 Predicting the oil prices: Do technical indicators help?Libo Yin () and Qingyuan Yang Energy Economics, 2016, vol. 56, issue C, 338-350 Abstract: This paper aims to investigate the predictability of technical indicators to directly forecast oil prices and compare their performances with macroeconomic variables. We find that technical indicators do exhibit statistically and economically significant in-sample and out-of-sample forecasting power under OLS regressions and forecast combinations, clearly exceeding that of well-known macroeconomic variables and state-of-the-art oil-macro forecasting variables. Moreover, the strength of the predictive evidence is substantial during recessions and expansions and can detect the typical decline in the oil returns near business-cycle peaks effectively. Furthermore, technical indicators reveal substantial economic value for investors, in terms of superior oil risk premium forecasts and sizable utility gains. The technical indicators' ability to predict the oil price stems in part from its ability to predict changes in sentiment, suggesting the financialization of oil markets. Keywords: Oil price predictability; Technical indicators; Macroeconomic variables; Out-of-sample forecasts; Business cycle (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:56:y:2016:i:c:p:338-350 DOI: 10.1016/j.eneco.2016.03.017 Access Statistics for this article Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant More articles in Energy Economics from Elsevier |
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