Pricing and Hedging of Oil Futures - A Unifying Approach -

We develop and empirically test a continuous time equilibrium model for the pricing of oil futures. The model provides a link between no-arbitrage models and expectation oriented models. It highlights the role of inventories for the identification of different pricing regimes. In an empirical study the hedging performance of our model is compared with five other oneand two-factor pricing models. The hedging problem considered is related to Metallgesellschaft ́s strategy to hedge long-term forward commitments with short-term futures. The results show that the downside risk distribution of our inventory based model stochastically dominates those of the other models. In the mid eighties highly liquid spot markets for crude oil superseded the integrated contract system of the major oil companies. As prices in the spot market tend to be highly volatile, risk management became an increasingly important issue in the oil business. This is reflected in the success of oil futures contracts at the New York Mercantile Exchange (NYMEX) and the International Petroleum Exchange (IPE). For example, in 2000 about 37 million crude oil futures contracts were traded on NYMEX, which represents a volume of 37 billion barrels, more than the worldwide oil production. An effective use of futures contracts in risk management requires an understanding of the factors determining futures prices and of the price sensitivities with respect to these underlying risk factors. In particular, the change of oil futures markets from backwardation into contango and vice versa needs to be captured. In the more recent literature on commodity futures pricing, two approaches have mainly been followed. The first one is based on the notion of a “convenience yield”, defined as the benefit which accrues to the owner of the commodity but not to the owner of the futures contract (Brennan (1991)). Important examples of this approach are the models of Brennan and Schwartz (1985), Gibson and Schwartz (1990), Brennan (1991), Schwartz (1997), Model 3, and Hilliard and Reis (1998). Despite their varying complexity all these models share the