期刊
GLOBAL FINANCE JOURNAL
卷 35, 期 -, 页码 177-201出版社
ELSEVIER
DOI: 10.1016/j.gfj.2017.10.007
关键词
Oil spot price; Mean reversion price; Demand elasticity; Supply elasticity; Price scenarios
资金
- Texas A&M Engineering Experiment Station (TEES)
- Department of Statistics at Texas AM University
We propose price forecasting algorithms based on regression analysis of historic oil prices over 150 years (1861-2012). From 1986 onward daily market prices allow more detailed analyses of the principal crude oil benchmarks (West Texas Intermediate [WTI] and Brent). The mean reversion price for a given time period corresponds to the marginal cost of supply. When supply and demand are out of equilibrium, spot prices move in a bandwidth bound at the bottom by cash cost of supply and at the top by the concurrent price of demand destruction. Short-term elasticity of demand is 0.015 (highly inelastic), and long-term elasticity of supply changed from 0.99 (highly elastic) during 1965-1983 to 0.39 (less elastic) during 1984-2012. We derive functions for the long-term equilibrium price and expand them into scalable equilibrium price functions for forecasting future price scenarios if business-as-usual is assumed. We also consider how two hypothetical black swan events (unknown unknowns) may affect the mean equilibrium price.
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