Volatility modeling with conditional volatility and realized volatility

This paper introduces the realized volatility (RV) into the variance equation of conditional volatility model, and a new conditional volatility model based on RV named RV-GARCH is constructed. The new model combines the advantages of ARCH-family models with the fluent information provided by the high frequency data. Through Monte Carlo simulation analysis and empirical study on Chinese Treasury bond index, it is shown that Realized volatility provides additional information to capture and forecast volatility of asset returns. The conditional distribution of return standardized by RV-GARCH model volatility is nearly normal, while that standardized by traditional GARCH model volatility is still characterized with high kurtosis and fat tail and not normal.