Within the GAＲCH-X framework put forward by the authors，this paper considers several new volatility forecasting models based on daily high，low，opening and closing prices of financial assets． These models combine the GAＲCH modeling procedure and the results of volatility estimation in the early literature，and therefore extend the static estimators into the dynamic driving factors of volatility． Empirical results with the daily prices of the Composite Index of Shanghai stock market over the last decade reveal that the forecasting performances of these new models for volatility and Value-at-Ｒisk are significantly better than the traditional GAＲCH model．