<p>Extreme risks in the oil market driven by major crises have emerged as a critical threat to global financial stability. This paper investigates extreme risk contagion from the oil market to the global stock market system from the perspective of network interconnectedness. Using the spatial autoregressive model, our study shows that extreme risks in the oil market can spread widely across global stock markets via their network connections. On this basis, we develop tail risk networks, including the MODWT-CoVaR and MODWT-VaR networks, to further examine extreme risk contagion from the oil market to the global stock market system. The empirical results demonstrate the existence of such contagion and its heterogeneity across time scales. Furthermore, extreme oil market risks have a pronounced impact on the network connection structure of global stock markets over the medium to long term. Finally, the results indicate that during turbulent periods, developed Euro-American stock markets, especially those in the United States, Canada, and the Netherlands, are more likely to transmit extreme oil market risks throughout the global stock system. Overall, our findings suggest that global policymakers should consider oil-to-stock risk contagion behavior from a network-based systemic perspective to better manage energy market risks and maintain the stability of the global financial system.</p>

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Revisiting Extreme Risk Contagion from the Oil Market to Stock Markets: A Systemic Perspective Based on Network Interconnectedness

  • Yueli Liu,
  • Xiu Jin,
  • Jinming Yu

摘要

Extreme risks in the oil market driven by major crises have emerged as a critical threat to global financial stability. This paper investigates extreme risk contagion from the oil market to the global stock market system from the perspective of network interconnectedness. Using the spatial autoregressive model, our study shows that extreme risks in the oil market can spread widely across global stock markets via their network connections. On this basis, we develop tail risk networks, including the MODWT-CoVaR and MODWT-VaR networks, to further examine extreme risk contagion from the oil market to the global stock market system. The empirical results demonstrate the existence of such contagion and its heterogeneity across time scales. Furthermore, extreme oil market risks have a pronounced impact on the network connection structure of global stock markets over the medium to long term. Finally, the results indicate that during turbulent periods, developed Euro-American stock markets, especially those in the United States, Canada, and the Netherlands, are more likely to transmit extreme oil market risks throughout the global stock system. Overall, our findings suggest that global policymakers should consider oil-to-stock risk contagion behavior from a network-based systemic perspective to better manage energy market risks and maintain the stability of the global financial system.