Which determinant is the most informative in forecasting crude oil market volatility: Fundamental, speculation, or uncertainty?

Yu Wei, Jing Liu, Xiaodong Lai and Yang Hu

Energy Economics, 2017, vol. 68, issue C, 141-150

Abstract: This paper aims to identify the most informative determinant in forecasting crude oil market volatility. We use a new GARCH-class model based on mixed data sampling regression and the dynamic model averaging combination method to examine the predicting power of the determinants. We integrate both the global economic policy uncertainty (GEPU) indices and several national economic policy uncertainty (EPU) indices with traditional determinants, such as global oil demand, supply, and speculation. Our analysis suggests that the EPU indices comprehensively integrate the information contained in other determinants. Specifically, GEPU indices and the U.S.’s EPU index have superior predictive powers for West Texas Intermediate spot oil volatility. This finding highlights the importance of EPU indices, implying that they are key factors to consider when determining crude oil market volatility.

Keywords: Crude oil market; Volatility forecasting; GARCH-MIDAS; Dynamic model averaging method (search for similar items in EconPapers)
JEL-codes: C22 C52 Q43 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (151)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:68:y:2017:i:c:p:141-150

DOI: 10.1016/j.eneco.2017.09.016

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