Oil Markets and Price Movements: A Survey of Models
Hillard Huntingtona, Saud M. Al-Fattahb, Zhuo Huangc Michael Gucwaa, and Ali Nouria
(Sept. 2011, Revised May 2013)
aEnergy Modeling Forum, Huang Engineering Center, Stanford University, 475 Via Ortega, Stanford, CA 94305-4121.
bKing Abdullah Petroleum Studies and Research Center, P.O. Box 88550, Riyadh 11672, Saudi Arabia; firstname.lastname@example.org
cPeking University, Beijing, 100871, China.
During the 1970s, oil market models offered a framework for understanding the growing market power being exercised by major oil producing countries. Few such models have been developed in recent years. Moreover, most large institutions do not use models directly for explaining recent oil price trends or projecting their future levels. Models of oil prices have become more computational, more data driven, less structural and increasingly short run since 2004. Quantitative analysis has shifted strongly towards identifying the role of financial instruments in shaping oil price movements. Although it is important to understand these short-run issues, a large vacuum exists between explanations that track short-run volatility within the context of long-run equilibrium conditions. The theories and models of oil demand and supply that are reviewed in this paper, although imperfect in many respects, offer a clear and well-defined perspective on the forces that are shaping the markets for crude oil and refined products.
The complexity of the world oil market has increased dramatically in recent years and new approaches are needed to understand, model, and forecast oil prices today. There are several kinds of models have been proposed, including structural, computational and reduced form models. Recently, artificial intelligence was also introduced.
This paper provides: (1) model taxonomy and the uses of models providing the motivation for its preparation, (2) a brief chronology explaining how oil market models have evolved over time, (3) three different model types: structural, computational, and reduced form models, and (4) artificial intelligence and data mining for oil market models.
Keywords: Oil models, oil prices, supply and demand analysis, financial markets.