| Summary: | 碩士 === 國立中央大學 === 財務金融研究所 === 94 === In the thesis, the S&P 500 index is used to compare the accuracy of forecasting volatility by the GARCH-Jump model developed by Maheu and Mccurdy (2004) relative to the benchmark GJR-GARCH model with normal distribution. We use the criteria of , MSE, and P to evaluate the accuracy of forecasting volatility one period into the future, as well as 5-, 10-, and 15-period forecasts. Two volatility targets are calculated by the 5-min prices, realized volatility and bipower volatility. They allow us to obtain theoretical ex post jump measures. Then, we test whether models added the last previous jump measures improve the accuracy of forecasting volatility, which implies that jumps occurred past the period make an effect on future volatility. Finally, we compare results with different volatility targets.
We find that the GARCH-Jump model and the models added the last previous jump measures do not provide superior volatility forecasts. The results of two volatility targets are the same. This implies that adding jump component would noise the accuracy of forecasting index volatility.
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