Credit Risk Measurement Of Listed Companies Based On KMV Model

Finance is the core of modern economy.The high risk characteristic of Finance makes a safety and steady financial system plays a vital role in a stability and development global economic. Financial institutions, especially Banks faced many different kinds of risks in its operating process, including credit risk, market risk, operation risk and liquidity risk, etc. Credit risk is one of the most important type of risk. From the time dimension, the credit risk is a kind of old risk. From the spatial dimension,credit risk not only affects every aspect of our social economic life,but also affected the stability and development of global economy. Now, with the further expansion of credit transactions, the credit risk problem become more prominent.We can see from the regional and global financial crisis happened in recent years that as countrie’s economic increasingly tied closely with each other, credit risk revealed a strong infectivity in different regions, different countries. The outbreak of credit risk problem in any country is likely to be transmitted to other tache, trigger a worldwide credit crisis. In addition, a series of new changes in Banks also makes the credit risk problem more severe. Increased competition led directly to spread income decreases and the introduction of the low-credit customers, thus increasing the the risk of hidden dangers, reduced Banks’ability to resist risks. All changes led to a higher request for bank’s credit risk management.For a long time, most research is concentrated in the areas of market risk. Due to the lack of credit data and hard to quantify, the research of credit risks were ignored by people.Howerver,subprime mortgage crisis happened in2008and interbank competition in recent years highlight credit risk problems again. Credit risk management is divided into three parts:risk measurement, risk management and risk control. We can see that effective management is established on the basis of accurate measurement of credit risk. Increasingly complex financial markets need us to learn more lessons from foreign advanced credit risk quantitative management tools. Based on the systematic introduction to foreign modern credit risk model, We picked the KMV model to do empirical analysis and used a series of data from the China stock market to verify the effectiveness of the model in our country.This article mainly divides into five chapters.In the first chapter we introduced the topic background, illustrates the research aim and research content of this article. The second chapter is the overview of credit risk and credit risk measurement method. The third chapter is the introduction of KMV model released by moody’s KMV company,this part is the focus of this article. We explain the model’s basic thoughts, assumptions,operating steps in details.Furthermore,we combined the existing research results to improve the model’s parameters.The fourth chapter is the empirical part of this article.We picked16loss companies in real estate industry as default group and16profit companies as non-default group in the same industry and similar asset size. The empirical results show that the default distance(DP) of default set of listed company are significantly greater than the non-default set,this conclusion accords with the actual situation of company’s credit situation. In chapter5we conclude from four aspects:model data source, parameter setting, using range and future model improvement to discribe the applicability of KMV model in our country. At lastwe put forward some suggestions.One of the innovation of this paper is introduced credit risk measurement methods in a new point of view. First of all, from the demand perspective,we suggests that financial market changes put forward higher requirement of credit risk measurement method. After that we explained from the perspective of supply that in order to satisfy the needs of the financial market, evolution of the process from the classical models (Expert analysis, Credit rating, Credit scores) to modern models(KMV model, CreditMetric model, Credit portfolio model and Credit Risk+model). The second innovation is model parameter estimation,we correct the parameters of the equity value in KMV model. The third innovation of this paper comes from the innovation of the sample grouping method. Due to lack of China’s corporate defaults sample data, we cannot use default and non default enterprises directly as the empirical sample, but only to find approximate to replace default enterprises and the default sample grouping method. This article doesn’t use common ST and non-ST companies to replace default enterprise and non-default enterprise, but chose profit as the distinguish standard, loss companies are set to the default group, profitable companies for the non-default group. The deficiency of this paper lies in that the sample data only select a single time period and a single industry, Other industries and more time periods will futher vertify the validity of the model. In addition,other parameters in the model are established on the basis of other scholar’s research,so we don’t confirm the accuracy.