Research On The Early Warning Of Credit Risk In Chinese Listed Companies Based On UTADIS Method

China's economy is in a period of rapid development.Credit has an inestimable role in ensuring stable and rapid economic development.It can be said that economic development is also the development of credit.With the rapid development of the global economy,credit risks have become increasingly prominent and have had a huge impact on the economy,which has also had a great impact on our production and life.In particular,since the outbreak of the global financial crisis in 2008,the close connection of the world economy can be said to be the result of a full-fledged move.Once a listed company has a credit risk,the company will fall into a financial crisis and then spread to many related industries and related personnel.Interests may even cause other companies to face bankruptcy.Therefore,measuring and avoiding the credit risk of listed companies is particularly important for operators,investors,financial institutions,and government regulators.The establishment of a high-precision credit risk early warning model is an issue that needs to be urgently addressed.At present,many organizations have used software developed by financial mathematics tools to establish models for predicting credit risk of listed companies,including the KMV model proposed by KMV,neural network model,Logistic regression model,MHDIS model proposed by Greek scholars,and CDS spreads.Models and so on.Compared with Western countries,China's credit risk management is still not mature enough,and there are some deficiencies.This article uses the UTADIS model proposed by Jacquet-Lagrèze on the basis of many scholars' research to predict the credit risk of listed companies in China.UTADIS(UTilites Additives DIScriminantes)multi-objective decision-making method is an effective method to classify listed companies into different categories based on some indicator data.It is a method based on the preference solution set to evaluate a set of utility equations and uses the linear programming method,which can reduce errors when classifying the categories.The UTADIS method does not impose special requirements on multicollinearity and heteroskedasticity.This method can be based on the listed company's financial data over the past few years to assess whether the company's credit risk exists now or in the future,and can be a rough assessment of a company's future development.Based on this method,this paper will use utility function theory and linear programming theory to list listed companies into ST and non-ST categories according to the financial data of listed companies.ST is based onabnormalities in the financial status of the company's securities market.The company's stock is “special Dealing with the company.When Xie Chunyan did credit risk research,he considered that the “abnormal financial situation” was specially dealt with was in line with our unhealthy judgment on the financial status of the company and was a reasonable criterion for conducting credit risk research.For the availability,authenticity,and validity of data,this paper selects 44 listed companies from China's central enterprises as research samples,and selects two years of financial data for research.The results show that the UTADIS method can effectively identify the existence of credit risk of listed companies,which can help managers make the right management decisions,to help investors make a reasonable investment,reduce investment risks and improve supervision efficiency of regulatory authorities.