Financial Risk and Management Reviews 2412-3404 2411-6408 10.18488/journal.89.2018.41.1.23 Financial Risk and Management Reviews Forecasting Equity Index Volatility: Empirical Evidence from Japan, UK and USA Data Financial Risk and Management Reviews Financial Risk and Management Reviews 06-2018 2018 06-2018 06-2018 4 1 1 23 17 Sep 2018 27 Nov 2018 Using non-linear models to forecast volatility for three equity index samples, this study examines weekly returns of three indices; Dow Jones Industrial index, FTSE 100 index, and Nikkei 225 index. The sample covers a twenty year sample period. The study employs an in sample and out of sample volatility forecast using standard symmetric loss functions in order to identify an appropriate model that best forecast volatility. Using the mean error (ME), root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE), the study finds the EGARCH model to outperform the ARCH, and GARCH model in forecasting volatility.