 for the USA and Canada and from September 1983 to December 1988 for Japan. The model was estimated using the SURE method for the US, Canada and OLS for Japan. The results of the study indicated that for the three countries, 20-35 percent of industries had significant foreign exchange exposure and particularly with more exposure in the case of Canada and Japan. Except for the US, non-traded goods industries indicated a gain with appreciation of local currency. Industry export and import ratios were associated with negative and positive exposures respectively. For the US and Japan, foreign dominated assets showed a significant negative exposure to exchange rate changes. Overall, the study found insignificant contemporaneous effect. There have also been several studies that have

used cointegration and Granger causality to study the direction of movement between stock prices and exchange rates. Taylor, M. P. et al. (1988) was one of the

early studies using this. They studied the impact of the abolition of the UK exchange control on the degree of integration of the UK and overseas stock markets

such as West Germany, Netherlands, Japan and US employing the Granger causalityand Engel Granger Cointegration test over the two sub-periods spanning from Apr

il 1973 to September 1979 and October 1979 to June 1986 respectively. The studyconcluded that, there was no significant increase in the correlation of stock market returns as a result of the abolition of exchange control. Cointegration tes

t confirmed that the UK and foreign (non-US) stock market indices were cointegrated in post-1979 period but not before that.

Oskooe, B.M. and Sohrabian, A. (1992) tried to test the causality as well as cointegration between stock price and effective exchange rate using monthly observations over the period July 1973 to December 1988 for a total of 186 observations

from the U.S. economy. They found that there was a bi-directional causality between stock prices and the effective exchange rate of the dollar at least in theshort run. The co-integration analysis revealed that there was no long run relationship between two variables.

Libly Rittenberg (1993) employed the Granger causality test to examine the relationship between exchange rate changes and stock price level changes in Turkey. Since causality tests are sensitive to lag selection, he employed three different

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optimal lag selection, i.e. an arbitrarily selected, Hsiao method (1979), and the SMART or subset model auto regression method of Kunst and Martin (1989). In all cases, he found that causality runs from price level change to exchange rate changes but there is no feedback causality from exchange rate to price level changes.

Ajayi, A. and Mougoue (1996) examined the intertemporal relation between stock indices and exchange rates for a sample of eight advanced countries during the period 1985:4 to 1991:6. By employing the co-integration and causality tests on daily closing stock market indices and exchange rates, the study found that (i) an

increase in aggregate domestic stock price has a negative short-run effect on domestic currency values, (ii) sustained increase in domestic stock prices will induce domestic currency appreciation in the long run and (iii) currency depreciation has negative short-run and long-run effects on the stock market.

Qiao, Yu (1997) employed daily stock price indices and spot exchange rates obtained from the financial markets of Hong Kong, Tokyo and Singapore over the period

from January 3 1983 to June 15 1994 to examine the possible interaction betweenthese financial variables. Based on Granger causality test, he found that the c

hanges in stock prices are caused by changes in exchange rates in Tokyo and HongKong markets. However, no such causation was found for the Singapore market. Onthe reverse causality from stock prices to exchange rates, his results show suc

h causation for only Tokyo market. Therefore for Tokyo market there is a bi-directional causal relationship between stock returns and changes in exchange rates.

The study also uses Vector Autoregression model to analyse a long run stable relationship between stock prices and exchange rates in the above Asian financialmarkets. His results found a strong long run stable relationship between stock prices and exchange rates on levels for all three markets.

Johnson and Soenen (1998) analysed the stock price reactions of 11 Pacific Basinstock markets to exchange rate changes with respect to the US dollar and Japane

se Yen for the period January 1985 to June 1995. The study found that a significantly strong positive

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Ibrahim (2000) investigated the interactions between stock prices and exchange rates in Malaysia, using bi-variate and multivariate co-integration and the Granger causality test. The study took multiple variables such as stock prices, three

exchange rate measures, viz, the real effective exchange rate, the nominal effective exchange rate and RM/US$, money supply, and reserves during the period 1979:1 to 1996:6. The results from bivariate models indicated that there was no long-run relationship between the stock market and any of the exchange rates; however, there was some evidence of co-integration when the models were extended to include money supply and reserves. This finding indicates that in the short run,a concerted stance on monetary policy, exchange rate and reserve policy is vital

for stock market stability, and, also indicates there is informational inefficiency in the Malaysian stock market. Multivariate test showed: (i) there was unidirectional causality from stock market to exchange rate; (ii) both the exchangerates and the stock indices were Granger caused by the money supply and reserves; (iii) there was bi directional causality between variables only in the case of

nominal effective exchange rate.

Amare and Mohsin (2000) examined the long-run association between stock prices and exchange rates for Japan, Hong Kong, Taiwan, Singapore, Thailand, Malaysia, K

orea, Indonesia and Philippines. The study considered monthly data spanning fromJanuary 1980 to June 1998 and employed cointegration technique. The long-run relationship between stock prices and exchange rates was found only for Singaporeand Philippines. They attributed this lack of cointegration between the said variables to the bias created by the omission of important variables. When interest rate variable was included in their cointegrating equation, they found cointegration between stock prices, exchange rates and interest rate for six of the nine countries. Granger, C.W.J. et al (2000) applying co-integration and Granger causality test and structural break test on daily data of exchange rate and stock prices in Hong Kong, Indonesia, Japan, South Korea, Malaysia, the Philippines, Singapore, Thailand and Taiwan for the period 1986 to 1998 suggested: (i) there exists very little interaction between currency and stock markets except for Singapore for the period January 3, 1986 to November 30, 1987; (ii) there is no definitive pattern of interaction between the two

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markets, however, changes in exchange rates lead to stock prices in the case ofSingapore and vice versa in the case of Taiwan and Hong Kong during the period December1, 1987 to May 31, 1997; (iii) In the case of South Korea, changes in the

exchange rate Granger causes stock prices where as the reverse direction such as changes in stock prices Granger causes exchange rates is found in Hong Kong and the Philippines. The rest of the countries such as Malaysia, Singapore, Thailand and Taiwan are characterized by feedback interactions in which change in exchange rate can take the lead and vice versa from the period June 1, 1997 to June16, 1998.

