期刊
ENERGY
卷 231, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2021.120949
关键词
COVID-19; Oil futures; Main board and second board stock markets; GARCHSK-Mixed copula-CoVaR-network; Multidimensional risk spillovers
资金
- National Natural Science Foundation of China [71671145, 71971191, 71973028]
- Natural Science Foundation of Fujian Province, China [2017J01518]
- Projects of Social Science Planning in Fujian [FJ2020B120]
- Humanities and social science fund of ministry of education of China [17YJA790015, 17XJA790002, 18YJC790132, 18XJA790002]
- Science and technology innovation team of Yunnan provincial universities [2019014]
- Yunnan Fundamental Research Projects [202001AS070018]
The study indicates that during the COVID-19 period, the risk spillovers between oil and stocks are more pronounced, with significant risk spillovers from the US and Chinese stock markets to the oil markets; the impact of the second board stock markets on the oil market is significant, especially during the COVID-19 outbreak; and the bidirectional risk spillovers between China and oil have rapidly increased during the COVID-19 pandemic.
This paper investigates the multidimensional risk spillovers among crude oil, the US and Chinese stock markets during the COVID-19 epidemic through a GARCHSK-Mixed Copula-CoVaR-Network method. Firstly, we find that during the COVID-19 period, the oil-stock risk spillovers are obviously stronger than those during the normal period. And there are significant risk spillovers from the US and Chinese stock markets to the oil markets. It is also discovered that the oil markets are greatly influenced by the second board stock markets, also known as the growth enterprise markets, especially during the COVID-19 outbreak. Furthermore, the bidirectional China-oil risk spillovers during the COVID-19 pandemic have rapidly increased. Besides, it is reported that the relationships across oil futures, main board and second board stock markets in the US and China are stable under different TSI levels and extreme events. Finally, the GARCHSK-Mixed Copula-CoVaR-Network outperforms the control groups in terms of marginal distribution and dependence structure. Our study not only offers new method and insight into the oil-stock relationship, but also has economic implications for investors and policymakers. (c) 2021 Elsevier Ltd. All rights reserved.
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