Research on the Value at Risk of Basis for Stock Index Futures Hedging in China Based on Two-State Markov Process and Semiparametric RS-GARCH Model

摘要

This article aims to investigate the Value at Risk of basis for stock index futures hedging in China. Since the RS-GARCH model can effectively describe the state transition of variance in VaR and the two-stateMarkov process can significantly reduce the dimension,this paper constructs the parameter and semiparametric RS-GARCHmodels based on two-stateMarkov process. Furthermore, the logarithm likelihood function method and the kernel estimation with invariable bandwidth method are used for VaR estimation and empirical analysis. It is found that the three fitting errors (MSE, MAD, and QLIKE) of conditional variance calculated by semiparametricmodel are significantly smaller than that of the parametric model.Theresults ofKupiec backtesting onVaR obtained by the two models show that the failure days of the former are less than or equal to that of the latter, so it can be inferred that the semiparametric RS-GARCHmodel constructed in this paper ismore effective in estimating theValue at Risk of the basis for Chinese stock index futures. In addition, the mean value and standard deviation of VaR obtained by the semiparametric RS-GARCH model are smaller than that of the parametric method, which can prove that the former model is more conservative in risk estimation.