Bruce Morley and Eric Pentecost (2000) investigated the nature of the relationship between stock prices and spot exchange rates on G-7 countries by employing the cointegration test and codependence technique. The study considered the monthly observations spanning from January 1982 to January 1994, and broadly concluded

that stock prices and exchange rates do not exhibit common trends, but do exhibit common cycles.

Bala Ramasamy and Matthew Yeung (2001) studied the hit and run behaviour in theinteraction between stock prices and exchange rates of nine countries, namely Ho

ng Kong, Indonesia, Japan, South Korea, Malaysia, the Philippines Singapore, Thailand and Taiwan affected by the Asian flu. The study considered the quarterly data spanning from January 1, 1997 to December 31, 2000, forming around 1,040 samples for each country. By employing the Granger causality test, the study concluded that stock prices Granger caused movements in the exchange rate in the caseof all the countries except Hong Kong, where bidirectional-causality was seen. However, different results were obtained when they (Bala Ramasamy and Matthew C.H.Yeung, 2002) followed with an examination of the links between the foreign exchange and stock markets on six countries in the East Asia region, namely Indonesia, South Korea, Malaysia, Thailand, the Philippines and Singapore. The study considered the period from January 2, 1995 to August 6, 2001, forming around 1,720observations. By employing the cointegration test and Granger causality test, the study concluded that there are inconsistent results in tests

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for bivariate causality between stock prices and exchange rates. This finding suggested that the stock and foreign exchange markets in the region may still be unstable.

Hatemi, J. A. and Irandoust, M. (2002) examined a new Granger non-causality testing procedure developed by Toda and Yamamoto (1995) to contribute to the debateon exchange rates and stock prices in Sweden. The study also examined the possible causal relation between these variables in a Vector Auto Regression model. The results of the study found that Granger causality is unidirectional running from stock prices to effective exchange rates. The results also revealed that an increase in Swedish stock prices is associated with an appreciation of the Swedish Krona.

Lean, H.H, Halim, M and Wong, W.K. (2003) employed the cointegration and bivariate causality tests to explore the relationship between exchange rates and stockprices prevalent in the pre-Asian crisis, during Asian crisis and during 9/11-terrorist attack in the US periods on the seven Asian countries such as Hong Kong,

Indonesia, Singapore, Malaysia, Korea, Philippines and Thailand badly hit by the Asian financial crisis. The study also included Japan for the control purpose.

The empirical results of the study found that during the period before 1997 Asian financial crisis, all the countries except the Philippines and Malaysia experienced no evidence of Granger causality and no specific cointegration relationship between the exchange rates and stock prices. Causality, but not cointegration, between the capital and financial markets appears to become strong during theAsian financial crisis period and all the countries showed evidence of causality

between the two markets. The study also found a surprising result that after the 9/11-terrorist attack, the causality relationship between the two markets turns back to normal as in the pre Asian crisis period, when in all the countries except Korea are found no linkages between exchange rates and stock prices. In addition, the study found that after the 9/11-terrorist attack, there is less cointegration relationship between exchange rates and stock prices. Based on these findings, the study broadly concluded: (i) Asian financial crisis has bigger and more direct impact on the causality relationships between stock prices and currency exchanges in Asian markets and the 9/11-terrorist attack in the USA basically

has no impact on the causality relationship

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between the two markets; and (ii) the financial and capital markets become moremature and more efficient after the crisis. Kasman Saadet (2003) examined the relationship between stock prices and exchange rates by using the daily data from1990 to 2002 of exchange rates and aggregate stock indices of Turkey. By employing Johansens cointegration test and Granger causality test, the study found a long-run stable relationship between stock indices and exchange rates. The study also concluded that causality relationship exists only from exchange rate to industry sector index.

Stavarek Daniel (2004) investigated the nature of the causal relationship between stock prices and effective exchange rates in the four old EU member countries(Asia, France, Germany and the UK), four new EU member countries (Czech Republic, Hungary, Poland and Slovakia) and in the USA. Both the short term and long term causalities between these variables were explored using the monthly data. Thestudy employed cointegration analysis, vector error correction modeling and standard Granger causality test to examine whether stock prices and exchange rates were related to each other or not and what kind of causality direction exists between them. The results of the study found much stronger causality in countries with developed capital and foreign exchange markets (old EU member countries and

the USA) than in the new comers. The evidence also suggested more powerful long-run as well as short-run causal relations during the period 1993-2003 than during 1970-1992. Causalities seem to be predominantly unidirectional with the direction running from stock prices to exchange rates.

