Affiliation:
1. Center for Petroleum Asset Risk Management The University of Texas, Austin, Texas, USA
Abstract
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.
Subject
Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment
Cited by
3 articles.
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