Dynamic Causality Analysis of COVID-19 Pandemic Risk and Oil Market Changes

Mike K. P. So, Jacky N. L. Chan and Amanda M. Y. Chu
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Mike K. P. So: Department of Information Systems, Business Statistics and Operations Management, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China
Jacky N. L. Chan: Department of Information Systems, Business Statistics and Operations Management, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China
Amanda M. Y. Chu: Department of Social Sciences, The Education University of Hong Kong, Tai Po, Hong Kong, China

JRFM, 2022, vol. 15, issue 6, 1-11

Abstract: Crude oil draws attention in recent research as its demand may indicate world economic growth trend in the post-COVID-19 era. In this paper, we study the dynamic lead–lag relationship between the COVID-19 pandemic and crude oil future prices. We perform rolling-sample tests to evidence whether two pandemic risk scores derived from network analysis, including a preparedness risk score and a severity risk score, Granger-cause changes in oil future prices. In our empirical analysis, we observe 49% to 60% of days in 2020 to 2021 during which the pandemic scores significantly affected oil futures. We also find an asymmetric lead–lag relationship, indicating that there is a tendency for oil futures to move significantly when the pandemic is less severe but not when it is more severe. This study adopts preparedness risk score and severity risk score as proxy variables to measure the impact of the COVID-19 pandemic risk on oil market. The asymmetric lead–lag behavior between pandemic risk and oil future prices provides insights on oil demand and consumption during the COVID-19 pandemic.

Keywords: coronavirus; financial contagion; financial risk management; Granger causality test; network analysis; pandemic risk (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2022
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