›› 2018, Vol. 30 ›› Issue (1): 24-35.

• 经济与金融管理 • 上一篇    下一篇

我国金融市场系统重要性机构的评估及政策启示

张天顶, 张宇   

  1. 武汉大学经济与管理学院, 武汉 430072
  • 收稿日期:2015-11-24 出版日期:2018-01-28 发布日期:2018-01-24
  • 作者简介:张天顶,武汉大学经济与管理学院副教授,博士生导师,博士,武汉大学美国加拿大经济研究所全职研究员;张宇,武汉大学经济与管理学院硕士研究生。
  • 基金资助:

    国家自然科学基金面上项目(71673205);国家社会科学基金重大项目(16ZDA032);武汉大学自主科研(人文社会科学)项目(2017QN028)。

Evaluating Chinese Systemic Important Financial Institutions and Some Policy Implications

Zhang Tianding, Zhang Yu   

  1. Economics and Management School, Wuhan University, Wuhan 430072
  • Received:2015-11-24 Online:2018-01-28 Published:2018-01-24

摘要:

本文引入成分期望损失方法,借助上市金融机构在资本市场上的日频交易数据,针对我国银行业、证券业、保险业以及信托业等金融部门的系统重要性机构进行测量和评估,同时针对研究结果采用条件在险价值的方法考察稳健性。实证研究发现:我国金融部门中系统重要性机构相对稳定,而且针对系统性风险测量表明风险主要集中于少数金融机构。根据不同金融部门的成分期望损失贡献度的相对比较,银行业在我国金融部门系统性重要机构评估中占据重要的地位,其次为保险业,证券业居其后。本文随后根据我国金融机构成分期望损失的贡献度对系统重要性程度划分了三个类别,政策制定者据此可以对处于不同类别中系统重要性程度不同的金融机构施加具有差异性的监管要求。最后,本文结合样本外成分期望损失值的预测,进行了稳健性分析,并结合研究发现提供了相关研究思路和政策启示。

关键词: 系统重要性金融机构, 系统性风险, 成分期望损失, 评估, 宏观审慎监管

Abstract:

This paper introduces a Component Expected Shortfall method and uses the daily transaction data to identify the China's domestic Systemic Important Financial Institutions (SIFIs) in the banking, securities, insurances and trust sectors, and then applies the CoVaR method to test their robustness. The research results show that the SIFIs ranking is relatively stable over time and concentrated in a small number of institutions. Thus, policy-makers can focus on the SIFIs, and policies needn't change frequently. A comparative analysis of the CES contributions by different financial sectors shows that the banking sector dominates in systemic importance identification, which is followed by the insurance sector and the securities sector. This paper also proposes an approach to allocate the SIFIs into three categories based on their CES contributions and the robustness test shows that this classification is reasonable and practical. Finally, this paper applies the out-of-sample analysis and compares the results with in-sample analysis. The forecast provides some new ideas and policies for both researchers and policy-makers.

Key words: systemic important financial institutions, systemic risk, component expected shortfall, evaluating method, macro prudential regulation