Volatility forecasting models for CSI300 index futures
Volatility forecasting models for CSI300 index futures
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发表时间：
2010
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通讯作者：
Weige Yu
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作者：
Weige Yu
以CSI300指数期货5分钟高频模拟交易数据为例，采用滚动预测方法计算这些模型的样本外日波动率预测，并采用自举SPA检验对不同历史波动率模型和实现波动率模型的预测精度进行评价。实证结果表明，基于高频数据的实现波动率模型和扩展的SV模型优于其他模型。然而，GARCH及其扩展模型在预测沪深300指数期货波动率方面表现最差。
Taking 5-minutes high-frequency mock trading data of CSI300 index futures as example,the out-of-sample daily volatility predictions of these models are calculated by using rolling predicting method,and a bootstrap SPA test is used to evaluate the predicting accuracy for different historical volatility models and realized volatility models.The empirical results show that,realized volatility model based on high-frequency data and the extended SV model are superior to other models.However the GARCH and its extended model,which are popular in financial academe and practice,perform worst for volatility predicting of CSI300 index futures.