Victor Murinde and Sunil Poshakwale (2004) investigated the price interactions between the two main components of European emerging financial markets, viz. theforeign exchange market and the stock market before and after the adoption of the Euro by most European Union (EU) economies. The study employed Granger (1969)causality test to analyse daily observations on the stock price index and nominal exchange rate for Hungary, Czech Republic and Poland from January 2, 1995 to December 31, 1998, for the pre-Euro period and January 1, 1999 to December 31, 2003 for the Euro period. The study found that for the pre-Euro period, mutually reinforcing interactions existed 12


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between exchange rates and stock prices in the Czech Republic and Poland but nointeraction seem to exist for Hungary. During the Euro period, exchange rates unidirectionally Granger cause stock prices in all the three sample economies. The

study also concluded that a higher positive correlation existed among the stockand the foreign exchange markets in Hungary, Czech and Poland during the Euro p

eriod and pre Euro period respectively. There have also been a few studies of the interaction between stock prices and exchange rates in the Indian context. Perhaps the earliest is Abdalla et al (1997). They studied the interactions between

exchange rates and stock prices in the case of India, Korea, Pakistan and the Philippines by applying bi-variate vector autoregressive models on monthly observations of stock price index and the real effective exchange rate over 1985:1 to1994:7. The study found unidirectional causality from exchange rate to stock prices in all the countries except the Philippines. This finding suggests policy implication that the respective governments should be cautious in their implementation of exchange rate policies since these policies have ramifications in theirstock markets. Pethe and Karnik (2000) investigated the interrelationships between stock prices and macro economic variables such as exchange rate of rupee vis--vis dollar, prime lending rate, narrow money supply, broad money supply and index of industrial production on the monthly data spanning from April 1992 to Decem

ber 1997. By employing unit root test, cointegration and error correction models, the study found there was no long run stable relationship between stock prices, exchange rates, prime lending rate, narrow money supply, broad money supply and index of industrial production.

Karmarkar et al (2001) by employing the coefficient determination and regressionanalysis on weekly closing values of exchange rate (RM/US$) and five composite

as well as five sectoral indices of stock market over the period 2000 concludedthat the depreciation of the rupee with respect to dollar leads to an appreciation of stock prices and vice versa.

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However, when Bhattacharya et al (2002) studied the nature of causal relation between stock market, exchange rate, foreign exchange reserves and value of tradebalance in India from 1990:4 to 2001:3 by applying co-integration and long run Granger non causality test, they found that there was no causal linkage between stock prices and the three variables under consideration. Muhammad, N. (2002) examined the long-run and short-run association between stock prices and exchange rates for four south Asian countries, namely Pakistan, India, Bangladesh and Srilanka for the period January 1994 to December 2000. The study employed monthly data and applied cointegration, error correction modeling approach and standard Granger causality tests. The major findings of the study are as follows. There isno long run equilibrium relationship between stock prices and exchange rates for

Pakistan and India. In the case of Bangladesh, there is a long-run relationshipbetween the variables considered for the study. The results for Srilanka showeda long-run relationship for lag one and two but for higher lag order; the studydid not find any cointegration between stock price and exchange rate. However,

the Engel and Granger test found a cointegrating relationship to stock prices and exchange rates for Srilanka. Granger causality test confirmed that there seemed to be no short run association between stock prices and exchange rates eitherin the case of Pakistan and India. The error correction model confirmed that the

re is bi-directional long-run causality in the case of Srilanka; however, thereis no short-run causation in either direction for Bangladesh and Srilanka.

In order to examine the dynamic linkages between the foreign exchange and stockmarkets for India, Nath and Samanta (2003) employed the Granger causality test on daily data during the period March 1993 to December 2002. The empirical finding of the study suggests that these two markets did not have any causal relationship. When the study extended its analysis to see if liberalization in both the markets has brought them together or not then also the study did not find any significant causal relationship between exchange rate and stock price movements except for the years 1993, 2001 and 2002.

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Mishra, A. K (2004) examined whether stock market and foreign exchange markets are related to each other or not in the context of India. The study employed Grangers causality test and Vector Auto Regression technique on monthly stock return,

exchange rate, interest rate and demand for money for the period April 1992 toMarch 2002. The major findings of the study are (a) there exists a unidirectional causality between the exchange rate and interest rate and between the exchange

rate return and demand for money; (b) there is no Grangers causality between theexchange rate return and stock return. Through Vector Auto Regression modeling,the study confirmed that though stock return, exchange rate return, the demand

for money, and interest rate are related to each other but it lacks any consistent relationship. The forecast error variance decomposition further evidences that (a) the exchange rate return affects the demand for money, (b) the interest rate causes exchange rate return change (c) the exchange rate return affects the stock return, (d) the demand for money affects stock return, (e) the interest rate affects the stock return, and (f) the demand for money affects the interest rate. 4.0 Methodology: The discussion in the preceding section reveals that thereis neither theoretical nor empirical consensus on any definite pattern or consistent relationship between the stock and foreign exchange markets. Similarly, noconclusive generalization can be made about the causal nexus between these two m

arkets. However, this is a question of vital importance to policy makers as wellas investors, in so far as information from one market can be used to predict the behavior of the other market. If stock and foreign exchange markets are related and causation runs from stock market to foreign exchange market, then authorities can focus on domestic economic policies to stabilize the stock market. On the other hand, if causation runs from foreign exchange market to stock market, then the crises in the stock market can be prevented by controlling exchange rates.

