This paper aims to demonstrate the superiority of Extended Mean-Gini (EMG) framework which is consistent with the second-order of stochastic dominance theory. The study provides a comprehensive analysis of investors’ distinct risk averse behavior towards optimal futures hedging strategy. The empirical distribution function method and the more efficient kernel estimation method are employed in the estimation of EMG hedge ratios. Furthermore, the moving data window procedure is used to examine the stability of the dynamic hedge ratios. The research is conducted on Malaysian Crude Palm Oil and CPO Futures markets for the period of 16th March 1995 to 28th June 2011. The empirical results show that the EMG approach is apparently more appropriate than the MV approach where EMG framework incorporates the risk aversion factor. The study also shows the instability of dynamic hedge ratios across time horizons hence not favorable to investors who adopt the “ buy and hold ” strategy.
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