Relationship between Exchange Rate Movements and Stock Market Returns in India

BUSINESS RESEARCH Methods

ABSTRACTThe study attempts to examine the interactions between the BSE stock prices and four major world exchange rates, namely, US Dollar, Euro, Great Britain Pound and Japanese Yen. Data relating to BSE stocks and the named currencies were taken at the last date of each month from 31st January 2000 to 31st December 2013 and used for the analysis. Short term and long term relationships have been measured using the Causality test, Engle Granger Co-integration Test and Unit-root Test. The Granger causality test shows that stock prices Granger cause exchange rates of US Dollar and Japanese yen but there is no reverse causation from U.S Dollar and Japanese Yen returns to BSE stock returns. There is a unidirectional causal relationship from returns of Euro to BSE stock returns but no reverse causation from BSE stock returns to returns of Euro. Also, there is no causal relationship between BSE stock returns and Great Britain Pound (GBP). Finally, the Co-integration test showed the existence of long-relationship between BSE stock returns and the four currencies taken.

INTRODUCTIONIndian stock market slipped below the trillion-dollar level in terms of total valuation of all listed companies this morning, as downward pressure continued on rupee and share prices. Since April 2013, Indian stock market has fallen by 4 per cent (from Rs. 63.88 lakh crore to Rs. 60.90crore) in rupee terms, but around 18 per cent (from $1,209 billion to $992 billion) in dollar terms. The rupee has depreciated by over 12 per cent during this period reported on 6th August 2013. Besides this, the Financial Crisis of 2008 witnessed drastic fluctuations in stock market and foreign exchange markets. During the Asian crisis of 1997-98, the world had noticed that emerging markets collapsed due to substantial depreciation of exchange rates (in terms of US$) and dramatic fall in stock prices. Such observations highlight the importance of studying the association between exchange rate movements and stock market returns.Exchange rate is simply the price of one currency in terms of another currency. A currency is said to be appreciating (depreciating) when its price/value in terms of another currency increases (decreases). An exporting firm (importing firm) will benefit from the depreciation (appreciation) of the local currency through its impact on the competitiveness of the firm in the international market. There has been a considerable debate over making a choice between a fixed exchange rate regime and a floating exchange rate regime. Factors affecting exchange rate are current account deficits, interest rate differential between countries, external debt and economic and political conditions. On the other hand, stock market is a market in which shares of publicly held companies are issued and traded either through exchanges or over-the-counter markets. A rise (fall) in the share price will benefit the seller (buyer) of the share. Factors affecting stock price movements are GDP, inflation, money supply, interest rate, trade balance, firms performance, employment, etc.There already exist theories which tell us that there exist interaction relations between stock prices and exchange rates. However, empirical research results dont always support these theories. There are two approaches which support the existence of a relationship between exchange rate movements and stock market returns.The first approach is the Goods Market Approach which suggest that variations in exchange rates affect the competitiveness of a firm as fluctuations in exchange rate affect the value of firms earnings and cost of the funds borrowed in foreign currencies and hence its stock price. An appreciation of the domestic currency reduces the earnings of an exporting firm as it reduces the foreign demand for its products and hence reduces its stock price. On the other hand, a depreciation of the local currency improves the competitiveness of an exporting firm by making its product more attractive and hence increases the earnings as well as the stock price of the firm. The influence of exchange rate fluctuations on the value of an importing firm will be opposite to that of an exporting firm. Apart from this, exchange rate changes also affect the cost (value) of the borrowed (lent) funds denominated in foreign currency and affect the value of a firms future payables (or receivables) in foreign currency. Thus, exchange rate movement affects the stock market returns through its impact on the value of a firms earnings and its payables (receivables).The second approach is the Portfolio Balance Approach which focuses on the supply and demand mechanism for the determination of exchange rate. A booming stock market in a country would increase the demand for its local currency as foreign investors would be attracted towards the growing stock market and would result in capital flows from the investors. With the falling stock market, investors would prefer to sell their stock and convert their money denominated in local currency into foreign currency to move out of the country with the falling stock market. So growing stock market/rising stock prices would increase the demand for a countrys currency and hence lead to appreciation of the local currency. And the falling stock prices would decrease the demand for a countrys currency and hence lead to depreciation of the local currency.With such diverse hypotheses, there is a need to study the relationship between stock market and exchange rate movements, particularly in India because India has witnessed many episodes of drastic variations in exchange rate and stock prices and hence it is important to understand the underlying relation behind such movements. Also, India is one among such countries which has moved from a fixed exchange rate regime to a floating exchange rate regime since the financial crisis of 2008. So a study in this field will help the policymakers, economists and investors to predict the trends in exchange rates (stock prices) from the stock price movements (exchange rate movements), provided there exists a relationship between the two variables.The studies already conducted in this area have given contradicting results with no general consensus. So a detailed research is required in this area to arrive at a consensus. This research paper is an attempt to study the dynamic relationship between exchange rate movements and stock market returns. In examining the relationship between stock prices and exchange rates, the important question is whether changes in the stock prices affect exchange rates or vice-versa. To approach this question, we use three tests: Grangers causality test, Co-integration test and Unit Root test.