In the very first step the study employed the ordinary least square time seriesregression analysis to examine the behavior of stock return and exchange rate return. The linear regression analysis is defined as the following two regressionequations.

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S t = + Et + t Et = 1 + 1 S t + 1t

(1) (2)

Wh r

oth nd 1 in qu tion 1 nd 2 r pr s nts th int rc pt, nd 1 r pr s nts th co ffici nts for xch ng r t r turn nd stock pric r turn r sp ctiv ly wh r , St nd Et r stock pric r turn nd xch ng r t r turn t tim p riod t nd t nd 1t r

th

whit

nois

rror t

rms in

oth th

qu tions. In ord

r to

x min th dyn mic int r ctions of stock nd for ign xch ng m rk ts in Indi , v rious sophistic t d tim s ri s conom tric t chniqu s r mploy d. Although th

r r m ny ppro ch s to mod ling c us lity or short-t rm int r ctions in t mpor l syst ms, w first pply th prototyp mod l d v lop d

y Gr ng r (1969) notonly

c us it is th simpl st nd most str ight forw rd

ut lso th xist nc

of c us l ord ring in Gr ng rs s ns points to l w of c us tion nd impli s pr dict

ility nd rog n ity (A

d ll , t l (1997)). How v r, th non-st tion ryn tur of most tim s s ri s d t nd th n d for voiding th pro

l m of spurious or nons ns r gr ssion c lls for th x min tion of th ir st tion rity prop

rty. Th study mploy d Augm nt Dick y Full r T st nd Phillips P rron t st to r mov th unit root pro

l ms mong th v ri

l s

oth t without tr nd nd int r

c

pt

nd with tr

nd

nd int

rc

pt l

v

l r

sp

ctiv

ly. Gr

ng

rs c

us

lity [propos

d

y Gr ng r (1969) nd popul riz d

y Sims (1972)] m y

d fin d s th for c sting r l tionship

tw n two v ri

l s. In short, Gr ng r c us lity t st st t

s th t if S & E r two tim s ri s v ri

l s nd, if p st v lu s of v ri

l S signific ntly contri

ut to for c st th v lu of th oth r v ri

l E, th n Sis s id to

Gr ng r c using E nd vic v rs . Th t st involv s th followingtwo r gr ssion qu tions:

n n

St =

0

+

i =1m

iEti +

j =1m

j S t j + u 1t

(3)

Et = 1 +

i =1

iEti +

j =1

jS t j + u 2t


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(4)

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where St n

Et re the stock price n

exch n e r te to

e teste

, n

u1t n

u2t re mutu y uncorre te

white noise errors, n

t

enotes the time perio

.Equ tion 3 postu tes th t current S is re te

to p st v ues of S s we sof p st E. Simi r y, Equ tion 4 postu tes th t E is re te

to p st v ues ofE s we s re te

to p st v ues of S. Three possi

e conc usions c n

e

uce

from such n ysis, viz, uni

irection c us ity,

i

irection c us ity n

th t they re in

epen

ent of e ch other. 1. Uni

irection c us ity from Eto S is in

ic te

if the estim te

coefficients on the

e

E in Equ tion 3 re st tistic y

ifferent from zero s roup (i.e.,n

i =1

i

0 ) n

the set of estim te

coefficients on the e

S in Equ tion 4 ism

not st

tistic

y

ifferent from zero (i.e.,j =1

j

= 0 ).

2. Uni

irection c us ity from S to E exists if the set of e

E coefficients inn

Equ tion 3 is not st tistic y

ifferent from zero (i.e.,

i =1

i

= 0 ) n

the set of

the e

S coefficients in Equ tion 4 is st tistic y

ifferent from zero (i.e.,m

j =1

j

0 ).

3. Fee

ck or

i ter c us ity is su este

when the sets of E n

S coefficients re st tistic y n

si nific nt y

ifferent from zero in

oth re ressions.

4. Fin y, in

epen

ence is su este

when the sets of E n

S coefficients renot st tistic y si

nific nt in

oth the re

ressions.

There re two import nt steps invo ve

with the Gr n ers c us ity test. First, s


20/49

t tion ry

t is require

for Equ tions 3 n

4. Secon

, in

ition to the nee

for testin the st tion ry property of the

t , the Gr n er metho

o o y is somewh t sensitive to the en th use

in Equ tions 3 n

4. It is

etter to use more r ther th n fewer en th since the theory is couche

in terms of there ev nt p st inform tion. The chosen

17


21/49

en th must

e m tche

with the ctu en th. If it is esser th n ctu

en th, the omission of re ev nt s c n c use

i s n

if it is more th n the re ev nt en th c uses the equ tion to

e insufficient. To

e with thispro

em, Hsi o (1981) h s

eve ope

system tic utore ressive metho

for choosin ppropri te en th. Therefore, the ppropri te en th is one whereAk ikes Fin Pre

iction Error (FPE) is owest. Ak ikes inform tion criteri (AIC), or Schw rz Criterion (SC) or Like ihoo

R tio (LR) criterion or H nn n Quinn inform tion criterion (HQ) is so usefu for choosin

the

en

th. To furtherconfirm the impu se response

etween stock price n

exch n e r te n

to pre

ict the

eh vior mon them in comin future, the stu

y exten

s the n ysis tow r

s Vector Auto Re ression mo

e in (VAR). VAR system consists set of re ression equ tion in which the v ri

es re consi

ere

to

e en

o enous. In VAR metho

o o y, e ch en

o enous v ri

e is exp ine

y its e

or p st v ues n

the e

v ues of other en

o enous v ri

es inc u

e

in the mo

e . In ener , there re no exo enous v ri

es in the mo

e . Thus,

y voi

in the imposition of priori restriction on the mo

e the VAR

s si nific nt y to thef exi

i ity of the mo

e . A VAR in the st n

r

form represente

s:

