基于静态与动态CoVaR方法银行系统性风险研究
发布时间：2019-05-16 01:58
【摘要】：近年来我国金融市场发展跌宕起伏,接二连三发生多起风险事件,2013年的"钱荒","债灾",2015年年中和2016年初的股灾,这一次次金融风险事件的背后无不揭示着我国金融体系的脆弱性,一次次危机的背后也都不同程度的存在银行系统性风险,银行体系与资本市场和社会经济联系最为紧密,因此对银行系统性风险的测度方法和传导效应研究意义重大。本文首先对系统性风险管理理论发展历程和最新进展进行研究,重点探讨了风险管理主流工具风险价值VaR模型及其衍生出来的CoVaR模型,之后选用更新、更全面的风险度量工具——CoVaR模型对我国商业银行系统性风险及其溢出效应进行研究,以我国16个主要上市银行和申万二级银行指数作为样本,运用分位数回归技术分别构建了商业银行与系统间的静态CoVaR模型和动态CoVaR模型,对商业银行系统性风险及其溢出效应进行综合分析。基于静态CoVaR分析银行风险时,测算了各银行自身风险及其与银行业整体之间的双向风险溢出效应,并应用聚类分析方法,从风险数据的角度对银行进行分类研究。结果表明单一的运用VaR模型可能会导致银行业整体的风险水平被低估,CoVaR方法在风险价值的基础上综合考虑风险的溢出效应,是一种更为全面的风险管理工具。从测算结果来看,各银行的无条件风险与其对银行整体的风险溢出并没有明显的相关关系,我国大部分银行的风险水平高于银行整体,大型国有商业银行自身风险和对系统的溢出效应相对较小,大多数股份制银行波动较大,对系统风险溢出较高。银行风险与其受到银行系统的溢出有一定的正相关关系,即银行的自身风险越高也越容易受到银行业系统风险的影响。基于动态CoVaR分析银行风险时,借助资产定价模型的原理,引入了更加符合我国金融市场特征的宏观变量,构建了比较有效的动态CoVaR模型。通过测算结果发现,国有银行自身风险比较低,表现相对稳定,但一旦陷入危机对将对银行板块形成较强的风险溢出效应。股份制银行自身风险比较高,对系统的风险溢出效应在中等水平。一般情况下,城市商业银行的风险价值中等,但系统陷入危机时风险上升最快,容易受到系统的影响,对系统的风险溢出效应比股份制银行大。最后,根据理论研究和实证分析的结果,分别对降低银行自身风险和加强银行系统性风险监管提出了建议。
[Abstract]:In recent years, the development of China's financial market has experienced ups and downs, with a number of risk events one after another, the "money shortage" in 2013, the "debt disaster", and the stock market disasters in mid-2015 and early 2016. Behind this financial risk event, the fragility of China's financial system is revealed, and there are systemic risks of banks to varying degrees behind the crisis, and the banking system is most closely related to the capital market and social economy. Therefore, it is of great significance to study the measurement method and conduction effect of bank systemic risk. In this paper, the development course and latest progress of systemic risk management theory are studied, and the risk value VaR model of the mainstream tool of risk management and its derived CoVaR model are discussed in detail, and then the update is selected. The CoVaR model, a more comprehensive risk measurement tool, studies the systemic risk and spillover effects of commercial banks in China, and takes the index of 16 major listed banks and Shenwan secondary banks as samples. The static CoVaR model and dynamic CoVaR model between commercial bank and system are constructed by using quantile regression technique, and the systemic risk and spillover effect of commercial bank are comprehensively analyzed. When analyzing the bank risk based on static CoVaR, this paper calculates the risk of each bank and its two-way risk spillover effect with the banking industry as a whole, and applies the cluster analysis method to classify the bank from the point of view of risk data. The results show that the single use of VaR model may lead to the underestimation of the overall risk level of the banking industry. CoVaR method is a more comprehensive risk management tool, which considers the spillover effect of risk comprehensively on the basis of risk value. From the measured results, there is no obvious correlation between the unconditional risk of each bank and its risk spillover to the bank as a whole. The risk level of most banks in our country is higher than that of the bank as a whole. The risk of large state-owned commercial banks and the spillover effect to the system are relatively small, most of the joint-stock banks fluctuate greatly, and the spillover to the system risk is higher. There is a positive correlation between bank risk and the spillover of the banking system, that is, the higher the risk of the bank itself, the more vulnerable it is to the risk of the banking system. Based on the dynamic CoVaR analysis of bank risk, with the help of the principle of asset pricing model, the macro variables which are more in line with the characteristics of China's financial market are introduced, and a more effective dynamic CoVaR model is constructed. Through the calculation results, it is found that the risk of state-owned banks is relatively low and relatively stable, but once they fall into the crisis, they will have a strong risk spillover effect on the banking sector. The risk of joint-stock banks is relatively high, and the risk spillover effect on the system is at the medium level. In general, the risk value of city commercial banks is medium, but when the system falls into crisis, the risk rises the fastest and is vulnerable to the influence of the system, and the risk spillover effect on the system is greater than that of joint-stock banks. Finally, according to the results of theoretical research and empirical analysis, some suggestions are put forward to reduce the risk of banks and strengthen the supervision of systemic risk of banks.
