基于CPV模型和压力测试的我国商业银行信用风险研究
发布时间：2018-08-29 10:55
【摘要】：2007年美国次贷危机爆发，演变成一场席卷全球的金融海啸，究其原因，是美国某些银行信用风险管理不善。当前欧债危机愈演愈烈，欧洲银行业信用风险不断攀升，全球银行业亦是如此。传统的信用风险管理模型已不再能够完全适应经济金融环境以及银行业发展的需要，全面且有效的商业银行信用风险管理模式、方法、技术是目前所有国家及全世界银行业都非常关注的课题。借鉴发达国家的风险技术与方法、吸取其他国家在金融危机中的经验教训，结合我国的实际国情，对我国商业银行信用风险度量技术和管理方法进行深入研究，不仅具有相当的理论价值，还有着极大的现实意义。 本文首先介绍了该研究的选题背景及意义，国内外研究成果评述，研究方法及结构安排，本文的创新点。其次，对商业银行信用风险进行了概述，介绍了信用风险的基本内涵，我国商业银行信用风险现状，压力测试的基本知识以及我国商业银行信用风险压力测试的可行性。指出目前我国商业银行存在不良贷款额度过高、房地产信贷风险加大、风险评估体系不健全等方面的问题。再次，介绍了信用风险度量模型，简述了传统信用风险度量方法，详述了CPV、KMV、CreditRisk+、CreditMetrics四种现代信用风险度量模型的比较，揭示了CPV模型应用在本研究的优势和对我国国情的适用性。随后，在基于CPV模型和压力测试的实证分析中，介绍了CPV模型的基本原理，基于CPV模型应用2003年4季度至2012年2季度的经过CPI指数调整、季节调整、指标筛选的CPI、GDP、固定资产投资、城市人均季度总收入4个解释变量对我国商业银行不良贷款率代表的违约率进行了回归分析，得出了不良贷款率和宏观经济变动的关系，，并进行了假定情景下的压力测试。实证结果表明CPI、GDP、固定资产投资、居民人均收入4个解释变量经过CPI指数调整和季节调整后，能够对根据不良贷款率转换的宏观经济指数Y进行很好的解释，拟合优度超过95%，进一步说明了CPV模型在我国商业银行信用风险度量研究中的有效性和适用性。其中CPI、GDP、固定资产投资3个指标对不良贷款的影响较大。违约率与CPI成正向变动关系，GDP和固定资产投资与不良贷款率呈反向变动关系，符合客观经济情况。模型建立了以不良贷款率为代表的商业银行信用风险和宏观经济状况的关系，符合人们对宏观经济形势会影响信贷风险的认识，能够为监管部门和银行信用风险管理部门提供一定的决策参考，具有一定的现实意义。 在此基础之上，提出了我国商业银行信用风险管理的若干意见，包括培育先进的信贷文化、建立健全的内部控制系统、建立健全的信用风险量化制度体系、加快数据库建立步伐、完善不良贷款处理机制、加大IT支持与人才培养方面的投入等方面。
[Abstract]:The subprime mortgage crisis broke out in 2007, which turned into a global financial tsunami. The reason is the poor credit risk management of some American banks. The European debt crisis is intensifying and the credit risk of European banks is rising, as is the global banking sector. The traditional credit risk management model can no longer fully meet the needs of the economic and financial environment and the development of the banking industry, comprehensive and effective commercial bank credit risk management model, method, Technology is a subject of great concern to banks in all countries and around the world. Drawing lessons from the risk techniques and methods of developed countries, drawing lessons from other countries in the financial crisis and combining the actual conditions of our country, the paper makes a deep study on the credit risk measurement techniques and management methods of Chinese commercial banks. It not only has considerable theoretical value, but also has great practical significance. Firstly, this paper introduces the background and significance of the research, the review of domestic and foreign research results, the research methods and structure arrangement, and the innovation of this paper. Secondly, it summarizes the credit risk of commercial banks, introduces the basic connotation of credit risk, the present situation of credit risk of commercial banks in China, the basic knowledge of stress testing and the feasibility of credit risk stress test of commercial banks in China. It is pointed out that the commercial banks in our country have some problems, such as the excessive amount of non-performing loans, the increase of real estate credit risk and the unsound risk assessment system. Thirdly, the credit risk measurement model is introduced, the traditional credit risk measurement method is briefly introduced, the comparison of four modern credit risk measurement models based on CPV,KMV,CreditRisk CreditMetrics is given in detail, and the advantages of the CPV model applied in this study and its applicability to the situation of our country are revealed. Then, in the empirical analysis based on CPV model and stress test, the basic principle of CPV model is introduced. Based on CPV model, the CPI index adjustment and seasonal adjustment are applied to the period from the fourth quarter of 2003 to the second quarter of 2012. The four explanatory variables of CPI,GDP, fixed asset investment and urban per quarter gross income selected by the index are regression analysis of the default rate represented by the non-performing loan rate of commercial banks in China, and the relationship between the non-performing loan ratio and the macroeconomic changes is obtained. The stress test was carried out under the hypothetical scenario. The empirical results show that the four explanatory variables of fixed asset investment and per capita income of CPI,GDP, can explain the macroeconomic index Y which is converted according to the non-performing loan ratio after the adjustment of CPI index and seasonal adjustment. The goodness of fit is more than 95, which further illustrates the validity and applicability of CPV model in the study of credit risk measurement of commercial banks in China. Among them, the CPI,GDP, fixed assets investment three indexes to the bad loan influence is bigger. The relationship between default rate and CPI is positive. The relationship between fixed asset investment and non-performing loan ratio is reversed, which is in line with the objective economic situation. The model establishes the relationship between the credit risk and the macroeconomic situation of commercial banks, which is represented by the non-performing loan ratio, and accords with the understanding that the macroeconomic situation will affect the credit risk. It can provide some decision-making reference for supervision department and bank credit risk management department, which has certain practical significance. On this basis, some suggestions on credit risk management of Chinese commercial banks are put forward, including cultivating advanced credit culture, establishing a sound internal control system, and establishing a sound credit risk quantification system. Speed up the establishment of the database, improve the processing mechanism of non-performing loans, and increase the input of IT support and personnel training.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F832.33
