A Forecast Comparison of GARCH Models and Implied Volatility Jain Neeraj Assistant Professor, S.G.T.B. Khalsa College, University of Delhi, New Delhi, India Research Scholar, Department of Commerce, Delhi School of Economics, University of Delhi, New Delhi, India. neeraj2409@outlook.com Online published on 12 May, 2017. Abstract This research paper empirically investigates the performance of various models of volatility forecasting. Along with “unconditional standard deviation”, most commonly use measure of volatility, present research considered six others models of volatility forecasting, namely Standard GARCH (Generalized Autoregressive Conditional Heteroscedasticity) model, GJR-GARCH model, Exponential GARCH model (eGARCH), Asymmetric Power GARCH model (apGARCH), Component Standard GARCH model (csGARCH), and Option Implied Volatility model. To forecast volatility, the daily closing values of NSE Nifty 50 (Index) are considered from period 1st April 2002 to 31st March 2015, a span of 13 years. The present study found no single model as the best performing model. Overall performance found GJR-GARCH and option implied volatility having consistence performance. Interestingly, most commonly used model i.e. unconditional standard deviation found to be the worst model among all models studies in present research. Top Keywords Volatility, GARCH Family Models, Realized Volatility, Standard Deviation, Backtesting. Top |