Indian Stock Market Volatility Asymmetric GARCH Models

Over the last few years, modeling and forecasting volatility of a financial time series has become a fertile area for research. This is simply because of the fact that volatility is considered as an important concept for many economic and financial applications. The examples may refer to the portfolio optimization, risk management and asset pricing etc. This study models the volatility present in the inter-day returns in the stock of the two major national indices of India. Sensitive Index or S&P BSE SENSEX related to Bombay Stock Exchange (BSE) and S&P CNX NIFTY associated with National Stock Exchange (NSE). The focus is on daily stock return data corresponding to the 1990–2013 time intervals. The objective is to model the phenomena of volatility clustering and persistence of leverage effect in empirical time series using asymmetric GARCH family of models. Research showed that GJR-GARCH model successfully models both the S&P BSE SENSEX and S&P CNX NIFTY returns data.