Hedging Strategy Using Copula and Nonparametric Methods: Evidence from China Securities Index Futures

Abstract

Calculating accurately the optimal hedge ratio plays an important role in the futures market for both practitioners and academicians. In this paper, we combine copula and nonparametric technique, where marginal setting is modeled by nonparametric technique and bivariate is linked by dynamic Patton (2006)'s SJC copula function, to estimate the parameters of optimal hedge ratio. Various types of GARCH models to fit the marginal distribution are also compared. Furthermore, model specification for marginal setting is investigated by Hong and Li (2005)'s statistics, which test the i.i.d. and U(0,1) simultaneously. The empirical results show that transformed residuals generated by nonparametric technique are i.i.d. U(0,1), while most of one generated by popular GARCH-type are not. For hedging effectiveness, our methods perform better than traditional copula-GARCH models. The robust test also supports the results. Keywords: Hedge Strategy; Optimal Hedge Ratio; Nonparametric Estimation; Patton (2006)'s SJC-Copula; Hong and Li (2005)'s Statistics; CSI 300 Index Futures. JEL Classifications: C49; G10; G15