Volatility Spillovers between Stock Returns and Foreign Exchange Rate changes: Evidence from Three SAARC Countries

1. Volatility Spillovers between Stock Returns and Foreign Exchange Rate changes: Evidence from Three SAARC Countries By Qurat-ul-annAzmat NUST Business School

2. Introduction • Relationship between Stock Market and Foreign Exchange Market. • Advent of floating exchange rate in 1973, reforms of financial markets in early 1990s and Asian currency crisis in 1997-1998 have established a strong pitch for the dynamic relation ship between stock and foreign exchange markets (Mishra, 2004). • Floating exchange rate appreciation reduces the competitiveness of export markets; and has a negative effect on the domestic stock market (Yucel and Kurt, 2003). • For import dominated country, it may have positive effect on the stock market by lowering input costs (Adjasi et.al; 2008). NUST Business School

3. Empirical Evidence • Some studies show significant positive relationship between the two markets (Cheung and Westermann ; 2000). • While others show significant negative correlation between stock market and local currency (Solnik; 2000). • There are studies which have found weak or no relationship between the two markets (Bodart & Reding ;1999). NUST Business School

4. Seven South Asian countries- Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan and Sri Lanka- formed the South Asian Association for Regional Cooperation (SAARC) in 1985. • They formed the SAARC Preferential Trading Agreement (SAPTA) in 1993 and transformed it into South Asian Free Trade Area (SAFTA) in 2004 with a view to enhancing their productive capacity and the region’s trading interests. • Under the World Bank designated category, amongst the seven countries India, Pakistan Sri Lanka are considered developing countries. NUST Business School

5. Aim of Study • To investigate the dynamic relationship between foreign exchange market and stock market among the three SAARC countries i.e India, Pakistan and Srilanka. • If there is some link between these two markets how volatility in one market spill over to other market. • Time period (2001-2009) • Long run relationship :Engle Granger approch. • Volatility spillover: EGARCH NUST Business School

6. Implication Improved knowledge of volatility spillover effect between the stock and currency markets, and consequently the degree of their integration, will expand the information set available to international portfolio managers, multinational corporations, and policymakers for decision-making. NUST Business School

7. Literature Review • Flow oriented models [Dornbusch and Fisher (1980)] 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 and their stock prices. NUST Business School

8. Stock oriented models [Branson and Frankel (1983)] • Agents should allocate their entire wealth among domestic and foreign assets including currencies in their portfolio. • An increase in domestic stock prices leads individuals to demand more domestic assets. To buy more domestic assets, they are required to sell foreign assets as they are relatively less attractive now. As a result of which there is an appreciation of local currency due to more demand of domestic assets. NUST Business School

9. Kanas (2000) first uses EGARCH models in investigating the volatility spillover effects in US, Canada, Japan, UK, France, and Germany for the period between 1986 and 1998, his study shows significant symmetric spillover effects from stock market returns to foreign exchange rate changes. • Yang and Doong (2004) invested the same phenomenon using G-7 countries. The results point to significant volatility spillovers and an asymmetric effect from the stock market to the foreign exchange market for France, Italy, Japan and the US, suggesting integration between stock and foreign exchange markets in these countries. NUST Business School

10. Wu (2005) investigated the same phenomenon among Japan, South Korea, Indonesia, Philippines, Singapore, Thailand and Taiwan for the period 1997-2000 splitting the sample into crises and recovery periods. He found a bi-directional relationship between the volatility of stock returns and exchange rate changes during the recovery period in all countries except South Korea, as well as significant contemporaneous relationships between the two markets for most of the countries. Furthermore, he found volatility spillovers increased in the recovery period. NUST Business School

11. Data • Monthly average data related to stock indices and spot exchange rates was used. • For Pakistan KSE-100 index, India S&P CNX Nifty and Srilanka Colombo all share index prices were used. • Spot exchange rates of relevant currency of each country was taken in terms of US dollar. • Data sources: Yahoo finance and oanda.com. NUST Business School

12. Methodology • Following Kanas (2000) continuously compounded stock returns and exchange rate changes were calculated as the first differences of the natural log. Stock returns=Lnp(t)-Lnp(t-1) Exchange rates= Lnp(t)-Lnp(t-1) • Following Qyyum and Kamal (2006) for testing the existence of co integrating relationship between the stock market prices and the exchange rate Engle and Granger (1987) two step method was used. NUST Business School

13. For volatility analysis bivariate extension of the EGARCH (p,q) model was applied in order to examine whether the volatility of stock returns affects and is affected by the volatility of exchange rate changes within each economy. • The EGARCH specification (Nelson, 1991) is used in order to test whether the volatility spillover effects are asymmetric. NUST Business School

