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Forecasting Oil Volatility Using a GARCH-MIDAS Approach: The Role of Global Economic Conditions

Afees Salisu (), Rangan Gupta (), Elie Bouri () and Qiang Ji ()
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Qiang Ji: Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China; School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China

No 202051, Working Papers from University of Pretoria, Department of Economics

Abstract: In this study, we offer two main innovations. First, we subject six alternative indicators of global economic activity, including the one recently developed by Baumeister et al. (2020), to empirical tests of their relative predictive powers for crude oil market volatility. Second, we accommodate all the relevant series at their available data frequencies using the GARCH-MIDAS approach, thereby circumventing information loss and any associated bias. We find evidence in support of the ability of global economic activity to predict energy market volatility. Our forecast evaluation of the various indicators places a higher weight on the newly developed indicator of global economic activity by Baumeister et al. (2020), based on a set of 16 variables covering multiple dimensions of the global economy, than other indicators. The results leading to these conclusions are robust to multiple forecast horizons and consistent across alternative energy sources.

Keywords: Energy Markets Volatility; Global Economic Conditions; Mixed-Frequency (search for similar items in EconPapers)
JEL-codes: C32 C53 E32 Q41 (search for similar items in EconPapers)
Pages: 21 pages
Date: 2020-05
New Economics Papers: this item is included in nep-ene, nep-for, nep-mac and nep-sea
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