LITERATURE REVIEWSince Relationship between exchange rate movements and stock prices play an essential role in Indian economy, it is of great concern to many professionals, policymakers, economists and investors. Here is an account of the research done on this topic:Guan Zhao (2008) analysed the relation between two variables stock prices and exchange rates for New Zealand market. Four major techniques were used to study the relationship, which were simple regression, measuring foreign exchange exposure on the return of the stock, multi factor arbitrage model to explore whether there is link between foreign exchange risk and common stock return for U.S, Canada, and Japan and lastly, the Co-integration and Granger Causality. The result indicates that there is no long run relationship between these exchange rates and New Zealand Stock Exchange when we use both daily and weekly data.

Benjamin M. Tabak (2006) studied the dynamic relationship between Stock prices and exchange rates using evidence of Brazil. Linear and nonlinear Granger causality tests were employed. It was found that there is no long run relationship, but granger causality from stock prices to exchange rates with negative correlation. Also it was found of nonlinear Granger causality from exchange rates to stock prices in line with traditional approach.

Nath and Samanta studied the dynamic relation between exchange rate and stock prices in India. The study indicates that stock market returns has causal influence on return in exchange rate with possibility of minimal influence in reverse direction.

Gaurav Agrawal and Ankita Srivastava (2010) analysed the relationship between BSE returns and Rupee and U.S Dollar exchange rates. Investigating the causal relationship between the two variables highlights unidirectional relationship from returns on BSE and Exchanges rates.

I.S.A. Abdalla and V.Murinde (1996) analysed the relationship exchange rate and stock price interactions in emerging financial markets of India, Korea, Pakistan and Philippines. The macro and micro economic factors were considered. The model used to conduct the study was Grangers Causality Test. For the sample they selected they chose all non-OCED countries, which had adopted a floating interest rate. The tests conducted on the sample included ADF, Grangers Causality and Error Correction model. Results show that Granger-cause stock prices in Korea, Pakistan and India, where as stock prices Granger-cause exchange rates in the Philippines.

Sheng-Yung-Yang* and Shuh-Chyi Doong (2004) studied the Price and Volatility Spillovers between the stock prices and exchange rates of the G-7 counties. The expansion in foreign trade and the floating rates regimes encouraged them to study this topic. The data they collected was of the closing exchange rates and stock market indices of the G-7 countries. For analysis they used the Vector Autoregressive model, Exponential GARCH and Quasi-Maximum Likelihood Estimation. The results point out movement in stock prices will affect future exchange rate movements, but changes in exchange rates have less direct impact on the stock prices. Md. Lutfur Rahman and Jashim Uddin (2008) investigated the interactions between stock prices and exchange rates in the emerging economy of Bangladesh. Johansen test showed that there is no co-integrating relationship between the stock prices and the exchange rates of US Dollar, Euro, Japanese Yen and Pound sterling. The exchange rates and stock prices data series are non-stationary. Grangers causality test was used to show that stock prices Granger cause exchange rates of US Dollar and Japanese Yen but there is no causal relationship between stock prices and exchange rates of Euro and Pound sterling.Gopalan Kutty (2010) examined the relationship between stock prices and exchange rates in Mexico. The results showed that stock prices lead exchange rates in the short run and there is no long run relationship between these two variables.Basabi Bhattacharya and Jaydeep Mukherjee (2006) investigated the causal relationship between stock prices and macroeconomic aggregates in the foreign sector in India. Unit root test, co-integration test and long-run Grangers non-causality test were used to test the causal relationships between the BSE Sensitive Index and three macroeconomic variables - exchange rates, foreign exchange reserves and value of trade balance. The results showed that there is no causal linkage between stock prices and these three variables.Muhammad, Naeem and Abdul Rasheed (2002) examined the short-run and long-run associations between stock prices and exchange rates for four South Asian countries and used the Grangers causality test, co0integration test and error correction modelling approach. The results showed no short-run and long-run relationships between stock prices and exchange rates for Pakistan and India. There was a bi-directional long-run causality between these variables for Sri Lanka and Bangladesh.