S t = 10 + 11S t 1 + 12 Et 1 + e1t

Et =

20 +

21 S t 1 +

22 Et 1 + e2t(5) (6)

Where, St is the stock price t the time perio

t, Et is the exch n e r te t the time perio

t, io is e ement i of the vector Ao, ij is the e ement in row i n

co umn j of the m trix A1 n

eit s the e ement i of the vector et n

it represents in the

ove equ tion s e1t n

e2t respective y re white noise error term n

oth h ve zero me n n

const nt v ri nces n

re in

ivi

u y seri y uncorre te

.

Now we

iscuss

out v rious steps, which re invo ve

in VAR estim tion. To st rt with VAR estim tion proce

ure requires the se ection of v ri

es to

e inc u

e

in the system. The v ri

es inc u

e

in the VAR re se ecte

ccor

in

to the re ev nt economic mo

e . The next step is to verify the st tion rity of the v ri

es. Re r

in the

18


22/49

issue of whether the v ri

es in VAR nee

to

e st tion ry Sims (1980) n

Do n(1992) recommen

inst

ifferencin even if the v ri

es cont inin unit root1. Here in this p per, Au mente

Dickey Fu er (ADF) n

Phi ips Peron (PP)tests re use

to c rry out unit root test.

The next step is to se ect the ppropri te en th. The en th of e ch ofthe v ri

es in the system is to

e fixe

. For this we use Like ihoo

R tio (LR) test. After settin

the

en

th, now we re in position to estim te themo

e . But it m y

e note

th t the coefficients o

t ine

from the estim tion ofVAR mo

e c nt

e interprete

irect y. To overcome this pro

em, Litterm n (1979) h

su este

the use of Innov tion Accountin Techniques, which consists of

oth Impu se response functions (IRFS) n

V ri nce Decompositions (VDS). Impu se response function is

ein use

to tr ce out the

yn mic inter ction mon v ri

es. It shows how the

yn mic response of the v ri

es in the system to shock or innov tion in e ch v ri

e. For computin the IRFS, it is essenti th t the v ri

es in the system re or

ere

n

th t movin ver e process represents the system. V ri nce

ecomposition is use

to

etect the c us re tions mon the v ri

es. It exp ins the extent t which v ri

e is exp ine

y the shocks in the v ri

es in the system. The forec st error v ri nce

ecomposition exp

ins the proportion of the movements in

sequence

ue to its own shocks verses shocks to the other v ri

es.5.0 V ri

e Description n

D t Points:

To ex mine the

yn mic interre tionship

etween stock n

forex m rkets in In

i , the stu

y consi

ere

two v ri

es such s stock price return n

exch n e r te(INR/USD) return. To represent the In

i n stock m rket, the present stu

y consi

ere

two iqui

ity in

ices here such s Sensex n

S & P CNX Nifty n

to represent the Forei n exch n e m rket, we h ve t ken into consi

er tion the nomin

i ter exch n e r te of In

i n Rupee versus US $. The stock return n

exch n e return is

efine

s f owin y.

1

They r ue th t the o of VAR n ysis is to

etermine the inter re tionship mon the v ri

es, not to

etermine the p r meter estim tes. The m in r ument inst

ifferenti tin is th t it throws w y inform tion concernin the co movements in the

t such s the possi

i ity of co inte r tin re tionships.

19


23/49

RSt = n (St) n (St 1) REt = n (Et) n (Et 1) Where, RSt n

REt represents the stock price return n

exch n e r te return n

St n

St 1 re the stock prices of time perio

t n

t 1 n

Et n

Et 1 re the exch n e r te of time perio

t n

t 1 respective y.

The present stu

y consi

ere

the month y

t of stock price n

exch n e r te,where the s mp e perio

sp nnin from Fe

ru ry 1995 to M rch 2005, formin roun

121 o

serv tions. The

t for stock prices re co ecte

from the respectivewe

p es of BSE n

NSE n

the

t on nomin

i ter exch n e r te (INR/USD) re co ecte

from the H n

ook of St tistics on In

i n Economy (2004 05).6.0 Estim te

Equ tion n

Resu t Interpret tion:

At the outset,

efore un

ert kin ny time series econometric n ysis of the

t , it wou

e usefu to see the

ro

tren

s n

eh vior of the v ri

es, which m y he p in interpretin the mo

e resu ts tter. For this purpose, time series p ots re

r wn for the v ri

es. Fi ures 3 to 8 p ot the month y movement of stock in

ices n

the exch n e r tes n

the r tes of return on their respective in

ices n

exch n e r te over the s mp e perio

. As c n

e expecte

, the month y

t on most of the v ri

es exhi

it tren

s (

oth stoch stic n

et

erministic)

n

consi

er

e vo

ti

ity, which v

rie

over time. It is

so quite c e r from these fi ures th t the returns exhi

it pronounce

c usterin , f ct consistent with the o

serve

empiric re u rities re r

in the sset returns s we s the exch n e r te returns. In the next step, we h ve compute

