Abstract
Predicting the exchange rate fluctuations and volatility is possibly one of the very toughest exercises in economics as it affects the market movement. The dynamic relationship between stock prices and exchange rate have drawn the attention of many economists for both theoretical and empirical reasons and plays an important role in influencing the development of a country’s economy (Nieh & Lee, 2001). Therefore, the present study is focusing on stock market prices and exchange rate, which in theory, is expected that one affects the other. The US Dollar (USD)-Indian Rupee (INR) exchange rates and stock market prices of India from January 2006 to December 2015 are considered as sample data for this study. In this research, Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root tests are applied to test stationarity of data and the data was found stationary at first difference. Karl Pearson correlation test was used to find the correlating relationship between the variables and it is found that both the variables are significantly correlated. Johansen’s cointegration test is applied to determine the long-run equilibrium relationship between the study variables and identified that the variables are not cointegrated. Granger causality test is employed to determine the causality and short-run relationship between the variables and the result revealed bidirectional causality between variables.
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