Dependences and volatility spillovers between the oil and stock markets : New evidence from the copula and VAR-BEKK-GARCH models

Yu, L; Zha, R; Stafylas, D; He, K; Liu, J

Abstract

This paper examines the dynamic relationship between the oil market and stock markets from
two perspectives: dependence between the crude oil market (WTI) and stock markets of the
US and China, and volatility spillovers between them during 1991-2016. We further analyze
structural breaks of market dependences and consider the extent of their influence on such
relationships. Our vine-copula results show that the dependences between the three paired
markets, WTI-US, WTI-China and US-China, vary dynamically across the six identified
structural break periods. In particular, the dependence between WTI-US is stronger and more
volatile than that between WTI-China during most of the periods. The dependence between
US-China remains at a lower level in the earlier periods, but increases in the final period. Our
VAR-BEKK-GARCH results demonstrate distinctive volatility spillovers across these periods,
with varying directionality, in response to the structural changes. Overall, our results indicate
that the oil market stimulates rapid and continual fluctuations in market dependences, which
become manifest most acutely in the aftermath of the Financial Crisis of 2007-08,
demonstrating the increasing interdependence between the oil and stock markets. Further, the
growing influence of China on the dynamics of these relationships, in the period following the
Great Recession, presents evidence that it begins to assume an increasingly important role in
global economic recovery.
Keywords: Oil market; Stock market; Dependence; Volatility spillover; Copula model;
Multivariate GARCH model.

Citation

Yu, L., Zha, R., Stafylas, D., He, K., & Liu, J. (2020). Dependences and volatility spillovers between the oil and stock markets : New evidence from the copula and VAR-BEKK-GARCH models. International Review of Financial Analysis, 68, 101280. https://doi.org/10.1016/j.irfa.2018.11.007

• Journal Article Type: Article
• Acceptance Date: Nov 15, 2018
• Online Publication Date: May 7, 2019
• Publication Date: Mar 1, 2020
• Deposit Date: Dec 11, 2018
• Publicly Available Date: Nov 7, 2020
• Journal: International Review of Financial Analysis
• Print ISSN: 1057-5219
• Publisher: Elsevier
• Volume: 68
• Pages: 101280
• DOI: https://doi.org/10.1016/j.irfa.2018.11.007
• Publisher URL: https://doi.org/10.1016/j.irfa.2018.11.007
• Related Public URLs: https://www.journals.elsevier.com/international-review-of-financial-analysis/
• Additional Information: Funders : Key Program of National Natural Science Foundation of China;National Program for Support of Top-Notch Young Professionals; Beijing;Youth Foundation of Ministry of Education of China; Grant Number: 71433001; Grant Number: 71631005; Grant Number: 71671013; Grant Number: 16YJC790026