Journal Press India^®

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Volatility plays a very important role in any financial market around the world. Accurate forecasting of volatility is essential for taking wise and timely decisions for transacting financial products and to manage other financial applications. The goal of any volatility model is to be able to forecast volatility. In this paper “VOLATILITY FORECAST OF BSE LTD. BROAD INDICES”, focuses on volatility forecasting through three widely used time series volatility models namely, the Historical Variance, time series of univariate data, the Generalized Autoregressive Conditional Heteroscedastic Model (GARCH) and the Risk Metrics, Exponential Weighted Moving Average (EWMA) . The characteristics of these volatility models are explored using monthly data on the BSE broad indices for a period of 4 years. (Jan 2010 to Jan 2014). “VOLATILITY FORECAST OF BSE LTD. BROAD INDICES”, analysis through GARCH(1,1) of BSE S&P, BSE MIDCAP, BSE SMALL CAP, BSE 100, BSE 200 and S&P 500 have shown the volatility ranging from 1.52 to 6.87%, whereas the same indices through Exponential Generalized Autoregressive Conditional Heteroscedastic Model (EGARCH )model has shown the volatility range from 4.55 to 10.59%.

Keywords

Volaitity forecast, BSE broad indices, Time series, Generalized Autoregressive Conditional Heteroscedastic Model (GARCH), Risk metrics, Exponential Weighted Moving Average (EWMA)

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