As the 2008 international financial crisis occurs,credit risk has been more and more concerned by the international community. But by economic globalization brings social development makes the traditional measurement and management ways and means of credit risk has been far not adapt to the current complex society's new situation and new problems .even more cannot satisfy people's needs on the listed company scientific quantitative measurement and effective management of credit risk. Through the reference and study developed capital market's advanced modern credit risk management techniques and methods, Establish a regional economic credit risk measurement model and method which suitable for China's national conditions is an important issue for credit risk management facing. So, the research of credit risk metric of listed companies in certain areas not only has theoretical significance, but also has a strong practical significance.Based on this, after several main foreign credit risk metric model are discussed and reviewed,the author chosed the KMV model which based on Black - Scholes - Merton option pricing theory as the research emphasis in this paper, this model is used more widely abroad and suitable for our country's practical situation,and used it to measure the credit risk of jiangxi province's listed companies . In the process of research the author also corrected the KMV model, and compared its result with the unmodified model's descriptive statistics results, and according to the result of KMV model select appropriate financial indicators did regression analysis and T distribution examination for the default distance (DD) ,the results show that the company asset scale, profitability, debt-repaying ability, growth ability and stock price stability all have influence on credit risk,and the most influential factor is company growth ability.Finally, through empirical research process and the results of the analysis, KMV model which puts the popularization and application in China presented related suggestions. |