Proceedings of the 5th International Conference on Economic Management and Model Engineering, ICEMME 2023, November 17–19, 2023, Beijing, China

Research Article

Industry Systemic Risk Measurement Based on GARCH-EVT Method and Copula Function

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  • @INPROCEEDINGS{10.4108/eai.17-11-2023.2342748,
        author={Jiaxuan  Ding and Qianqian  Wang and Minrui  Chen},
        title={Industry Systemic Risk Measurement Based on GARCH-EVT Method and Copula Function},
        proceedings={Proceedings of the 5th International Conference on Economic Management and Model Engineering, ICEMME 2023, November 17--19, 2023, Beijing, China},
        publisher={EAI},
        proceedings_a={ICEMME},
        year={2024},
        month={2},
        keywords={garch evt-copula hybrid model; systemic risk; marginal expected loss; tail de-pendence},
        doi={10.4108/eai.17-11-2023.2342748}
    }
    
  • Jiaxuan Ding
    Qianqian Wang
    Minrui Chen
    Year: 2024
    Industry Systemic Risk Measurement Based on GARCH-EVT Method and Copula Function
    ICEMME
    EAI
    DOI: 10.4108/eai.17-11-2023.2342748
Jiaxuan Ding1, Qianqian Wang1, Minrui Chen1,*
  • 1: Zhuhai College of Science and Technology
*Contact email: 2295174035@qq.com

Abstract

The article uses data from the Shanghai and Shenzhen 300 Index and the Shen-wanwan Industry Index from 2010 to 2021, constructs a dynamic weighted mixed Copula model based on GARCH EVT, analyzes the dependence between each indus-try and the market tail, and explores the systematic risk contribution of each industry based on marginal expected loss (MES). The empirical results indicate that industries such as agriculture, forestry, animal husbandry, and fishing, as well as non banking and finance, have relatively low tail dependence, while industries such as real estate and household appliances have relatively high tail dependence; The banking industry has the smallest contribution to systemic risk, while the construction materials indus-try has the largest contribution; During the 2015 "stock market crash", the tail depend-ence between industry indices such as real estate and mining and market indices in-creased, with the most significant increase in risk contribution from the defense, mili-tary, and chemical industries.