基于CCA模型的我国商业银行系统性风险度量研究

发布时间：2018-03-04 04:08

本文选题：商业银行　切入点：系统性风险　出处：《山西财经大学》2017年硕士论文　论文类型：学位论文

【摘要】：自从2006年11月,中国金融系统全面对外开放,中国金融业开始进入机遇与风险并存的经济环境,银行业作为金融业的中流砥柱,面临新的挑战,不仅如此,由于美国次级房贷危机引发的金融风暴使全球经济陷入了新一轮的金融危机,作为我国金融行业的重要组成部分,商业银行难逃此次危机,这给我国商业银行带来不小的压力。由于系统性风险在此次金融危机中扮演的重要角色,有关系统性风险的研究便成为国内外学者研究的热门课题。本文就我国商业银行系统性风险的度量问题展开研究,在介绍系统性风险的概念和影响因素的基础上,对我国商业银行系统性风险进行了定量分析,以期本文能够为继续研究商业银行针对系统性风险逆周期监管的学者提供一定的思路、建议。本文主要采用或有权益分析法,将我国整个银行体系中的所有2010年以前上市的银行作为一个整体单位来研究,得到违约概率和违约距离等风险指标,并结合这些指标探讨2007年第一季度至2016年第一季度我国商业银行的系统性风险发展水平,最后结合前期的度量研究对我国商业银行防御系统性风险提供建议。通过本文的量化研究,可以得到想要抵御系统性风险,违约距离应该维持在什么水平;违约概率为0.03时,说明有较大经济危机,会产生系统性风险,对于我国商业银行来说,应将违约概率控制在0.01以内;预期损失净现值反映商业银行可以预计到的风险损失值,通过本文分析可知,往往在风险过后,商业银行才增加预期损失净现值,有悖于逆周期监管的核心宗旨;目前我国政府针对我国经济的根本问题,采取了一系列措施,有助于我国整体金融的健康稳定发展,一定程度上从根本上缓解了我国商业银行所面临的系统性风险问题。本文的创新之处在于,首次利用CCA模型对能代表我国商业银行整体水平的所有2010年以前上市的商业银行作为一个部门所面临的系统性风险进行量化分析,突破以往仅对单个银行的系统性风险进行计量研究的局面;数据的处理上,对于前期未上市银行股权市场价值不可得的情况,暂时选用账面价值代替;本文采用MATLAB对CCA模型进行编程,在编程过程中,借鉴了KMV模型的编程模式,用该程序可以直接利用股权市场价值及其波动率和负债账面价值算出资产市场价值及其波动率,进而得到违约距离、违约概率、预期损失净现值等可以直接衡量风险的指标。
[Abstract]:Since November 2006, when China's financial system was fully opened to the outside world, China's financial industry has begun to enter an economic environment in which opportunities and risks coexist. As the mainstay of the financial industry, the banking industry is facing new challenges, not only that. As a result of the financial turmoil caused by the subprime mortgage crisis in the United States, the global economy has fallen into a new round of financial crisis. As an important part of our financial industry, commercial banks cannot escape the crisis. This has put a lot of pressure on commercial banks in China. Because of the important role that systemic risk plays in the financial crisis, The research on systemic risk has become a hot topic for scholars at home and abroad. This paper studies the measurement of systemic risk of commercial banks in China, based on the introduction of the concept of systemic risk and its influencing factors. The quantitative analysis of the systemic risk of commercial banks in China is carried out in the hope that this paper can provide some ideas for the scholars who continue to study the countercyclical supervision of systemic risks in commercial banks. All the banks listed before 2010 in the whole banking system of our country are studied as a whole unit, and the risk indicators such as default probability and default distance are obtained. Combined with these indicators, this paper discusses the development level of systemic risk of commercial banks in China from in the first quarter of 2007 to in the first quarter of 2016. Finally, combined with the previous measurement research, it provides suggestions for commercial banks to defend against systemic risk. Through the quantitative research in this paper, we can find out what level the distance of default should be maintained in order to resist systemic risk; when the probability of default is 0.03, It shows that there is a large economic crisis, there will be systemic risk, for our commercial banks, the probability of default should be controlled within 0.01; the NPV of expected losses reflects the expected risk loss value of commercial banks, through the analysis of this paper, we can know, Often after the risk, commercial banks increase the net present value of expected losses, which is contrary to the core purpose of counter-cyclical supervision. At present, our government has taken a series of measures to address the fundamental problems of our economy. It is helpful to the healthy and stable development of the whole finance of our country, and to some extent alleviates the systemic risk problem faced by the commercial banks of our country. The innovation of this paper lies in:. For the first time, the CCA model is used to quantify the systemic risks faced by all commercial banks listed before 2010, which represent the overall level of commercial banks in China. To break through the situation that the systematic risk of a single bank was only studied in the past, and to deal with the data, the unlisted bank stock market value was temporarily replaced by book value. In this paper, MATLAB is used to program the CCA model. In the process of programming, the programming mode of KMV model is used to calculate the market value of assets and its volatility directly by using the stock market value and its volatility and the book value of liabilities. Then, the distance of default, the probability of default, the net present value of expected loss and so on can be obtained to measure the risk directly.
【学位授予单位】：山西财经大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F832.33

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