Supply Disruptions and Predictability of Oil Returns Volatility: A GARCH-MIDAS Approach

Afees Salisu, Ahamuefula Ogbonna, Rangan Gupta and Luis Gil-Alana

No 202502, Working Papers from University of Pretoria, Department of Economics

Abstract: We utilize a Generalized Autoregressive Conditional Heteroskedasticity-Mixed Data Sampling (GARCH-MIDAS) framework to show that monthly indicators of global supply concerns and the United States, as well as its regional and product-specific indexes, based on 200 million shipment-level transactions, produces an increase in daily West Texas Intermediate (WTI) oil returns volatility over the period of January 2013 to August 2024. Furthermore, in-sample predictability for oil returns volatility carries over to statistically significant and robust short-, medium, and long-term forecasting gains derived from the information content of the various supply disruption indexes, relative to a benchmark model of GARCH-MIDAS-realized volatility (RV), over the out-of-sample period of January 2020 and beyond. The elaborate indexes of considered supply disruption is also shown to outperform other popular monthly measures defining global supply restrictions and economic conditions, when incorporated in the GARCH-MIDAS model. Our results have important implications for investors and policymakers.

Keywords: Oil markets volatility; Supply disruptions; GARCH-MIDAS model; Predictability (search for similar items in EconPapers)
JEL-codes: C32 C53 E23 Q40 Q43 Q47 (search for similar items in EconPapers)
Pages: 23 pages
Date: 2025-02
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Persistent link: https://EconPapers.repec.org/RePEc:pre:wpaper:202502

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