Dynamic comovement and extreme risk spillovers between international crude oil and China's non-ferrous metal futures market. (January 2023)

• Record Type: Journal Article
• Authors: Zhang, Tianding; Zeng, Song
• Is Part Of: Resources policy. Volume 80(2023)
• Publication Date: 2023-01
• Subjects: Crude Oil -- China's non-ferrous metals -- Comovement -- Risk spillovers -- Cycle; F65 Q02; Mines and mineral resources -- Periodicals; Ressources minérales -- Périodiques; Ressources naturelles -- Gestion -- Périodiques; Environnement -- Politique gouvernementale -- Périodiques; 333.8
• DOI: 10.1016/j.resourpol.2022.103263
• Languages: English
• ISSNs: 0301-4207

Abstract

Abstract : This paper analyses the dynamic comovement and extreme risk spillovers between international crude oil and China's non-ferrous metals futures by combining the application of Copula and CoVaR models, considering the effects of structural breaks and the frequency of cycles. The results show a positive linkage between crude oil and China's non-ferrous metals, with significant long-period comovement. Upside risk in crude oil prices can generate stronger extreme shocks to non-ferrous metals, as evidenced by the outbreak of COVID-19 in 2020. Compared to zinc and aluminum, copper is more susceptible to risk spillovers from crude oil, particularly in the event of a downside trend in crude oil. In addition, WTI crude oil and Brent crude oil show some variability in the upper and lower tail spillover effects. Our research explained to some extent the time-varying, cyclical and asymmetric impact on the non-ferrous metal futures market under crude oil shocks, which can be informative for industry planners, regulators, and investors in making targeted decisions. It is mainly the case when dealing with the many effects of geopolitical conflicts, trade frictions, and commodity supply and demand mismatches. Highlights: The time-varying dependence structures between crude oil and China's non-ferrous metal futures are explored. The decomposition of the variational mode decomposition (VMD) model is embedded in the copula approach. The conditional value-at-risk (CoVaR) and value-at-risk (VaR) are estimated for exploring the risk spillovers.