This paper develops a decision-analytic model to value commodity price forecasts in the presence of futures markets. The method is applied to a data set on crude oil prices. We find that to be valuable, forecasts must be accurate at predicting both gains and losses, and that there are positive and diminishing marginal returns to forecast value from improvement in key measures of accuracy. We also find that forecast value is specific to user class, and that value is unique to specific users within the class.

Keywords:
supply and demand pricing, Modeling & Simulation, Upstream Oil & Gas, transaction cost, Energy Economics, asset and portfolio management, futures market, discount rate, supply and demand forecasting, project valuation
Subjects:
Asset and Portfolio Management, Energy Economics, Project economics/valuation, Market analysis /supply and demand forecasting/pricing
Copyright 2007, Society of Petroleum Engineers
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