DATA AND METHODOLOGYSources of DataOur study is directed towards observing the dynamics between stock market volatility and exchange rate movements. The study has focussed upon four foreign currencies namely Japanese Yen, Great Britain Pound (GBP), U.S Dollar and Euro. For data on stock market returns, the study has chosen the CNX BSE stock prices. The frequency of data is kept at monthly level and the time of study is from January 2000 to December 2013.The data consists of:1. Monthly closing prices of the BSE index to compute stock market returns.2. Monthly Exchange rates of Yen, GBP, U.S Dollar and Euro expressed in terms of Indian Rupees, used to compute exchange rates.The sources of the data are Yahoo Finance and Money Control.MethodologyGrangers Causality Test:Grangers Causality Test is used for testing whether one time series is sufficient to predict another time series. The Grangers causality test attempts to determine whether the past values of a variable are helpful in predicting the changes in another variable. According to this test, variable Y is granger caused by Variable X if Variable X assists in predicting variable Y. This in turn, means that the lagged values of Variable X are statistically significant in explaining Y. The null hypothesis that is tested here is that X does not Granger Cause Y and Y does not Granger Cause X.Co-Integration Test: In a time series analysis, co-integration is a pre-requisite for a long term relationship between the variables, having unit roots. Two or more variables are said to be co-integrated if they both are non-stationary. Through Johansen approach, it is possible to determine the number of co-integrated vectors for any number of variables that are non-stationary. Co-integration test is used to determine whether the group of non-stationary variables is co-integrated or not. Through ADF test once it is established that the series is non-stationary or in other words, it means that it is integrated of order (1), we test whether they are co-integrated. This means that using co-integration test, it can be established whether the variables have a long term relationship or not.Unit Root Test: While using a time series data for estimating the parameters using Ordinary Least Square Estimate (OLSE), many econometric variables can be found to influence. When one time series variable is regressed on another time series variable, using OLSE, the value of R^2 can be very high, in spite of the fact that there is no co-relation between the variables. This can lead to some unauthentic regression between variables that are totally unrelated. Thus, prior to testing for Grangers Causality, it is essential to test whether the variables are stationary or not for each and every time series. The test for stationary variables is usually done using a unit root test for the order of integration. A series is said to be stationary if the mean and variance remain constant with time. Of the variables chosen are non-stationary, the assumptions based upon which Grangers Causality can be computed would not be valid.

ANALYSISResults of the Unit Root TestThe null and the alternate hypotheses for this test are as follows: H0: The series has unit root (The series is stationary)H1: The series does not have a unit root (The series is not stationary)The Augmented Dickey Fuller unit root test was employed to examine the stationarity property of series. The results are given in table 1. The results show that null hypothesis is rejected for the series in first difference. This implies that monthly price of BSE, U.S. Dollar, Japanese Yen, Great Britain Pound and Euro are not stationary in ADF level statistic. However, series are found to be stationary in ADF - first difference.Results of the Grangers Causality TestTable 2 shows the results of the Pairwise Granger Causality test.The table shows that there is a unidirectional relationship from BSE stock returns to returns of U.S Dollar and Japanese Yen since the p-values are less than 0.05 at 1% level of significance. There is no reverse causation from U.S Dollar and Japanese Yen returns to BSE stock returns. There is a unidirectional relationship from returns of Euro to BSE stock returns but no reverse causation from BSE stock returns to returns of Euro.There is no short-term relationship from BSE stock returns to returns of Great Britain Pound.Results of the Co-Integration TestThe null and the alternate hypotheses for this test are as follows: H0: There is a long term relationship between BSE stock returns and US $, Japanese Yen, GBP and Euro.H1: There is no long term relationship between BSE stock returns and the respective exchange rates.Table 3 shows the results of Engle Granger Co integration test. The results show that for all the currencies, the p-values are less than 0.05 at 1% level of significance.It shows the residuals from co-integration regression are stationary and are integrated of order zero, indicating that there is a long term relationship between BSE stock returns and U.S Dollar. Similarly, BSE is found to be co-integrating with Euro, Japanese Yen and Great Britain Pound.

FINAL REMARKSThrough this research study, we analysed the relationship between BSE stock and foreign exchange markets using monthly data from January 2000 to December 2013. The study investigates the short-run as well as the long-run relationship between stock prices and exchange rates by using Grangers Causality test, Co-integration test and Unit Root test. The results show that there is a unidirectional causality from BSE stock returns to returns of US Dollar and Japanese Yen. A unidirectional causality is found from Euro returns to BSE stock returns. The results also show that BSE stock is co-integrating with US Dollar, Japanese Yen, GBP and Euro.