【学位授予单位】：南京大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F224;F832.33
，
本文编号：2477934
[Abstract]:In recent years, the development of China's financial market has experienced ups and downs, with a number of risk events one after another, the "money shortage" in 2013, the "debt disaster", and the stock market disasters in mid-2015 and early 2016. Behind this financial risk event, the fragility of China's financial system is revealed, and there are systemic risks of banks to varying degrees behind the crisis, and the banking system is most closely related to the capital market and social economy. Therefore, it is of great significance to study the measurement method and conduction effect of bank systemic risk. In this paper, the development course and latest progress of systemic risk management theory are studied, and the risk value VaR model of the mainstream tool of risk management and its derived CoVaR model are discussed in detail, and then the update is selected. The CoVaR model, a more comprehensive risk measurement tool, studies the systemic risk and spillover effects of commercial banks in China, and takes the index of 16 major listed banks and Shenwan secondary banks as samples. The static CoVaR model and dynamic CoVaR model between commercial bank and system are constructed by using quantile regression technique, and the systemic risk and spillover effect of commercial bank are comprehensively analyzed. When analyzing the bank risk based on static CoVaR, this paper calculates the risk of each bank and its two-way risk spillover effect with the banking industry as a whole, and applies the cluster analysis method to classify the bank from the point of view of risk data. The results show that the single use of VaR model may lead to the underestimation of the overall risk level of the banking industry. CoVaR method is a more comprehensive risk management tool, which considers the spillover effect of risk comprehensively on the basis of risk value. From the measured results, there is no obvious correlation between the unconditional risk of each bank and its risk spillover to the bank as a whole. The risk level of most banks in our country is higher than that of the bank as a whole. The risk of large state-owned commercial banks and the spillover effect to the system are relatively small, most of the joint-stock banks fluctuate greatly, and the spillover to the system risk is higher. There is a positive correlation between bank risk and the spillover of the banking system, that is, the higher the risk of the bank itself, the more vulnerable it is to the risk of the banking system. Based on the dynamic CoVaR analysis of bank risk, with the help of the principle of asset pricing model, the macro variables which are more in line with the characteristics of China's financial market are introduced, and a more effective dynamic CoVaR model is constructed. Through the calculation results, it is found that the risk of state-owned banks is relatively low and relatively stable, but once they fall into the crisis, they will have a strong risk spillover effect on the banking sector. The risk of joint-stock banks is relatively high, and the risk spillover effect on the system is at the medium level. In general, the risk value of city commercial banks is medium, but when the system falls into crisis, the risk rises the fastest and is vulnerable to the influence of the system, and the risk spillover effect on the system is greater than that of joint-stock banks. Finally, according to the results of theoretical research and empirical analysis, some suggestions are put forward to reduce the risk of banks and strengthen the supervision of systemic risk of banks.
【学位授予单位】：南京大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F224;F832.33
，
本文编号：2477934
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