A Dynamic Hedging Approach for Refineries in Multiproduct Oil Markets

A multiproduct portfolio hedge ratio strategy for oil futures is investigated using a multivariate GARCH model based on dynamic conditional correlation and an error correction model (DCC-ECM-MVGARCH). By considering the characteristics of refiner profits from crack spread and the mutual relations among crude oil, gasoline and heating oil spot and future prices, we estimate the time-varying optimal hedge ratios for the oil-cracking margin. In addition, a naïve strategy, a traditional OLS model and dynamic BGARCH model are selected to compare with our model for hedge effectiveness. Comparison of hedge effectiveness for in-sample and out-of-sample data reveals that the dynamic DCC-ECM-MVGARCH model is more sensitive to market fluctuations, provides a more accurate description of changes in volatility and has more advantages than other models. Therefore, the empirical results prove that application of the DCC-ECM-MVGARCH model for hedging of oil market portfolio can play an important role in avoiding the double risk of crude oil and oil product markets for refineries