Market Conditions and Stock Indices Hedging; A Markov Regime Switching Approach

This paper utilises a new approach for determining minimum variance hedge ratio in stock index futures markets. More specifically, the performance of time-varying hedge ratios generated from Markov Regime Switching (MRS) models is investigated. The rational behind the use of these models stems from the fact that the dynamic relationship between spot and futures returns may be characterised by regime shifts, which in turn suggests that by allowing the hedge ratio to be dependent upon the "state of the market", one may obtain more efficient hedge ratios and hence superior hedging performance, compared to other methods in the literature. The performance of the MRS hedge ratios is compared to that of alternative models that have been proposed in the literature such as GARCH, Error Correction and OLS models. In and out-of-sample tests indicate that the MRS hedge ratios outperform the other models in reducing portfolio risk in the FTSE 100 market. In the S&P 500 market the MRS model outperforms the other hedges only within sample. Overall the results indicate that by using MRS models, market agents may be able to increase the performance of their hedges, measured in terms of variance reduction.