Corporate Credit Risk Metric Model Based On Option Underlying Beta And Its Empirical Research

In order to accurately predict and identify the credit risks of listed companies,this paper comprehensively considers the real uncertainty risk in the financial market and establishes a reasonable and scientific credit risk structured model.It mainly utilizes the "dominant" expression advantage of the option underlying beta and the KMV model which can dynamically and sensitively reflect the credit status of the listed company,hoping to effectively improve the risk identification and management capabilities of financial institutions and enterprises.Firstly,according to the structured model which employs the equity value of the company with the idea of option characteristics to the corporate credit risk metric,this paper innovatively combines option underlying beta with the KMV model with the ideology of option pricing to capture the nonlinear relationship between the company's equity price and asset value from the perspective of the option underlying beta.Furthermore,the corporate credit risk metric model based on option underlying beta is established.Secondly,the article attempts to estimate the option underlying beta by least squares regression.To do this,the article combines the CAPM framework and characteristics of the option underlying beta to construct the relationship between the company's equity value return and the company's asset value return,and uses the weighted average cost of capital(WACC)to determine the underlying beta,and further excavates and depicts the process of the change in the company's asset value.Finally,in order to verify the effectiveness of the new model in screening the listed company's default risk and the difference with the classic KMV model,the 38 "Special treatment(ST)" and"non-ST" sample companies in the Shanghai and Shenzhen stock exchanges are selected for empirical analysis.Meanwhile,comparative analysis is performed by using multiple test methods such as Moses Extreme Reaction,Kolmogorov-Smirnov,Wald-Wolfowitz,and ROC curve analysis.The following empirical conclusions are obtained:·There is a significant difference of default distance between the "ST" and "non-ST"companies calculated by the new model and the classic KMV model.It shows that the model is effective in distinguishing the credit default status of these two types of companies,that is,the model can identify the credit default risk of these two types of companies.·The difference of default distance between "ST" and "non-ST" companies calculated by using the new model is more significant than that of classic KMV model.This shows that the new model proposed in this paper is more efficient in distinguishing the credit default status of "ST"and "non-ST" companies to some extent.