Do higher order moments of return distribution provide better decisions in minimum-variance hedging? Evidence from US stock index futures

Abstract

Using daily S&P 500 spot index and index futures data, this article examines the effects of conditional skewness and kurtosis parameters of a skew-Student density function on dynamic minimum-variance hedging strategies. We find an important role for autoregressive marginal skewness and joint kurtosis in risk management. While static higher order moments improve reductions in variance of hedged portfolios over the case of normality, the inclusion of an autoregressive component significantly extends these improvements. This occurs in both tranquil and tumultuous periods. Furthermore, when transaction costs are considered, taking into account variations of higher order moments retains the best performance. JEL Classification: G11, G13