the

escriptive st tistics of the stock return n

exch n e r te return. The summ ryst tistics re presente

in the T

e 1. It c n

e seen from the t

e th t

othstock in

ices return (Rsensex n

Rnifty) re ne r norm . However, exch n e r te return is not norm n

more pe k th n in norm

istri

utions. This supports the ener o

serv tion th t forei n exch n e m rkets return is not norm

istri

ution,

ut the stock m rket returns re ne r norm . The pr ctic imp ic tion for the tr

in n

investin community in the fin nci m rkets is th t thereturn is ne r 20


24/49

norm

istri

ution s we h ve o

serve

in the c se of

oth stock in

ices (Rsensex, Rnifty), the investin n

tr

in str te y c n

e to

uy n

ho

for on sp n of time n

there wi

e some cert in profit out of the fore oin str te y. But if the return

istri

ution is not norm s we h ve o

serve

in the c seof forei n exch n e m rket in In

i , this str te y of

uy n

ho

for on time m y not necess ri y yie

ny c e r profit. Therefore, in forei n exch n e m rket convex tr

in str te ies where the tr

er m y

uy in m rket which is re

y ppreci tin

n

se in m rket which is

epreci tin

. However, we re not t this st e

e to o into the

et i s of

visin profit

e tr

in n

investin str te y from the for oin resu ts, n

in ny c se our resu ts re re ev nt for further investi tion n

rese rch. To ex mine the st tion rity property of the v ri

es use

in our stu

y, we h ve c rrie

out the ADF n

PP unit root test. A the tests h ve

een con

ucte

oth with intercept one n

with intercept n

time tren

2. The nu hypothesis is th t there exists unit root or the un

er yin process is non st tion ry. The resu ts of unit root tests re iven in T

e 2. The optimum en th in the c se of ADF n

PP tests is chosen on the

sis of AIC n

FPE criterion. From the t

e, we c n see th t thenu hypothesis is rejecte

i.e. the v ri

es re st tion ry t their return (Rsensex, Rer te, Rnifty) eve . However, the nu hypothesis c n not

e rejec

te

i.e.

the v

ri

es

re non st

tion

ry

t their

eve

(Sensex, Er

te, Nifty). Therefore, the OLS re ression c n

e run with the

t n

v ri

es t thereturn eve without the fe r of yie

in spurious p r meters. In or

er to seethe

e ree of ssoci tion

etween the stock return n

exch n e r te return thecorre tion m trix is constructe

. The resu ts re reporte

in T

es 5 n

6 respective y. From the T

e 5, it c n

e conc u

e

return on Sensex n

return onexch n e r te re ne tive y corre te

(r = 0.219) where s from T

e 6 thes me conc usion c n

e

erive

th t

oth return Nifty n

return exch n e r te re so ne tive y corre te

( r = 0.211). To ex mine the

epen

ence (

oth t

e ree n

irection)

etween the stock return n

exch n e r te return, the re

ression equ tions re estim te

y the metho

of or

in ry e st squ res (OLS), which metho

is justifie

e r ier s they re foun

to

e st tion ry2

Eviews 4.0 p ck e w s use

for the unit root tests.

21


25/49

v ri

es. The

equ cy of the equ tions in exp inin stock return n

exch n ereturn

eh vior re ju

e

y the ppropri teness of the si ns n

m nitu

es of the re ression coefficients, st tistic criteri such s the coefficient of mu tip e

etermin tion (R2), DW st tistic, for uto corre tion mon resi

u s, Tv ues of the re ression coefficients n

the st n

r

error of estim te (SEE),which re presente

in T

e 3 n

4 respective y. From the t

e, it is inferre

th t the coefficient of the exp n tory v ri

es preserve expecte

si n.In T

e 3, one percent

epreci tion of return er te (INR/US$) wi e

to 1.09 percent

ecre se in stock return (Rsensex). Like wise one percent incre sein stock return (Rsensex) wi e

to the ppreci tion in exch n e r te return

y 0.04 percent. In T

e 4, one percent

epreci tion in exch n e r te e

s to 1.03 percent

ecre se in stock return (Rnifty). Simi r y one percent incre se in stock return (Rnifty) e

s to ppreci te the exch n e r te return (INR/USD)

y 0.04 percent. This shows th t

oth stock return n

exch n e r te return re positive y re te

to e ch other.

The stock return n


. The po icy imp ic tion of this forementione

resu ts of the positive re tion

etween stock return n

exch n e r te return ppe rs to

e not to very oo

news for the for

ei

n investors in In

i

ec

use i

e

y, for the portfo

io

iversific

tion, thestock return n

oc currency return shou

e ne tive y corre te

ec use when they convert to the

se currency, if the oc currency is

epreci te

to ether with the re

uce

stock return, it

s to the oss r ther th n re

ucin the oss to their portfo io. However, this spect h s to

e further stu

ie

ec usethe return of the stock m rket in In

i m y


to the stock m rket return

ro

which wou

e re ev nt to the forei n institution investors. We h ve not ex mine

th t issue in the context of the corre tion

etween stock n

forex m rkets in In

i . Nee

ess to mention, for intern tion

iversific tion of the portfo ios, the corre tions with the stock m rkets e sewhereh ve so to

e further reex mine

. Moreover, when the return in the stock m rket oes

own, n

the stock prices o

own, there wi

e n o

vious su

stitutioneffect

enomin te

ssets to forei n from

omestic currency

ssets, n

therefore, the

omestic currency v ue oes

own, n

the return in the forei n exch n e m rkets from th t perspective so oes 22


26/49

own. Thus our resu ts of the positive corre tion

etween stock m rkets n

forei n exch n e m rkets c n e si y

e exp ine

in terms of positive

em n

for

omestic

currency when the

omestic stock prices incre se, n

the opposite ction when

omestic stock prices

ecre se n

the

em n

for

omestic currency f s. In the fores i

perspective, the c us ity is from

omestic stock prices to

omestic currency. The export firms m y not

e th t

omin nt to inf uence the c us ity from

epreci te

omestic

currency to stron stock price movement in the In

i n context.

