A stochastic model for correlated commodity prices

Abstract

Stochastic models of commodity prices play an integral role in the risk management of companies exposed to commodity price risk. By applying price models, one can obtain expected values for the future prices of the commodity, and also a measure of the uncertainty related to the future price. These figures are crucial for risk management, for example in assessing the need for price hedging. In this thesis, we propose a model for the price development of two correlated products. The model can be used for forecasting future prices for two correlated products simultaneously, and hence it also allows us to simulate the price spread between the products. The model can be a useful tool for companies seeking to hedge price spread risk, or for investors seeking to speculate on the price spread. Providing a real-life example from the oil market, we will use genuine data from Brent and WTI futures trading. This thesis utilizes the Schwartz and Smith (2000) model as a basis for developing the model for two correlated products. Also, a three-factor model is proposed in order to describe observed price data more precisely.