The Status Quo Of Credit Debt Default In China And The Construction Of Risk Early Warning Model Based On Logistic Multiple Regression

Under the macro background of tight supervision and strong supervision in 2018,the credit bond market ushered in a new wave of default,which made the bond default risk more concerned.This paper sorts out all the default events in China from the perspectives of the time trend of default events,the types of default bonds,the company's attributes of default issuers,industry distribution and geographical distribution,the comparison of before 2018(2014-In 2017)and 2018 defaults is the focus of analysis.It concludes that there are more default bonds and the balance of default is large in 2018.The defaulters are concentrated in private enterprises.Medium-term notes and corporate bonds facing the peak of resale and expiration are the worst.The default events have no obvious industry or geographic attributes.This paper takes the default subject of 2014-2018 in September and September as an analysis sample,and takes the default subject of 2018 from October to December as the test sample for one-to-one matching.Select 25 financial indicators that represent the company's solvency,capital structure,profitability,growth,operational ability and cash position.Six principal component factors were extracted from the 19 significant differences between the two samples,and combined with the macroeconomic variable.A risk early warning model of logistic multiple regression was established.In the final sample,the correct rate of recognition was 79.2%,and the correct rate of sample detection was 78.6%.The model prediction ability was good.Finally,combined with the status quo of China's default and the research results of this paper,four policy recommendations are put forward.