Could the jump diffusion technique enhance the effectiveness of futures hedging models?

A multivariate Markov-switching ARCH (MVSWARCH) model in which variance/correlations for futures and spot returns is controlled by a state-varying mechanism is introduced and used to design a state-varying stock index futures hedge ratio. Additionally, a conventional random-variance framework, the MVGARCH (multivariate GARCH) model with a time-varying technique is employed and subjected to a benchmark model. The feasibility of these proposed models is examined using two types of spot positions selected from the U.K. stock markets: (1) the FTSE-100 market index, representing a well-diversified market portfolio, and (2) ten sub-stock indices defined by the Data Stream database, representing the sub-set of the market portfolio. The empirical results are consistent with the following notions. First, when futures and spot returns are simultaneously (individually) based on low or high volatility states, the corresponding correlation measure between futures and spot returns is higher (lower). Second, consistent with prior studies, the in-sample hedging effectiveness tests demonstrated the superior performance of the stat-varying hedge ratio generated by the MVSWARCH model in all cases. However, our empirical results further indicate that the out-of-sample performance of the MVSWARCH-based hedge ratio is statistically marginal when investors hold a well-diversified market portfolio as their spot position and tranquil periods are experienced.