基于KMV模型的商业银行信用风险测算研究

发布时间：2018-06-06 12:11

本文选题：KMV模型 + COPULA函数　；参考：《北京邮电大学》2013年博士论文

【摘要】：信用风险由交易对手违约所造成的既有损失,是金融市场中最古老、最重要的风险形式之一,也是中国现代商业银行面临的主要风险。通常上认为,贷款是其最主要、最明显的风险来源。实际上,它却广泛的存在于银行的所有业务之中,包括交易账户、表内外业务等。随着金融市场的不断发展,在创新、利用金融衍生工具进行避险的同时,也会引发商业银行的信用风险,如承兑、金融期货、债券、承诺和担保等。作为商业银行经营活动中最主要的风险之一,信用风险直接影响着现代社会经济生活的各个方面,也影响着一个国家的宏观经济决策和经济发展,甚至影响到整个全球经济的稳定与协调发展。商业银行作为信用风险的承载体,其信用风险管理体系的完善与否直接关系到商业银行的经营能否成功。中国大型商业银行于2010年底开始实施新巴塞尔资本协议。作为巴塞尔委员会的成员之一,严格执行新巴塞尔协议,有助于提高抵御金融危机的能力,也是中国银行业融入金融全球化,参与国际竞争的必然要求。在巴塞尔新资本协议逐步全球化实施的今天,信用风险管理作为银行业自身管理的重要组成部分,将成为中国银行业资本管理中的重中之重。本论文的研究工作主要是基于KMV模型在商业银行信用风险管理中的测算研究完成的。本文在分析KMV模型的基本思想、理论架构、模型计量步骤的基础上,讨论KMV模型的在实际应用中的测算情况以及研究KMV模型在中国的适用性,并利用KMV模型定量分析的研究方法,对上市公司ST公司和非ST公司的违约率进行测算,同时结合Copula函数讨论联合违约概率,找出了较为符合中国国情的结合了Copula函数的KMV模型,最后,对KMV模型在中国银行业中的风险测算和应用提出改进措施。本文相关研究成果主要概括为三点：第一,本文以KMV模型作为切入点,从对KMV模型的理论基础、参数设计、计算方法等基本点着手进行了详尽的讨论,把KMV模型从纷繁复杂的理论框架中梳理出来,讨论KMV模型在测度中国商业银行信用风险时的实际测算过程,与过程中的局限性和改进方法,形成了较为规范、具体和实用性的研究成果,为中国商业银行提高现有的风险管理水平,逐步引入国际上先进的风险管理方法提供了具有实际意义的参考。第二,由于组合信用风险的”厚尾”特征,为了提高商业银行中组合信用风险测算的准确率,本文构建了结合Copula函数的KMV模型。针对KMV模型的不足,将不同的Copula函数与KMV模型相结合,并采用”平方欧式距离”的方法进行模型评价。第三,利用中国上市公司ST公司与非ST公司的相关数据进行测算,说明KMV模型能够较好的测度我国上市公司的信用风险状况。针对KMV模型自身的局限性,利用中国资本市场上市公司相关数据,通过结合了copula函数后改进了的KMV模型测算联合违约概率,并通过“距离法”评价模型,找出最符合实际情况的改进后的KMV模型,使KMV模型更适用于测算中国商业银行组合信用风险。
[Abstract]:It is one of the oldest and most important forms of risk in the financial market. It is also the main risk faced by modern commercial banks in China. Generally speaking, loan is the most important and most obvious source of risk. In fact, it exists widely in all the business of the bank. With the continuous development of the financial market, the credit risks of commercial banks, such as acceptance, financial futures, bonds, commitments and guarantees, are also caused by the continuous development of financial markets and the use of financial derivatives to avoid risks, such as acceptance, financial futures, bonds, commitments and guarantees. As one of the most important risks in commercial banks' business activities, credit risk affects directly All aspects of the modern social and economic life also affect the macroeconomic decision-making and economic development of a country, and even the stability and coordinated development of the whole global economy. As the carrier of credit risk, the perfection of the credit risk management system of commercial banks is directly related to the success of commercial banks' operation.
China's large commercial banks began to implement the new Basel capital agreement at the end of 2010. As one of the members of the Basel Committee, the strict implementation of the new Basel agreement will help to improve the ability to resist the financial crisis. It is also the inevitable requirement for China's banking industry to integrate into the financial globalization and participate in international competition. In Basel new capital agreement gradually Today, with the implementation of globalization, credit risk management, as an important part of the banking industry's own management, will become the top priority in the capital management of China's banking industry.
The research work of this paper is based on the calculation of the KMV model in the credit risk management of commercial banks. Based on the analysis of the basic ideas, the theoretical framework and the steps of the model measurement of the KMV model, this paper discusses the calculation of the KMV model in the practical application and the applicability of the KMV model in China, and uses KMV The method of model quantitative analysis is used to calculate the default rate of ST and non ST companies in listed companies, and to discuss the joint default probability combined with Copula function, and find out the KMV model which is in line with the national conditions of China and combine the Copula function. Finally, the improvement measures are put forward to the risk calculation and application of the KMV model in the Chinese banking industry. The relevant research results of this paper are summarized as three points.
First, this paper takes the KMV model as a breakthrough point, discusses the basic points of the theoretical basis, parameter design and calculation method of the KMV model, and combs the KMV model from the complicated and complicated theoretical framework, and discusses the actual calculation process of the KMV model in measuring the credit risk of the commercial bank of China, and the limitation in the process. It has formed a more standardized, specific and practical research result, which provides a practical reference for Chinese commercial banks to improve the existing risk management level and gradually introduce advanced international risk management methods.
Second, due to the "thick tail" feature of combined credit risk, in order to improve the accuracy of the combined credit risk calculation in commercial banks, this paper constructs a KMV model combining the Copula function. Aiming at the shortage of the KMV model, the different Copula functions are combined with the KMV model, and the model is evaluated with the "square Euclidean distance" method.
Third, using the related data of ST company of Chinese listed company and non ST company, it shows that the KMV model can measure the credit risk status of the listed companies in China better. According to the limitations of the KMV model itself, it uses the related data of the listed companies in China capital market, and calculates the improved KMV model by combining the copula function. The joint default probability is combined with the "distance method" evaluation model to find the improved KMV model which is most consistent with the actual situation, so that the KMV model is more suitable for the calculation of the combined credit risk of China's commercial banks.
【学位授予单位】：北京邮电大学
【学位级别】：博士
【学位授予年份】：2013
【分类号】：F224;F832.33

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