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中国管理科学 ›› 2021, Vol. 29 ›› Issue (5): 14-24.doi: 10.16381/j.cnki.issn1003-207x.2019.0150

• 论文 • 上一篇    下一篇

保险业在金融系统性风险传染路径中起到“媒介”作用吗?——基于金融市场尾部风险传染路径的实证分析

王耀东1,4, 冯燕2,3, 周桦2,3   

  1. 1. 中央财经大学经济学院, 北京 100081;
    2. 中央财经大学保险学院, 北京 100081;
    3. 中国精算研究院, 北京 100081;
    4. 中信建投证券股份有限公司, 北京 100010
  • 收稿日期:2019-01-25 修回日期:2019-06-24 出版日期:2021-05-20 发布日期:2021-05-26
  • 通讯作者: 王耀东(1993-),男(汉族),河南汝州人,中央财经大学经济学院硕士研究生,研究方向:金融系统性风险、宏观量化,E-mail:wangyaodong1993@163.com. E-mail:wangyaodong1993@163.com.
  • 基金资助:
    国家社会科学基金资助青年项目(18CJY063)

Does Insurance Play a “Media” Role in the Path of Financial Systemic Risk Contagion?——Empirical Analysis on the Tail Risk Contagion Path of the Chinese Financial Market

WANG Yao-dong1,4, FENG Yan2,3, ZHOU Hua2,3   

  1. 1. School of Economics, Central University of Finance and Economics, Beijing 100081, China;
    2. School of Insurance, Central University of Finance and Economics, Beijing 100081, China;
    3. China Institute for Actuarial Science, Central University of Finance and Economics, Beijing 100081, China;
    4. China Security Company, Beijing 100010, China
  • Received:2019-01-25 Revised:2019-06-24 Online:2021-05-20 Published:2021-05-26

摘要: 2008年金融危机之后,保险业固有的不会产生系统性风险的传统认知被打破。关于保险业在金融系统性风险传染路径中的角色定位,本文从其业务特点和风险传染特点出发,首次提出"媒介"作用的猜想并进行实证研究。本文沿用当前主流研究方法,利用尾部风险的传染网络来研究其媒介作用的大小。本文选取了包括6家上市保险机构在内的34家金融机构,研究区间跨度为2011到2018年。根据金融市场数据"厚尾"和"非对称性"特征,文章首先采用AR-(GJR)GARCH-Skew-t模型对股票收益序列进行处理,然后根据Copula函数,计算尾部相依度,再通过最小生成树和阈值方法构建金融市场的风险传染网络。本文还通过构建保险业媒介中心度来探究其媒介作用的程度。实证结果表明:(1)在金融市场风险传染网络中,保险业起到连接银行市场和证券市场的重要媒介作用;(2)保险机构中又以多元化经营的中国平安的风险传染作用最强,其次是中国人寿。(3)银行市场中的兴业银行和保险市场的联系最紧密,证券信托市场则是中信证券、广发证券等。研究明确了风险传染的路径和关键性节点,为制定更具针对性的系统性风险监管措施提供了参考。

关键词: 系统性风险, 保险市场, Copula, 尾部相依度, 媒介中心度

Abstract: After the financial crisis, the traditional perception that insurance industry does not generate systemic risks was broken. By the analysis of its business characteristics and risk contagion characteristics, the conjecture of the ‘media’ role and conduct empirical research regarding the role of the insurance industry in the path of financial systemic risk contagion network was put forward. The empirical research follows the current mainstream research methods, using the tail risk infection network to study the magnitude of its median effect. 34 listed financial institutions including six listed insurance institutions are selected for empirical analysis, and the study period is from 2011 to 2018. According to the "thick tail" and "asymmetry" features of financial market data, the AR-(GJR) GARCH-Skew-t model is chosen to process the stock return sequences, and then the tail dependence degree can be calculated by the Copula function. Finally, the Minimum Spanning Tree and Threshold Method are used to construct risk contagion network in financial market. An index of insurance media centrality index based on betweenness centrality is constructed to explore the role of insurance industry in the systemic risk contagion network. The empirical results are showed as follows:(1) In the risk contagion network of financial markets, the insurance industry plays an important role in connecting the banking market and the security market; (2) The risk contagion effect of Ping An, which is a diversified insurance company, is the strongest, followed by China Life Insurance. (3) In the banking market, Industrial Bank and insurance market are most closely connected, while for the securities trust market is CITIC securities and GF securities. The path and key nodes of risk contagion network are identified in our study, which is very helpful to provide a reference for the formulation of more targeted systemic risk supervision measures. The innovation of this paper is to identify the "intermediary" role of the insurance industry in the financial risk contagion network from an empirical perspective, which is of certain value to academic research and practical systemic risk regulation.

Key words: systemic risk, insurance market, Copula, tail dependence, media

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