本文编号：2210988
[Abstract]:The subprime mortgage crisis broke out in 2007, which turned into a global financial tsunami. The reason is the poor credit risk management of some American banks. The European debt crisis is intensifying and the credit risk of European banks is rising, as is the global banking sector. The traditional credit risk management model can no longer fully meet the needs of the economic and financial environment and the development of the banking industry, comprehensive and effective commercial bank credit risk management model, method, Technology is a subject of great concern to banks in all countries and around the world. Drawing lessons from the risk techniques and methods of developed countries, drawing lessons from other countries in the financial crisis and combining the actual conditions of our country, the paper makes a deep study on the credit risk measurement techniques and management methods of Chinese commercial banks. It not only has considerable theoretical value, but also has great practical significance. Firstly, this paper introduces the background and significance of the research, the review of domestic and foreign research results, the research methods and structure arrangement, and the innovation of this paper. Secondly, it summarizes the credit risk of commercial banks, introduces the basic connotation of credit risk, the present situation of credit risk of commercial banks in China, the basic knowledge of stress testing and the feasibility of credit risk stress test of commercial banks in China. It is pointed out that the commercial banks in our country have some problems, such as the excessive amount of non-performing loans, the increase of real estate credit risk and the unsound risk assessment system. Thirdly, the credit risk measurement model is introduced, the traditional credit risk measurement method is briefly introduced, the comparison of four modern credit risk measurement models based on CPV,KMV,CreditRisk CreditMetrics is given in detail, and the advantages of the CPV model applied in this study and its applicability to the situation of our country are revealed. Then, in the empirical analysis based on CPV model and stress test, the basic principle of CPV model is introduced. Based on CPV model, the CPI index adjustment and seasonal adjustment are applied to the period from the fourth quarter of 2003 to the second quarter of 2012. The four explanatory variables of CPI,GDP, fixed asset investment and urban per quarter gross income selected by the index are regression analysis of the default rate represented by the non-performing loan rate of commercial banks in China, and the relationship between the non-performing loan ratio and the macroeconomic changes is obtained. The stress test was carried out under the hypothetical scenario. The empirical results show that the four explanatory variables of fixed asset investment and per capita income of CPI,GDP, can explain the macroeconomic index Y which is converted according to the non-performing loan ratio after the adjustment of CPI index and seasonal adjustment. The goodness of fit is more than 95, which further illustrates the validity and applicability of CPV model in the study of credit risk measurement of commercial banks in China. Among them, the CPI,GDP, fixed assets investment three indexes to the bad loan influence is bigger. The relationship between default rate and CPI is positive. The relationship between fixed asset investment and non-performing loan ratio is reversed, which is in line with the objective economic situation. The model establishes the relationship between the credit risk and the macroeconomic situation of commercial banks, which is represented by the non-performing loan ratio, and accords with the understanding that the macroeconomic situation will affect the credit risk. It can provide some decision-making reference for supervision department and bank credit risk management department, which has certain practical significance. On this basis, some suggestions on credit risk management of Chinese commercial banks are put forward, including cultivating advanced credit culture, establishing a sound internal control system, and establishing a sound credit risk quantification system. Speed up the establishment of the database, improve the processing mechanism of non-performing loans, and increase the input of IT support and personnel training.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F832.33
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本文编号：2210988
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