As we mentione

in the st section,

etween ny p ir of v ri

es there is possi

i ity of uni

irection c us ity or

i

irection c us ity or none. This c n so

e the c se

etween two p irs of v ri

es use

in our empiric n ysis.These re stock return (

oth Rsensex n

Rnifty) n

exch n e r te return (Rer te). There re r uments in the iter ture to support more th n one type of re

tionship. We therefore wou

ike to ex

mine ex

mine the

irection of c

us

ity etween these two p irs of v ri

es

efore formu tin mo

e s to n yze the interre tionship

etween them. As our v ri

es in return form re re

y foun

in st tion ry, we c n

irect y procee

with Gr n er c us ity. In this c se, wec n exp in the c us ity throu h ch n es in one v ri

e c usin the ch n es in nother v ri

e which wou

e fin

out throu h Gr n er c us ity. The first step for the Gr n er c us ity test is to foun

out the ppropri te en th for e ch p ir of v ri

es. For this purpose, we use

the vector uto re ression (VAR) or

er se ection metho

v i

e in Eviews 4.0 p ck e. This techniqueuses six criteri , n me y o ike ihoo

v ue (Lo L), sequenti mo

ifie

ike ihoo

r tio (LR) test st tistic, Ak ike fin pre

iction error (FPE), Ak ike inform tion criterion (AIC), Schw rz inform tion criterion (SC) n

H nn n Quinn inform tion criterion (HQ), for choosin the optim en th. These specific tion criteri resu ts re reporte

in T

es 7 n

8 respective y. In pr ctice, it m y not

e possi

e th t the criteri wi su est one en th s optim . One m y h ve to

e content with en th supporte

y 2 3 criteri on y. In this stu

y, the optimum en th h s

een foun

out to

e 2 n

1 for return Sensex n

return er te n

return Nifty n

return er te respective y,

se

on two criteri , AIC n

FPE.

23


27/49

Fin y, the resu t of Gr n er c us ity test is reporte

in T

es 9 n

10. From

oth the t

e it m y

e conc u

e

th t the nu hypothesis th t there is noGr n er c us ity

etween the p irs c n not

e rejecte

on y in the c se of return Nifty n

return exch n e r te t 5 percent eve of confi

ence. However, inc se of other v ri

es the nu hypothesis is stron y rejecte

. From t

e 9,it is c e r th t the p st v ues of return Sensex

o not Gr n er c use the current v ues of return on exch n e r te. Simi r y the p st v ues of return on exch n

e r te

o not Gr n

er c use the present v ues of return on Sensex. From forementione

resu ts, it is c e r th t p st v ues

out the

respective m rkets (

oth stock n

forex)

o not inf uence the current v ues ofthe return in

oth stock (BSE Sensex) n

forei n exch n e m rkets. As the p stv ues of the

ifferent m rkets re re

y f ctore

n

incorpor te

in the returns of Sensex n

exch n e r tes. This shows th t there is inform tion efficiency in the m rkets of Sensex n

forei n exch n e r tes. These resu ts shou

e contr ste

with the re ression resu ts reporte

in T

e 3. In T

e 3, the current v ues of return on Sensex n

return on exch n e r te re inf uence

thecurrent r tes of return on Sensex n

exch n e r tes. These further shows th treturn Sensex n

return exch n e r te m rket re perfect y inte r te

with e ch

other. From T

e 2, we c

n see th

t the v

ri

es

re non st

tion

ry either

ttheir eve n

o eve form, n

in

ifference form, they re st tion ry. This supports the r n

om w k mo

e s of we k form of efficiency for respective m rkets. This is consistent with our resu ts reporte

e r ier th t the return Sensex n

return forei n exch n e m rkets re inform tion y efficient n

inte r te

with e ch other. In T

e 10, the p st v ues of the ch n es in exch n e r te return

o not Gr n er c use the ch n es on return on Nifty. However, the p stv ues of return Nifty

o Gr n er c use the current v ues of return in forei nexch n e m rket t 3 percent si nific nce eve . From this, it is surmise

th tthe stock m rket (Nifty) is more efficient from inform tion criteri th n the forei n exch n e (INR/USD) m rket. But from we k form of m rket efficiency point of view,

oth Nifty n

forei n exch n e m rkets fo ow the r n

om w k p ttern.Both t their eve n

o eve forms, they re non st tion ry n

t their

ifference

form they re st tion ry.

