The Empirical Research On Credit Risk Of China Manufacturing Listed Companies Based On KMV Model

In many financial risks, whether developed or developing, credit risk is undoubtedly the most attention from Basel’s revised three times is not difficult to see that. The stock market has always been a barometer of a country’s economy, said China’s stock market compared to other financial markets is relatively mature, all companies can in China’s stock market listing, the line has had some representation within, if these companies happen Credit risk its influence can be imagined, the study listed company’s credit risk is significant.Since China Shanghai and Shenzhen stock markets have been opened, as of the end of December 2014, the Shanghai stock market numbers and Shenzhen A-share listed companies almost more than 2500, of which there are more than 1,700 manufacturing. In this paper KMV model to China Listed Company’s credit risk empirical research. The thesis is divided into five chapters, Chapter 1 Introduction legend background and significance of the concept outlined credit risk, credit risk characteristics and causes; the second chapter of the credit risk measurement and management methods of elaboration; the third chapter Introduction KMV model theory and our researchers to make KMV model is more suitable for China’s actual situation what improvements. The fourth chapter is part of empirical analysis in this section, first redefine default based on the actual situation of China’s research. Second, choose the A-share market assets on a similar scale manufacturing and ST shares and non-ST stocks on paired samples were KMV model empirical analysis, in the calculation of volatility using Garch (1,1) model, because our data on default lack, so the use of empirical research on default from the credit risk analysis of 30 samples, and calculates the distance between the two default coefficients depending on long-term debt, and four steps for the analysis of the results, wherein the fourth step, the use of Fisher discrimination method and financial data from different perspectives and KMV model analyzes the credit risk of the sample. After a four-step analysis, it concluded that the KMV model can distinguish between ST and non ST group, which by default point paired T test described in this sample of 30 long-term debt 0.75 times better identified The distinction between default group, but equidistant from the group for breach found some interval default group and the normal group were distributed, it analyzes the possible causes of this phenomenon, including the ups and downs of the stock system, calculation principle models, etc., Fisher discrimination method with further validation; empirical analysis of Chapter Ⅳ, the fifth chapter presents some countermeasures application KMV model analysis of the listed companies when, as well as inadequate and subsequent research direction.