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基于分位数回归商业银行系统性风险研究

Studies on Commercial Banks Systemic Risk based on Quantile Regression

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【作者】 寿晖张永安

【Author】 SHOU Hui;ZHANG Yong-an;School of Economics and Management,BeijingUniversity of Technology;School of Finance,Jiangxi University of Finance and Economics;

【机构】 北京工业大学江西财经大学

【摘要】 在宏观审慎监管框架下,对系统重要性银行的识别并对其提出更高监管要求是金融危机后的监管重点。文章选取代表不同类型的8家上市商业银行为样本银行,采用CoVaR模型和分位数回归技术对2007-2011年实体经济和金融数据进行实证分析。实证表明:从流动性方面看,资产规模较大的银行反而面临更高的流动性风险,其风险溢出效应更容易导致系统性风险的聚集,发生危机时对系统性风险贡献较大;在宏观经济周期逆转时,中小型银行相对大型银行更容易出现风险溢出效应导致系统性风险聚集;因此政策建议:银行业监管当局的监管重点在传统的资产规模庞大的银行,同时也要关注银行业务增长过快的中小银行,这些银行往往也是系统性风险聚集和金融危机爆发的始作俑者。

【Abstract】 Under prudential macroeconomic policy framework, the key supervision focuses on the identification of systemically important banks and their regulatory requirement. The paper empirically studies on eight different types of sample commercial banks by CoVaR model and quantile regression techniques. The finding is that from perspective of liquidity, the larger asset banks face higher liquidity risk, which is more likely lead to spillover aggregation of systemic risk. However downturn in the macroeconomic cycle, medium and small banks are more prone to risk spillover cause systemic risk. Therefore, policy recommendations are that the banking supervisory authority focuses on not only the traditional sizeable international banks asset, but also concerned about the medium and small banks of excessive business growth. These banks are also systemic risk aggregation and initiator of financial crisis.

【基金】 教育部人文社会科学研究项目(07JA630044);北京市教委重点资助项目(S0011212201002)
  • 【文献出处】 技术经济与管理研究 ,Technoeconomics & Management Research , 编辑部邮箱 ,2014年09期
  • 【分类号】F832.33
  • 【被引频次】16
  • 【下载频次】495
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