Abstract

Hedging decisions in the real world often contradict the literature. We reverse-engineer the optimal hedging problem by identifying patterns of price behavior that warrant using strategies more sophisticated than variance minimization (MV). Historical time series of spot and futures prices for the crack spread components (crude oil, gasoline, and heating oil) are used to generate different patterns of price dependency. A copula approach is used to model the joint dependence between spot and futures price shocks of the three commodities. We find that minimizing a downside risk criterion (what actual hedgers do) leads to consistently better outcomes than MV, as measured by Expected Utility. This is especially true in scenarios corresponding to strong upward or downward price movements. We provide a simple decision heuristic for hedgers by identifying price patterns whereby using sophisticated strategies for multi-commodity hedging is optimal in practice.

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