The study shows that using a combination of two forecasting models can help predict stock market volatility more accurately. By combining the realised GARCH model with extreme value theory, researchers were able to generate better forecasts for the S&P CNX NIFTY index. The new approach outperformed traditional models in predicting value-at-risk and expected shortfall. Overall, the realised-GARCH EVT models provided the most accurate forecasts, regardless of the method used to estimate volatility.