A Measurement Of The Credit Risk Of Listed Companies In China

Credit risk is not only affecting the social and economic activities in various fields, but also affecting a country’s economic development and macro-economic policy-making. Subprime mortgage crisis which occurred in2007triggered a global financial crisis, causing the financial institutions’great concerned about credit risk management. A measure of credit risk experienced by simply qualitative analysis to linear and non-linear model based on financial indicators, and then the process of credit risk quantification models based on modern financial theory. Credit risk measurement models widely used in developed countries are KMV, Credit Risk+, the Credit Metrics and Credit Portfolio View. However, the measurement about credit risk of listed company in domestic is multiple linear discriminate models represented by Z-score model, which is far behind the developed countries. This is urgent to learn from the international advanced measurement techniques. This paper will to measure the credit risk of listed companies in China,with the combination of KMV model and Logit model.KMV model is a method of calculating the expected default model, whose theoretical basis of the model is the Black-Scholes-Merton option pricing model. KMV model regard the equity of company as European call option, the value of the assets of the company as the underlying assets, a level of debt as the execution price, debt maturity as the option exercise date. This level of debt is defined as the default point. If the value of the assets of the company is higher than the point of default at maturity, the company repays its debt, and the equity value of the shareholders of the company is the difference between the value of the assets and the value of the debt; If the value of the company’s assets is less than the default point, the company is unable to repay the debt, which will choose to default, then the creditors get all the assets of the company, leaving nothing for the shareholders. Distance to default is the measurement the relative distance between the expected value of the assets of the company and the default point. The greater the distance to default, the smaller the probability of default of the company. Based on the large database of KMV Company, KMV model establish the corresponding relationship between the distance to default and the historical probability of default, and accordingly draw the expected default.This paper analyses the application environmental in China of KMV model. Considering the validity and accessibility of the data, KMV model is applicable to China. Meanwhile, there are difficulties for KMV applying to China:Shares of listed company did not achieve full circulation in the stock market, which will affect the calculation of the value of its equity; there is few listed company which go bankruptcy in China’s, making the selection of the credit crisis difficult; China has yet to establish a sound credit system and lack of historical default data of listed company, then we can not get the final results of KMV model-expected default frequency (EDF). Taking into account this difficulty, we use the method of combining KMV modeland Logit model, taking the intermediate results of the KMV model, distance to default (DD), as one of the independent variables of traditional Logit model, in order to mesure the credit risk of listed companies in China.This paper selects the listed companies which were special treatment from2009to2011for abnormal financial condition as the credit crisis companies, and selects the listed companies which were not special treatment as credit normal company. Then select samples of2009as modeling samples, samples of2010and2011as test samples.Empirical steps are as follows:Firstly, set specific parameters of the KMV model in consideration of the specific situation of China, then calculate the distance to default (DD); secondly, introducing the distance to default to the traditional Logit model which based on the financial data of listed companies, build new Logit model. In order to determine the applicability of KMV model in China, compare the effectiveness of the two models from the goodness of fit of the model, discriminate accuracy, and predictive accuracy. Based on the t-1, t-2, t-3-year data of the listed company, this paper also explores the timeliness of the model-how long the model can predict the credit crisis of listed companies in advance.Finally, this paper concluded that-compared to traditional Logit model, the model introducing the distance to default is more effective to measure the credit risk of listed companies in China. Based on the t-2-year data of the listed company, the model introducing the distance to default can predict one year ahead of the credit crisis of listed companies.