The ordinary least squares (OLS) technique (Ederington 1979; Figlewski 1984), the co-integration method (Ghosh 1993; Lien and Luo 1993), and the bivariate GARCH-type models allowing time-varying nature in asset returns (Baillie and Myers 1991; Kroner and Sultan 1993; Park and Switzer 1995; Gagnon and Lypny 1995; Kavussanos and Nomikos 2000; Bystrom 2003) are the most common approaches to estimate minimum-variance hedge ratios. However, those conventional approaches calculate the optimal hedge ratios in a sense of linear correlation and could result in bias estimates if the joint distribution of spot and futures is not elliptical and/or is non-linear. Since copula functions of asymmetric dependence structures and extreme values can capture the extreme co-movements of spot and futures, this study proposes a dependence-switching model (DS model), which is integrated by copula functions and Markov-switching model by Hamilton (1989, 1994) and is allowed that the dependence of spot and futures can switch between two different structures. We construct a hedging portfolio via the DS model and evaluate the dynamic hedging performance. The results show that the DS model outperforms the conventional approaches such as OLS ECM and DCC-GARCH.
