A Trend Deduction Model of Fluctuating Oil Prices
AbstractCrude oil prices have been fluctuating over time and by a large range. It is the disorganization of oil price series that makes it difficult to deduce the changing trends of oil prices in the middle- and long-terms and predict their price levels in the short-term. Following a price-state classification and state transition analysis of changing oil prices from January 2004 to April 2010, this paper first verifies that the observed crude oil price series during the soaring period follow a Markov Chain. Next, the paper deduces the changing trends of oil prices by the limit probability of a Markov Chain. We then undertake a probability distribution analysis and find that the oil price series have a log-normality distribution. On this basis, we integrate the two models to deduce the changing trends of oil prices from the short-term to the middle- and long-terms, thus making our deduction academically sound. Our results match the actual changing trends of oil prices, and show the possibility of re-emerging soaring oil prices.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Fondazione Eni Enrico Mattei in its series Working Papers with number 2011.22.
Date of creation: Feb 2011
Date of revision:
Oil Price; Log-normality Distribution; Limit Probability of a Markov Chain; Trend Deduction Model; OPEC;
Other versions of this item:
- Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
- Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
- F01 - International Economics - - General - - - Global Outlook
- O13 - Economic Development, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
This paper has been announced in the following NEP Reports:
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Vo, Minh T., 2009. "Regime-switching stochastic volatility: Evidence from the crude oil market," Energy Economics, Elsevier, vol. 31(5), pages 779-788, September.
- Mark Holmes & Ping Wang, 2003. "Oil Price Shocks and the Asymmetric Adjustment of UK Output: A Markov-switching approach," International Review of Applied Economics, Taylor & Francis Journals, vol. 17(2), pages 181-192.
- Kosobud, Richard F & Stokes, Houston H, 1978. "Oil Market Share Dynamics: A Markov Chain Analysis of Consumer and Producer Adjustments," Empirical Economics, Springer, vol. 3(4), pages 253-75.
- Ibrahim Abada, 2012. "Study of the evolution of the northwestern European natural gas markets using S-GaMMES," Working Papers 1203, Chaire Economie du Climat.
- Ibrahim Abada & Pierre-André Jouvet, 2013. "A stochastic generalized Nash-Cournot model for the northwestern European natural gas markets: The S-GaMMES model," Working Papers 1308, Chaire Economie du Climat.
- Ibrahim Abada, 2012. "A stochastic generalized Nash-Cournot model for the northwestern European natural gas markets with a fuel substitution demand function: The S-GaMMES model," Working Papers 1202, Chaire Economie du Climat.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (barbara racah).
If references are entirely missing, you can add them using this form.