Combining minimum-CVaR hedging models with a novel maximum efficiency strategy for crude oil future

Combination hedging provides a powerful way to synthesize the information provided by individual models. This study propose a novel maximum-efficiency combination (MEC) to enhance hedging performance. Specifically, we treat hedging effectiveness as the pivotal criterion for competitiveness and derive combination weights by directly maximizing this metric. Based on the weekly WTI crude-oil futures prices from November 2004 to December 2023, the empirical results show that the proposed MEC strategy outperforms alternative combinations in reducing downside risks by combining different types of minimum-CVaR single models. Besides, combining the unconditional single models deliver the strongest performance among different combinations. The findings are robust to different confidence level and window width, and the superior performance of MEC can be attributed to two factors: flexible combination weights and the elimination of estimation error.