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Measuring the contribution of Chinese financial institutions to systemic risk: an extended asymmetric CoVaR approach

机译:衡量中国金融机构对系统风险的贡献:扩展不对称的COVAR方法

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摘要

This study proposes an extension of the Asymmetric CoVaR method in Espinosa et al. (J Bank Finance 58: 471-485, 2015) to capture the time-varying asymmetric responses of the financial system to positive and negative shocks to individual institutions. Building on the extended method and considering a set of Chinese financial institutions, we assess the extent to which distress within different institutions contribute to systemic risk. To provide a formal ranking of risk contributions, we implement the significance and dominance tests with bootstrap Kolmogorov-Smirnov statistics. The estimates of the extended Asymmetric CoVaR method reveal an asymmetric pattern that characterizes the tail interdependence in the Chinese financial system and this pattern changes dynamically over time. Particularly, the impact on the system of a fall in individual market value is only slightly larger than that of an increase during tranquil years. However, the entire system becomes extremely sensitive to downside losses than to upside gains during crises. The result also raises concern about privately owned banks in that they are systemically riskier than state-owned banks and other institutions. Using panel regressions, we also find firm characteristics such as institution size and volatility are important predictors of systemic risk contribution.
机译:本研究提出了espinosa等人的不对称CoVAR方法的延伸。 (J银行金融58:471-485,2015)捕捉金融系统的时变非对称回应对个别机构的积极和负面冲击。在扩展方法上建立一系列中国金融机构,我们评估了不同机构内遇险的程度促进了系统风险。为了提供风险贡献的正式排名,我们利用Bootstrap Kolmogorov-Smirnov Statistics实施了意义和优势测试。扩展不对称COVAR方法的估计揭示了一种不对称的模式,其特征在于中国金融系统中的尾部相互依存,并且这种模式随时间动态变化。特别是,对个人市场价值下降的影响仅略大于宁静岁月的增加。但是,整个系统对下行损失极为敏感,而是在危机期间上行增益。结果也提出了私人银行的担忧,因为它们的风险增长,而不是国有银行和其他机构。使用面板回归,我们还发现了机构规模和波动等公司的坚定特征是系统风险贡献的重要预测因素。

著录项

  • 来源
    《Risk Management: An International Journal》 |2020年第4期|310-337|共28页
  • 作者单位

    Cent South Univ Sch Business Changsha 410083 Hunan Peoples R China|Univ Windsor Supply Chain & Logist Optimizat Res Ctr Fac Engn Windsor ON Canada;

    Cent South Univ Sch Business Changsha 410083 Hunan Peoples R China;

    East China Univ Sci & Technol Dept Math Dept Finance Shanghai 200237 Peoples R China|East China Univ Sci & Technol Res Ctr Econophys Shanghai 200237 Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Systemic risk; Tail-risk dependence; Asymmetric CoVaR; Time-varying;

    机译:全身风险;尾风险依赖;不对称的COVAR;时变;

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