REFERENCES 1. Yahoo finance, https://in.finance.yahoo.com/2. Money control, http://www.moneycontrol.com/currency/3. Abdalla, I S A and V Murinde (1997), Exchange Rate and Stock Price Interactions in Emerging Financial Markets: Evidence on India, Korea, Pakistan, and the Philippines, Applied Financial Economics, Vol. 7, February.4. Bahmani-Oskooee, M and A Sohrabian (1992), Stock Prices and the Effective Exchange Rate of the Dollar, Applied Economics. 5. Neih, C C and C F lee (2001), Dynamic Relationships between Stock Prices and Exchange Rates for G-7 Countries, The Quarterly Review of Economics and Finance.6. Sheng-Yung Yang*, Shuh-Chyi Doong (2004), Price and Volatility Spillovers between Stock Prices and Exchange Rates: Emperical Evidence from G-7 Countries, International Journal of Business and Economics.7. Rahman, Md. Lutfur and Jashim Uddin (2008), "Relationship between Stock Prices and Exchange Rates: Evidence from Bangladesh", International Journal of Business and Management, Vol. 3, No. 98. Ajay, R A and M Mougoue (1996), "On the Dynamic Relation between Stock Prices and Exchange Rates", Journal of Financial Research9. Kutty, Gopalan (2010), "The Relationship between Stock Prices and Exchange Rates: The Case of Mexico", North American Journal of Finance and Banking Research, Vol. 4, No. 410. Bhattacharya B and J Mukherjee (2006), "Indian Stock Price Movements and the Macroeconomic Context - A Time-Series Analysis", Journal of International Business and Economics, Vol. V, No. 111. Muhammad, Naeem and Abdul Rasheed (2002), "Stock Prices and Exchange Rates: Are They Related? Evidence from South Asian Countries", The Pakistan Development Review, Vol. 41(4)12. Aydemir, O and E Demirhan (2009), "The Relationship between Stock Prices and Exchange Rates: Evidence from Turkey", International Research Journal of Finance and Economics13. Guan Zhao (2008), The interrelationship between New Zealand stock market and exchange rates, Unpublished work, Auckland University of Technology.14. Tabak. B (2006), The dynamic Relationship between Stock Prices and Exchange Rates: Evidence for Brazil, International Journal of Theoretical and Applied Finance.15. Nath C Golaka and G P Samantha (2003), Relationship between Exchange Rate and Stock Price in India: An Empirical Analysis. Unpublished.16. Gaurav Agrawal, Aniruddh Kumar Srivastav and Ankita Srivastav (2010), A study of Exchange Rates and Stock Market Volatility, International Journal of Business and Management, Vol. 5, No. 12

Annexures:Table 1: ADF: Augmented Dickey Test

VariableADF level Statisticp-valueADF-First Differencep-value

BSE Sensex1.3510.653-31.01210.0167

Euro-2.020.298-36.61240

U.S. Dollar-1.5890.489-38.78560.001

Japanese Yen-0.6630.286-43.21340

GBP-1.9080.223-27.6160

Table 2: Pairwise Granger Causality Test

F-ValueP-Value

BSE Sensex --> U.S.Dollar-4.112640.0167

U.S. Dollar --> BSE Sensex0.058760.34164

BSE Sensex --> EURO1.396720.21846

EURO --> BSE Sensex4.010.01421

BSE Sensex --> GBP1.83210.1823

GBP --> BSE Sensex0.6670.548

BSE Sensex --> Japanese Yen5.01020.0088

Japanese Yen --> BSE Sensex1.51020.612

Table 4: Engle - Granger Co - Integration Test

(a) Co - Integration between Sensex and U.S. Dollar (St = 0 + 1USt+ut)

VariableCo efficientt - Statisticp - value

Constant0.29782.8570.1312

U.S. Dollar-1.6134-10.01370.0001

R^20.5124

D-W-Statistic0.00579

Residual based on Co-integration ( u=ut-1+vt)

Variable ADF-StatisticP-value

^u-41.00150

(b) Co - Integration between Sensex and EURO (St = 0 + 1Eurot+ut)

VariableCo - efficientt Statisticp - value

Constant0.201530.458970.5891

EURO2.382119.59760

R^20.6547

D-W-Statistic0.00702

Residual based on Co-integration ( u=ut-1+vt)

Variable ADF-StatisticP-value

^u-45.31060

(c) Co - Integration between Sensex and GBP (St = 0 + B1GBPt+ut)

VariableCo - efficientt Statisticp - value

Constant17.194126.0310

GBP-1.7989-11.43220

R^20.4351

D-W-Statistic0.002975

Residual based on Co-integration ( u=ut-1+vt)

Variable ADF-StatisticP-value

^u-1.61234-0.39987

(d) Co - Integration between Sensex and Japanese Yen (St = B0 + B1JapaneseYent+ut)

VariableCo - efficientt - Statisticp - value

Constant0.0821831.059870.3001

Japanese Yen0.3089774.768170

R^20.7041

D-W-Statistic0.5565

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