Modelling Stock Market Volatility: Evidence from India

This study empirically investigates the volatility pattern of Indian stock market based on time series data which consists of daily closing prices of S&P CNX Nifty Index for ten years period from 1st January 2003 to 31st December 2012. The analysis has been done using both symmetric and asymmetric models of Generalized Autoregressive Conditional Heteroscedastic (GARCH). As per Akaike Information Criterion (AIC) and Schwarz Information Criterion (SIC), the study proves that GARCH (1,1) and TGARCH (1,1) estimations are found to be most appropriate model to capture the symmetric and asymmetric volatility respectively. The study also provides evidence for the existence of a positive and insignificant risk premium as per GARCH-M (1,1) model. The asymmetric effect (leverage) captured by the parameter of EGARCH (1,1) and TGARCH (1,1) models show that negative shocks have significant effect on conditional variance (volatility).