The Empirical Research On The Credit Risk Identification Of Chinese Listed Companies

With the ever-expanding credit in the worldwide, the credit risk which many enterprises and financial institutions from all countries face is also increasing in the meantime. It will bring extremely serious consequences on economy. An unprecedented massive global financial crisis which suddenly broke out in America also triggered more interest in the research of credit risk. The fundamental reason of this crisis could be due to the fact that the banks lowered the standard for loan so that they can increase their business by developing clients whose credit rating is not very high. So it can be considered that the explosion of this crisis was induced by neglect of supervision of credit risk. In order to prevent this kind of events which brings heavy damages in economy, many relevant institutions are putting more efforts on researching the credit risk than before.With the world economy being increasingly open, the global competition becomes more intense and the corporation among different countries becomes much closer. Our country had accession to the WTO in2001which required that our banking industry should be free to other countries and specified the time when foreign banks can do their business in our market. Because of the low efficiency in management of domestic banks, they will definitely get some impact. Furthermore all banks have to specify and manage the daily operation following the rules of New Basel Capital Accord. When our banking industry is enduring the double pressure, they have to pay more attention to strengthen and improve credit risk management. In such a complicated international economic and financial situation, it is particularly important to deeply understand the most advanced techniques of measuring the credit risk and when applying those techniques it is very essential to analyze our objective economic situation. We can establish new and advanced credit risk measurement and management models by amending the original models in order to effectively predict risk because those newly established models can better simulate the economic environment in China.The KMV model which has been widely used is established with strong theoretical basis for the pricing of call options. All data for this model can be obtained from the stock market and when inputting all the data into the KMV model it will calculate a variable to measure the probability to default and this variable can be used as a reference to predict whether the listed companies will default in the future. It is a time-consuming and laborious process to establish the default database and our country did not pay enough attention to such issues. Under this background the KMV model has more advantages than other credit risk measurement models. However, the economic environment can not be static. If the economic cycle changes the credit risk will be affected. The KMV model includes only one variable called risk-free interest rate reflects macroeconomic changes. When the economic situation changes the credit risk of company will be different. Therefore the predictive ability of the KMV model would be doubted.The KMV model includes a critical variable named the default point. Although there has been much research in the aspect of DPT, there isn’t a perfect definition of DPT to describe the Chinese market. Based on the former study this paper amends the DPT and tests the ability to recognize the credit risk of listed companies in China. The correct setting of the default point can effectively resolve the potential dangers in the application of KMV model. In addition, due to a lack of database it makes difficult to calculate the expected default frequency through an ideal mapping. Therefore the distance to default can be used directly as an ideal indicator of the different credit risk.This paper randomly chooses10companies from those being specially treated the first time in2010in the Shanghai A-share market. Meanwhile it chooses10non-ST companies from the same market and industry. With Eviews6.0and Excel software for all data analysis, it applies the KMV model including a new DPT which can better explains Chinese default situation to calculate the DD in2008,2009and2010, it will be convenient to monitor the change of credit risk before the ST time. Because KMV model has an advantage in recognizing the credit risk two years before the ST time, it can be expected that distance to default of2008can distinguish between ST and non-ST companies, but the evidence shows a different result. However, in2009and2010, the KMV model shows its advantage gradually, it can explain that the KMV model including a new DPT which is based on Chinese market is able to identify the default risk.