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A Semiparametric Forecasting Model for Volatility of Stock Index Futures and Its MCS Test
Pages: 14-24
Year: Issue:  4
Journal: Acta Scientiarum Naturalium Universitatis Sunyatseni

Keyword:  semiparametric forecasting modelstock index futuresrealized volatilityMCS test;
Abstract: Stock index futures plays an important role in the process of price discovery and risk preven-tion of capital market.The prediction of its return volatility is significantly important to achieve the risk a-version function of stock index futures.A semiparametric forecasting model based on the linear nonnega-tive autoregressive model is proposed to forecast the realized volatility of stock index futures,and the as-ymptotic properties of estimation method for this model are analyzed.In addition,taking 5 min high-fre-quency trading data of CSI300 index futures as example,the out-of-sample daily volatility predictions cal-culated by using rolling predicting method,and a bootstrap MCS test is used to evaluate the predicting ac-curacy for the proposed model and other 7 models.The empirical results show that,under various robust loss functions,the proposed model is the best model for volatility predictions of stock index futures among the 8 models.
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