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Nonlinear behavior of tail risk resonance and early warning: Insight from global energy stock markets

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  • Xie, Qichang
  • Fang, Tingwei
  • Rong, Xueyun
  • Xu, Xin

Abstract

This article calculates the tail risk of the global energy market and explores the nonlinear behavior of tail risk resonance at the global, regional and national levels from a dynamic perspective. Moreover, we apply various machine learning models to perform the experimental training on the drivers that affect tail risk resonance to establish a risk warning system. By simulation training and evaluation, we screen the optimal risk warning model and identify the important drivers of risk resonance in the energy market. The findings indicate that the energy system has a strong tail risk resonance phenomenon, and the occurrence of extreme events as well as a collapse in oil prices can significantly increase the system's risk resonance. The European region is the dominant risk emitter and the American region is the main risk receiver. The Russian-Ukrainian war significantly increased the risk resonance across regions. The Argentine energy market is the main receiver of tail risk and the US energy market is the primary sender of tail risk. By incorporating the risk factors into several machine learning models, the Random Forest model is found to provide effective early warning of tail risks. Additionally, importance analysis reveals that inflation levels, stock market volatility and trade policy changes are important factors affecting risk resonance in the energy market and have nonlinear effects on the risk resonance of the energy system.

Suggested Citation

  • Xie, Qichang & Fang, Tingwei & Rong, Xueyun & Xu, Xin, 2024. "Nonlinear behavior of tail risk resonance and early warning: Insight from global energy stock markets," International Review of Financial Analysis, Elsevier, vol. 93(C).
  • Handle: RePEc:eee:finana:v:93:y:2024:i:c:s1057521924000942
    DOI: 10.1016/j.irfa.2024.103162
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    More about this item

    Keywords

    Energy stock; Tail risk resonance; TENET method; Nonlinear impacts; Risk warning;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G01 - Financial Economics - - General - - - Financial Crises
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance

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