以沪深300指数的高频数据为例,采用滚动时间窗的样本外预测以及SPA检验法,对比了基于日收益数据的历史波动率模型和基于高频数据的实现波动率模型的预测能力。主要实证结果显示,实现波动率模型以及加入附加解释变量的扩展随机波动模型是预测精度最高的波动模型,但在学术界和实务界流行的GARCH及其扩展模型对我国A股市场波动的预测能力较差。
Taking high-frequency data of CSI300 index as example,the out-of-sample volatility predictions and a SPA test are used to evaluate the predicting ability for different historical volatility models and realized volatility models.The empirical results show that realized volatility model and the extended SV model are superior to other models.However the GARCH model and its extended type, which is popular in financial academe and practice,perform the worst for volatility predicting of Chinese A-share market.