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Risk spread in multiple energy markets: Extreme volatility spillover network analysis before and during the COVID-19 pandemic
Energy ; : 124580, 2022.
Article in English | ScienceDirect | ID: covidwho-1906985
ABSTRACT
Financial events in global energy markets could trigger extreme volatility spillovers and even become financial crises without effective risk management. To analyze extreme volatility spillovers in energy markets and demonstrate how risks are spread under extreme market conditions, this paper first measures the extreme volatility spillovers in the main energy markets from 2011 to 2019 using the vine Copula model then constructs the extreme volatility spillover networks based on their tail dependence correlations. Furthermore, the extreme risk spread is investigated by applying clique analysis. In consideration of the recent shock namely the COVID-19 pandemic, we further analyze the energy markets' extreme volatility spillovers in 2020. We find that extreme volatility spillover effects are stronger in renewable energy markets, especially during market booms and it also reflects an asymmetry feature of the energy markets’ extreme volatility spillovers. The water energy market is influential in the extreme volatility spillover networks. More significantly, there are strong volatility spillover effects among renewable energy markets, while risks are less likely to spread among non-renewable energy markets under extreme circumstances. We make contributions to reveal the volatility spillover under extreme conditions, then comprehensively analyze the risk spread in the extreme volatility spillover networks. By comparing how risks spread before and during the COVID-19, and between renewable and non-renewable energy markets, our findings could be of great help for policymakers and other stakeholders to cope with the uncertainties, especially in the extreme environment.
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Full text: Available Collection: Databases of international organizations Database: ScienceDirect Type of study: Prognostic study Language: English Journal: Energy Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: ScienceDirect Type of study: Prognostic study Language: English Journal: Energy Year: 2022 Document Type: Article