Econometric modelling for short-term oil price forecasting
2010; Wiley; Volume: 34; Issue: 1 Linguagem: Inglês
10.1111/j.1753-0237.2010.00171.x
ISSN1753-0237
AutoresAntonio Merino, Rebeca Albacete,
Tópico(s)Petroleum Processing and Analysis
ResumoOPEC Energy ReviewVolume 34, Issue 1 p. 25-41 Econometric modelling for short-term oil price forecasting Antonio Merino, Antonio Merino Chief Economist, Economic Research Department, Repsol, Paseo de la Castellana 278, 28046 Madrid, Spain. Email: amerinog@repsol.comSearch for more papers by this authorRebeca Albacete, Rebeca Albacete Senior Economist, Economic Research Department, Repsol, Paseo de la Castellana 278, 28046 Madrid, Spain. Email: ralbacetesm@repsol.comSearch for more papers by this author Antonio Merino, Antonio Merino Chief Economist, Economic Research Department, Repsol, Paseo de la Castellana 278, 28046 Madrid, Spain. Email: amerinog@repsol.comSearch for more papers by this authorRebeca Albacete, Rebeca Albacete Senior Economist, Economic Research Department, Repsol, Paseo de la Castellana 278, 28046 Madrid, Spain. Email: ralbacetesm@repsol.comSearch for more papers by this author First published: 13 April 2010 https://doi.org/10.1111/j.1753-0237.2010.00171.xCitations: 5 We thank Rodnan García for his help with the data and his comments. Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Abstract There is a lot of interest in forecasting oil price and in analysing which variables most affect price movements, especially whether non-fundamental variables such as financial activity have any systematic impact on oil price. In this paper we approach both questions by constructing a congruent econometric model with financial and fundamental variables and by analysing the relative weight of the variables in explaining the oil price forecast. After testing for different variables we find that the most accurate forecast from a monthly econometric vector model on oil price is obtained when non-commercial long positions, petroleum stocks and spare capacity are included as explanatory variables. The incorporation of non-commercial long positions clearly improves the accuracy of the prediction. The vector model is specified to include empirical cointegration relationship, which provides an approximation on the long-run restriction postulated by economic theory. Citing Literature Volume34, Issue1March 2010Pages 25-41 RelatedInformation
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