The Research On The Influencing Factors Of Corporate Bond Default In China

In 2014,the bond named Chao Ri defaulted,breaking the myth of "rigid payment" in China’s credit bond market and creating a precedent for credit bond defaults.In recent years,with the economic transformation and upgrading and stricter financial supervision,default events in China’s credit bonds have begun to occur frequently.The defaulters of bonds have begun to spread to some large-scale companies with good financial conditions.It is vast.Nowadays,in all walks of life,the phenomenon of bond default has become commonplace.The normalization of bond default has gradually become a new feature of China’s credit bond market.In this context,it is very important to study the factors that cause credit defaults in China to better manage credit risk.In this paper,we take companies with substantial bond defaults as research objects,and take listed companies with bond defaults between 2017 and 2019 as research objects,and select comparable companies in the same industry with stable financial conditions as control samples.The six perspectives of indicators,profitability,solvency,operating ability,growth ability and indicators per share are examined,and a KMV-Logit model is constructed to quantify the default risk of credit bonds.It also uses the KMV model and the classic logit model to conduct empirical analysis of the same data at the same time.Finally,a comparison and analysis of the results of the three models is made,and the following conclusions are mainly drawn:(1)The default distance DD calculated by the KMV model can preliminarily distinguish between the default group company and the control group company.The default distance DD of the default group company is generally relatively small,which indicates that the default risk of the default group is greater.(2)The classic Logit model is constructed based on the company’s actual default results and financial indicators.The company’s default is used as the dependent variable.For a company that has defaulted for the first time in t,the financial data indicator for t-1 years is used as the explanatory variable.return.The results show that the Logit model can well fit the financial status of listed companies in China,and the simulation results show that the overall discrimination rate of the model reaches 92.6%.According to the empirical results,the risk factors affecting the default of credit debt entities are mainly the return on assets,the asset-liability ratio,the total asset turnover ratio,the net asset growth rate,and the net cash flow per share.(3)The KMV-Logit hybrid model constructed in this paper is to introduce the market-oriented indicator default distance DD output by the KMV model into the Logit model as an explanatory variable and perform regression again.The empirical results show that the default distance,return on assets,asset-liability ratio,total asset turnover ratio,net asset growth rate,and net cash flow per share are factors that affect the risk of default.The empirical results show that after adding the default distance DD,the overall discriminant rate of the model is increased to 94.9%,which indicates that the hybrid model has a high degree of good fitting and can more comprehensively and effectively measure the influencing factors of default risk.