Research On Credit Risk Measurement Of Listed SMEs Based On KMV Model

Credit risk management is the eternal topic of financial markets, riskmanagement, in the trend of financial globalization, which is the major challengesfacing China’s financial market. At present, China’s credit risk management conceptsand technologies are not advanced. In particular, quantitative models of credit risk arein its infancy. China’s market economy is undergoing rapid development, ourgovernment has introduced policies to vigorously support the development of smalland medium-sized enterprises, Although small and medium-sized listed companies tostrive constantly to develop and grow, but the financing difficulties of SMEs is stillbecoming increasingly prominent. Therefore, to enhance the level of riskmeasurement becomes increasingly important. We should study and learn theadvanced international Credit Risk management techniques to enhance the level ofcredit risk measurement of small and medium-sized listed companies in China.On the basis of learning from international advanced small and medium-sizedlisted companies credit risk quantitative management technology and accessing tolarge amounts of literature, KMV model that widely used in foreign countries isselected to do empirical analysis combined with China’s actual situation in this paper.We can enhance its applicability in the Chinese market By the model correction。Firstly, this paper describes the basic principles and backgrounds of the original KMVmodel and analysis its applicability in the special market. Secondly, KMV model isfixed according to the characteristics of our company and the financial markets.Taking into account the characteristics of high growth in small and medium-sizedlisted companies, this paper introduces asset value growth rate parameters.ten different default parameters is set because the traditional breach point set does notnecessarily apply to our situation. Through the empirical analysis we can get theoptimal default point for small and medium-sized listed companies inChina.Thirdly,12ST or*ST small and medium-sized listed companies are selected asthe default sample.12normal small and medium-sized listed companies as thenon-default sample. By the identification of ROC curve the optimal default point forour situation is in the total liabilities, which is consistent with the current actualsituation in China. By the proof of the empirical analysis, the model has become moreeffective.Finally, this paper summarizes the conclusions, limitations and the futureresearch direction. Finally, this paper gives some feasible recommendations on howto improve the applicability of the KMV model in China. We can study the modeltheory and improve the model parameters through practice.In addition, theestablishment of large databases is very important, which can provide quality data tosupport the application of KMV Credit Risk Measurement Models and all the workwe have done is to make the KMV model in credit risk management in small andmedium-sized listed companies in China become more effective.