The Study Of China’s Listed Company’s Credit Risk Early Warning

With the continuous expansion of global credit, the problem of the credit riskexposed more and more serious, had become one of the main risks which the financialindustry needed to face. The essence of market economy is the credit economy, listedcompany as the main body of market economy, especially its credit status had valued bypeople. Credit risk early warning was the inevitable outcome of the development marketeconomy to a certain stage, it had created an enormous role in market economy as asocial supervision method of credit risk prevention, and its importance and promotingeffect has been proved by theory research and practice of developed countries. AsChina’s stock market boomed and the listed companies increased, credit problem hasbecome even more apparent. So the credit risk study of China’s listed companies has theimportant practical significance for financial market stability and healthy development.This paper is divided into six parts to make a theoretical analysis and empiricalresearch for our country’s credit risk warning. The1st part describes the background andsignificance of this study, and reviews the research situation at home and abroad. The2nd part introduces the concept of credit risk, the theoretical basis for credit risk earlywarning, the traditional methods and the modern models of credit risk early warning,and the modern models is evaluated. The3rd part elaborates theoretical foundation andcomputational framework of KMV based on the standard European options theorywhich this paper adopts. The4th part makes validity analysis use the data of ourcountry’s coal companies for the application of KMV model. This paper uses the34coallisted companies, evaluates this34ST/*ST and non-ST company’s credit risk by usingKMV model, and tests the ability of model recognition to credit risk of listed companies,the results show that the model can more accurately measure the credit risk of listedcompanies. The5th part analyzes influence factors of distance to default, and makes alinear regression analysis for the influence factors, this paper adds a social responsibilityindex at regression analysis. The6th part is the conclusion and outlook, proposes theinadequacies of this paper and the problem which need to solve at a later date.