Dynamics of systemic risk in European gas and oil markets under the Russia-Ukraine conflict: A quantile regression neural network approach

被引:11
|
作者
Zhou, En [1 ]
Wang, Xinyu [1 ]
机构
[1] China Univ Min & Technol, Sch Econ & Management, Xuzhou, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
Russia-Ukraine conflict; European energy markets; Quantile regression neural network; Systemic risk; Sensitivity analysis; GEOPOLITICAL RISKS; STOCK; VOLATILITY; CAVIAR;
D O I
10.1016/j.egyr.2023.03.030
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The Russia-Ukraine conflict (RUC) has triggered a serious natural gas (hereafter referred to as gas) and oil supply crisis in Europe. We propose a quantile regression neural network model to capture the non-linear evolution of systemic risk in the European gas and oil markets. We find that the RUC significantly increased systemic risk in both the European gas and the oil markets. The systemic risk is higher, and rises much more quickly and falls much more slowly in the gas market than in the oil market.The dynamics of systemic risk are closely linked to major events during the RUC. The US-dollar-to-ruble exchange rate contributes most to this systemic risk, followed by Europe's gas stocks and gas imports from Russia. In terms of risk exposure, the gas market is more vulnerable than the oil market. We propose an elasticity coefficient of systemic risk to evaluate its sensitivity to stress scenarios. Our study provides important insights into managing the systemic risk in European gas and oil markets after the RUC.(c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:3956 / 3966
页数:11
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