24


28/49

The resu t of

yn mic inter ction


exch n e r te returnis extr cte

y emp oyin Vector Auto Re ression technique. The resu t of forec st error v ri nce t 24 step he

horizon is reporte

in T

e 11 n

12 respective y. The impu se response


exch n e r te return is p otte

in Gr ph 1 n

2 respective y.Returns on Stock prices (BSE Sensex, NSE Nifty) n

Return on Exch n e r te (INR/US$)

In T

e 11, shock in return on er te exp ins on y 3.41 percent of forec st error v ri nce in return on Sensex, where s return on Sensex exp ins su

st nti portion i.e. 9.01 percent of forec st error v ri nce in return in exch n e r te from 6th step he

horizon onw r

s. From this fin

in , it c n

e surmise

th t the c us ity runs from return on Forei n exch n e r tes to return on Sensex s, t e st, 9 percent of the Return on Sensex is exp ine

y the Return on Forei n exch n e r tes. However, in T

e 12, return on Nifty exp ins 3.82 percent of forec st error v ri nce in return on exch n e r te where s m r in y hi her i.e. 4.10 percent of v ri nce in return on Nifty is exp ine

y return on exch n e r te from 5 step he

horizon. Thus we f i to conc u

e if the c us ityruns from Return on Nifty to return on exch n e r te or vice vers . From Gr ph 1

,

one st

n

r

evi

tion shock in return on Sensex exch

n

e r

te initi

y

ppreci tes up to secon

month n

in it ppreci tes n

conver es fter fifth month. Where s, one st n

r

evi tion shock in return on forei n exch n e r tereturn on Sensex initi y incre se up to secon

month n

ecre ses up to fourth month n

fter th t it conver es to the initi v ue. In Gr ph 2 one st n

r

evi tion shock in return on forei n exch n e r te incre ses the return onNifty up to fifth month n

then conver es.7.0 Conc usions:

Both the stock in

ices returns re ne r norm , where s exch n e r te return isnon norm n

more pe k. The pr ctic imp ic tion for the tr

in n

investin community in the fin nci m rkets is th t the return is ne r norm

istri

ution s we h ve o

serve

25


29/49

in the c se of

oth stock in

ices (Rsensex, Rnifty), the investin n

tr

in str te y c n

e to

uy n

ho

for on sp n of time n

there wi

e some cert in profit out of the fore oin str te y. But if the return

istri

ution is not norm s we h ve o

serve

in the c se of forei n exch n e m rket in In

i , this str te y of

uy n

ho

for on time m y not necess ri y yie

ny c e r profit. Therefore, in forei n exch n e m rket convex tr

in str te ies where the tr

er m y

uy in m rket which is re

y ppreci tin n

se in m rket which is

epreci tin

. However, we re not t this st

e

e to

o into the

et i sof

visin profit

e tr

in n

investin str te y from the for oin resu ts, n

in ny c se our resu ts re re ev nt for further investi tion n

rese rch. The stock return n


. The po icy imp ic tion of this forementione

resu ts of the positive re tion


exch n e r te return ppe rs to

e not to very oo

news for the forei n investors in In

i

ec use i

e y, for the portfo io

iversific tion,the stock return n

oc currency return shou


ec use when they convert to the

se currency, if the oc currency is

epreci te

to ether with the re

uce

stock return, it

s to the oss r ther th n re

ucin the oss to their portfo io. However, this spect h s to

e further stu

ie

ec use the return of the stock m rket in In

i m y


to th

e stock m

rket return

ro

which wou

e re

ev

nt to the forei

n institution

investors. We h ve not ex mine

th t issue in the context of the corre tion

etween stock n

forex m rkets in In

i . Nee

ess to mention, for intern tion

iversific tion of the portfo ios, the corre tions with the stock m rkets e sewhere h ve so to

e further reex mine

. Moreover, when the return in the stockm rket oes

own, n

the stock prices o

own , there wi

e n o

vious su

stitution effect

enomin te

ssets to forei n from

omestic currency

ssets, n

therefore, the

omestic currency v ue oes

own, n

the return in the forei n exch n e m rkets from th t perspective so oes

own . Thus our resu ts of the positive corre tion

etween stock m rkets n

forei n exch n e m rkets c n e si y

e exp ine

. exp ine

in terms of positive

em n

for

omestic currency when the

omestic stock prices incre se, n

the opposite ction when

omestic stock prices

ecre se n

the

em n

for

omestic currency f s.. In the fores i

perspective, the c us ity is from

omestic stock prices to

omestic currency.

26


30/49

The export firms m y not

e th t

omin nt to inf uence

the c us ity from

epreci te

omestic currency to stron stock price movement in the In

i n context From the Gr n ers c us ity test for return

t , it is foun

th t there is no c us ityfor the return series of stock n

exch n e r te except return Nifty n

return exch n

e r te. There is uni

irection c us ity

etween return Nifty n

return exch n e r te n

the c us ity is runnin from return Nifty to return exch n e r te. We wou

ike to interpret the c us ity resu ts s test of we kform of efficiency from n inform tion criteri s p st inform tions fromthe other m rket re incorpor te

throu h the r tion expect tions

y the investors in the respective current m rkets. Therefore, the p st inform tions from the other m rket wi not

e

e to pre

ict the return in the current m rket. Wem y note th t th t the simp e OLS re ressions resu t show th t the stock m rketinf uences the forex m rket n

vice vers . But inform tions from the otherm rkets re f ctore

into the returns of the respective current m rkets. From impu se response functions, it c n

e seen th t one st n

r

evi tion shock inthe return of ny m rket pro

uces the effect on the other m rket for few mont

hs

n

then conver

es. Therefore, the impu

se response function

so corro

or

tes our conc usion th t

oth the m rkets re efficient from the st n

point of thewe k form of m rket efficiency.

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