14. Conditional mean equation • Conditional Variance equation NUST Business School

15. Empirical Results • Descriptive Statistics Stock Returns and Exchange rate changes NUST Business School

16. Results of Augmented Dickey Fuller Test NUST Business School

17. Cointegration Results: Long term relationship and ADF test on residuals NUST Business School

18. EGARCH Estimation NUST Business School

19. Conclusion • The estimated results from cointegration analysis show that there is no long run relationship between the two markets. • Results show that volatility spillover effects from exchange rate changes to stock returns is significant in case of India and Sri Lanka which shows the integration of two markets while in case of Pakistan there is no significant spillover in both the markets. • Finally, for the asymmetric spillover effects result show that this effect is negative and significant for India from stock returns to foreign exchange rates and from exchange rates to stock returns in case of Sri Lanka. NUST Business School

20. References • Adjasi, C., Harvey, S. K., & Agyapong, D. (2008). Effect of Exchange Rate Volatility on the Ghana Stock Exchange. African Journal of Accounting, Economics, Finance and Banking, 3. Retrieved on 25 January 2011, from http://ssrn.com . • Behera, N. C. (2008). SAARC and Beyond Civil Society and Regional Integration in South Asia. South Asia Centre for Policy Studies, 19. • Bollerslov, T., & Wooldridge, J. M. (1992). Quasi-maximum Likelihood Estimation and Inference in Dynamic Models with Time-varying Covariances. Econometric Reviews, 11, 143-172. • Bodart, V., & Reding, P.(1999). Exchange Rate Regime, Volatility and • International Correlations on Bond and Stock markets. Journal of International Money and Finance, 18, 133-151. • Branson, W. H. (1983). Macroeconomic Determinants of Real Exchange Risk . In Managing Foreign Exchange Risk, R. J. Herring ed., Cambridge: Cambridge University Press. • Cheung, Y.W., & Westermann, F.(2000). Equity Price Dynamics Before and After the Introduction of Euro: A Note. CESifo, Munich. • Das, D. K. (2007).South Asian Free Trade Agreement: Prospects of Shallow Regional Integration. CSGR Working Paper 218 Coventry, University of Warwick. • Dornbusch, R., & Fischer, S. (1980). Exchange Rates and the Current Account. American Economic Review, 5, 960-971. • Engle, R., & Granger, C.W.J. (1987). Co-integration and Error-Correction: Representation, Estimation, and Testing, Econometrica, 35, 315-329. • Evans, M. D., & Lyons, R.(2001). Why Order Flow Explains Exchange Rates. Unpublished Working Paper. • Francis, B. B., Iftekhar, H., & Delroy M. H. (2002). Return Volatility Linkages in International Equity and Currency Markets, Bank of Finland Discussion Paper, 9. • Frankel, J. A.(1983). Monetary and Portfolio-Balance Models of Exchange Rate Determination. in Economic Interdependence and Flexible Exchange Rates, J.S. Bhandari and B. H. Putnam eds., Cambridge: MIT Press. • Kanas, A. (2000).Volatility Spillovers between Stock Returns and Exchange Rate Changes. Journal of Business Finance and Accounting, 27, 448-468. • Mishra, A.,K. (2004). Stock Market and Foreign Exchange Market in India: Are they Related? .South Asian Journal of Management, 11(2), 12-31. • Nelson, D. (1991). Conditional Heteroscedasticity in Asset Returns: A New Approach. Econometrica, 59, 347-370. • Qayyum, A., & Kemal, A.( 2006). Volatility spillovers between the stock market and the foreign market in Pakistan. Pakistan Institute of Development Economics, PIDE Working Papers, 7. Retrieved 20 January 2011, from http://ssrn.com/abstract=963308. • Solnik, B. (1987). Using Financial Prices to Test Exchange Rate Models- A Note, Journal of Finance, 42, 141-149. • Wu, R.(2005). International Transmission Effect of Volatility between the Financial Markets during the Asian Financial Crises. Transition Studies Review,15, 19-35. • Yang, S., & Doong, S. (2004). Price and Volatility Spillovers between Stock Prices and Exchange Rates: Empirical Evidence from the G-7 Countries. International Journal of Business and Economics, 3, 139-153. • Yucel, T., & Kurt, G. (2003). Foreign Exchange Rate Sensitivity and Stock Price: Estimating Economic Exposure of Turkish Firms. European Trade Study Group, Madrid. NUST Business School