This study aims at examining the short-run and long-run dynamic linkages among exchange rates and stock market index in India through a structured cointegration and Granger causality tests. Daily exchange rates of USD, EUR, CNY, JPY, and... more
This study aims at examining the short-run and long-run dynamic linkages among exchange rates and stock market index in India through a structured cointegration and Granger causality tests. Daily exchange rates of USD, EUR, CNY, JPY, and GBP to INR along with the daily movement of NSE NIFTY for a period spanning 13 years from 6 September 2005 to 31 December 2018 were used for the analysis. The results reveal that there is no evidence for a stable long-run relationship between NSE NIFTY and the exchange rates under study. However, the VAR-based Granger causality test shows that USD, JPY, and CNY have short-run causal relationship with NSE NIFTY. The NSE NIFTY also seemed to have an influence on USD expressed in terms of Indian rupee. The impulse response analysis further supports the results of the Granger causality test and provides information on the time required for the NSE NIFTY index to recover from a shock caused by the fluctuation in exchange rates.
This study aims at examining the short-run and long-run dynamic linkages among exchange rates and stock market index in India through a structured cointegration and Granger causality tests. Daily exchange rates of USD, EUR, CNY, JPY, and... more
This study aims at examining the short-run and long-run dynamic linkages among exchange rates and stock market index in India through a structured cointegration and Granger causality tests. Daily exchange rates of USD, EUR, CNY, JPY, and GBP to INR along with the daily movement of NSE NIFTY for a period spanning 13 years from 6 September 2005 to 31 December 2018 were used for the analysis. The results reveal that there is no evidence for a stable long-run relationship between NSE NIFTY and the exchange rates under study. However, the VAR-based Granger causality test shows that USD, JPY, and CNY have short-run causal relationship with NSE NIFTY. The NSE NIFTY also seemed to have an influence on USD expressed in terms of Indian rupee. The impulse response analysis further supports the results of the Granger causality test and provides information on the time required for the NSE NIFTY index to recover from a shock caused by the fluctuation in exchange rates.
Market efficiency of Indian stock market based on the daily return of NSE Nifty and BSE Sensex form 1 January 1994 to 31 December 2015 is tested by applying Unit root, Autocorrelation, Run test and Variance ratio methodologies for seven... more
Market efficiency of Indian stock market based on the daily return of NSE Nifty and BSE Sensex form 1 January 1994 to 31 December 2015 is tested by applying Unit root, Autocorrelation, Run test and Variance ratio methodologies for seven sub-periods based on the trends and patterns in the movements of Indian market. The unit root tests like ADF and PP proved that the Indian stock market is non-stationary and contains a unit root. The auto correlation results are also revealed high degree of dependence on previous prices, which means that previous prices are related with current prices. The strong autocorrelation behaviour of the variable leads to non stationarity situation in data series, which means that the stock market movements are not in predictable manner. The run test results also proved that there is no randomness in Indian stock market. The results from the sub periods for each test are also giving the results which support the whole study period results. It clearly proved real behaviour of Indian stock market. From the results, it is clear that the Indian stock market does not follow random walk and it is in inefficient in its weak form. KEY WORDS :-Market efficiency, Weak form, Dependency behaviour of Market, Independent Movements, Random Movements.
