Research On The Credit Risk Of Bond Market Based On Securities Trading Information

Chinese bond market grows fast in recent years.However,credit risk management has not caught up with the path of bond market.The number of credit default events is increasing fast in the domestic bond market since 2014.The number of defaulted bonds rose to 79 in 2016 and the money of default bond is up to 40.3 billion.From the perspective of the credit risk supervision of Chinese bond market,it is common that rating is not objective or timely and the rating method is relatively backward.So,it is urgent to find the credit risk supervision method which is suitable for Chinese bond market.In this process,we need to fully integrate the development of science and technology,such as big data.Basing on the situation of the domestic bond market and the situation of credit rating,this paper uses the transaction information of securities and big data mining method to construct two credit risk measurement and risk warning models.The DS model was constructed by the bond transaction information and bond underlying attributes.The bond credit risk was measured and predicted by the credit score which was calculated by the risk neutral default probability.Basing on the financial situation,stock transaction information of the issuer company and the pricing theory of BS model,the KMV model was constructed.The credit risk of the issuer was measured and forecasted by the default distance.This paper solves the problem that risk rating is not objective or timely because of incomplete information.If the credit rating agency reduces the credit rating of the issures,it will lead to remarkable increase in the yield to maturity of the bond.However,the yield to maturity of some bonds has risen significantly before the bond credit rating is reduced.Some investors know the credit risk of bond earlier than the professional credit rating agencies.The DS model is effective in the domestic bond market.The DS model has early warning function for bonds' credit deterioration,while its ability to predict good bonds were lower than the bad bonds.The KMV model used by foreign rating agencies cannot be used directly in the Chinese market.The default distance of the bond issuer which is calculated by KMV model cannot be converted directly into default probability because it is not normally distributed.When the parameter of the KMV model change,the distribution of the default distance of the issuer will change greatly.Overall,the expected value distribution of the default distance has a certain regularity with the change of the credit status of the issuer.When the issuer's credit rating is at the A level and above,the better the credit status of the issuer,the smaller the default distance.However,when the issuer's credit rating is below the A level and the better the credit status of the issuer,the bigger the default distance.