Dynamic Hedging with Futures: A Copula-Based GARCH Model

摘要

In a number of earlier studies it has been demonstrated that the traditional regression-based static approach is inappropriate for hedging with futures, with the result that a variety of alternative dynamic hedging strategies have emerged. In this study the authors propose a class of new copula-based GARCH models for the estimation of the optimal hedge ratio and compare their effectiveness with that of other hedging models, including the conventional static, the constant conditional correlation (CCC) GARCH, and the dynamic conditional correlation (DCC) GARCH models. With regard to the reduction of variance in the returns of hedged portfolios, the empirical results show that in both the in-sample and out-of-sample tests, with full flexibility in the distribution specifications, the copula-based GARCH models perform more effectively than other dynamic hedging models.