Dynamic dependence and risk connectedness among oil and stock markets: New evidence from time-frequency domain perspectives. (1st February 2021)

• Record Type: Journal Article
• Authors: Cui, Jinxin; Goh, Mark; Li, Binlin; Zou, Huiwen
• Is Part Of: Energy. Volume 216(2021)
• Publication Date: 2021-02-01
• Subjects: Oil and stock markets -- Time-frequency domains -- Dependence structure -- Risk connectedness; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2020.119302
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: This paper investigates the time-frequency dependence and risk connectedness among oil and stock markets in oil-importing and oil-exporting countries using the wavelet coherence and BK frequency connectedness method. Those two methods allow us to capture the dynamics of the dependence and risk connectedness over time as well as across different frequency bands (i.e. 1–5 days, 5–22 days, and more than 22 days). The empirical results demonstrate that the dependence structures among oil and stock markets are stronger on long-term scales and the lead-lag associations among oil and stock markets are mixed and time-varying. The total risk spillovers among oil and stock markets are mainly transmitted in the long-run (i.e. more than 22 days). The oil market receives much more risk spillovers from the stock markets in the US, EU, Canada, and Russia. The dynamic risk spillovers at diverse frequency bands are time-varying and heterogeneous. Besides, the major international crisis events, such as the GFC, oil price collapse, and the COVID-19 pandemic have greatly intensified the risk spillover magnitude. The time-frequency dependence and risk spillover analysis can offer great benefits for those energy and financial market participants with multivariate time-horizons in asset allocation and risk management practices. Highlights: The nexus among oil and oil-importing and oil-exporting stock markets are considered. The wavelet coherence is applied to depict the time-frequency dependence structure. The frequency connectedness is used to quantify the time-frequency risk spillovers. The expected-shortfall (ES) is employed in measuring the risk connectedness. The GFC and COVID-19 pandemic significantly intensified the risk connectedness.