Modeling Asymmetric Volatility in Indian Stock Market

The main feature of any financial instruments is stochastic nature of its returns. The spread of outcome of return from the asset is called volatility which influences numerous financial decisions. The main goal of estimating the volatility is to assess the market risk. Volatility is one of the key parameters for pricing financial derivatives. Estimation of volatility helps in risk management and it also helps in efficient management of portfolios. In the present study, asymmetric nature of volatility is modeled by applying two popularly used asymmetric GARCH models i.e., GJR-GARH model and PGARCH model. BSE-Sensex is used as a proxy for Indian stock market and period of study is from 1st july, 1997 to 30th march, 2013. Results of Augmented Dickey Fuller test reveals that the natural logarithmic values of Sensex returns and S&P 500 returns are stationary at their level form. Results of analysis with selected asymmetric GARCH models reveals the presence of leverage effect in Indian stock market and it also confirms the effect of periodic cycles on the conditional volatility in the market. In order to test whether the selected asymmetric GARCH models adequately captured the persistence in volatility and to test whether residuals from the selected models are free from ARCH effect, ARCH LM test is conducted. Results of ARCH-LM test concludes that there is no ARCH effect left in residuals obtained from both GJR-GARCH Model and PGARCH Model estimations.