This paper aims at evaluating volatility forecasts of the Nigerian Stock exchange rate obtained through Asymmetric models. We make use of Monthly data from January, 2000 to January, 2012 to evaluate the parameters of each model and produce volatility estimates. The results show that the coefficient of (a determinant of the presence of volatility clustering) is statistically significant in the EGARCH model; this appears to show the presence of volatility clustering. The forecasting ability is subsequently assessed using the symmetric lost functions which are the Mean Absolute Error (MAE), Root Mean Absolute Error (RMAE), Mean Absolute Percentage Error (MAPE) and Theil inequality Coefficient. The results show that GJR-GARCH model provides best estimates for persistence, volatility clustering and leverage and asymmetric effects. The results also show that when the leverage and asymmetric effects are absent or minimal, GARCH model provides the most accurate forecast of future volatility.