The Application Of The KMV Modei For Default Risk Measurement Of The Listed Companies In China

Commercial banks not only play an important role in the financial industry, in a modern market economies also occupy the main position. The globalization of Finance and banking deregulation, making China's financial market environment had a more significant change. Commercial banks are facing more severe situation, the most important is the credit risk intensifies and bank losses on assets increase. So in the current economic situation, strengthen the credit risk management of commercial bank can improve commercial bank's efficiency, promote commercial bank and financial market development.The default risk of commercial bank is one of the most important risks. Especially with the international banking crisis, economic theory circle and practice circle pay more and more attention to the risk of default. Listed company as the commercial bank customers, its default risk for banks is more worthy of study. Prediction and control of Listed companies on the default risk is very important.Credit rating of the borrowing enterprises in Shanghai is intended to help commercial banks to control the risk of default. This project is organized and promoted by the people's Bank of China。After several amendments, the assessment system has become mature, and also received wide application within the bank. The assessment system has not been model test yet. This paper attempts to use KMV model, an extensive international adaptation of credit risk measurement model, to simulate the score results, in order to achieve the purpose of loan rating test reference.According to the characteristics of model which is based on data of stock market, author will combine the credit rating of people's Bank of China to China's listed companies in 2010 and the credit risk measurement method of KMV model. First, we choose 77 listed companies as analysis of sample, and calculate KMV model key variables (default distance,DD and expected default rate,EDF,) by the Matlab program, then get the distance to default grade interval and the credit rating result fitting by the SPSS software. The interval's accurately rate is up to 96.1%. So investors can judge default risk by the result of Credit rating of the borrowing enterprises.