Abstract: The classical volatility models, such as GARCH, are return-based models, which are constructed with the data of closing prices.It might neglect the important intraday information of the price movement, and will lead to loss of information and efficiency.This study introduces and extends the rangebased autoregressive volatility model to make up for these weaknesses and obtain satisfactory volatility predicting performance.The results consistently show that the new model successfully captures the dynamics of the volatility and gains good performance relative to GARCH model.Furthermore, we find that the inclusion of the lagged return can significantly improve the forecasting ability of the volatility model, and the leverage effect does exist in volatility.

Key words: volatility model, price range, intraday information, forecasting performance