Research On Debt Default Risk Of Yango Group Based On KMV-LOGIT Model

The scale grew rapidly as more companies raised money through bonds.In a period of frequent bond bankruptcies,this is an important factor in the study of bond default risk,which is very important for the company itself,investors and regulators.In this paper,the sample of default group is from 2019 to 2021.A-share listed companies that default for the first time are selected,and companies listed at the same time as A-share and B-share are excluded to determine the default group.Companies with similar industry,similar market value and good financial condition were taken as the standard,and they were set as the control group in a ratio of 1:4.Finally,the KMV-LOGIT hybrid model is obtained.The results are compared with those of KMV and LOGIT models.The conclusion is:(1)Most average base groups were less distant from each other than the control group.Thus,these results suggest that,based on reality,default risk is higher than in the control group.Therefore,it is not advisable to use the KMV model to calculate the default rate.(2)The details of the classic logit model are based on historical and financial data,and are based on whether the company meets the variables.Based on the empirical research,this paper puts forward two main factors that affect the default risk of a company: solvency and return on equity.The logit model reflects the financial situation of the company well,with an overall rating of 88.1%.(3)DD can obtain the basic distance of KMV model output.Because KMV is inventory-based,it is possible to compensate for delays in the logit model with historical accounting information.Therefore,the fundamental distance DD is used as an argument and applied to the logit model.The conclusion is that net asset profitability,capital adequacy ratio and breach of DD agreement are the most important factors that cause the default risk of debtors.In addition,after the introduction of DD default,the model fits better than the existing rodit model,and the overall recognition rate increases to 89.6%,indicating that the default risk model can be measured more comprehensively and accurately.(4)Finally,this thesis is based on the mixed KMV-Logit model.Taking the default debt scene as an example,this paper analyzes the default,problems and reasons of Sunnyside.Based on Sunnyside’s 2021 financial data,the model is used to predict default risk.The results show that the mixed KMV-Logit model has strong applicability in the study of debt default risk.