Research On The Effect Of Credit Default Risk Measurement Of Pharmaceutical Listed Companies Based On KMV-Logistic Model

Since the release of the "13th Five-Year Plan" for the development of the pharmaceutical industry,the state has encouraged the research and development of innovative drugs,and the market scale of the pharmaceutical manufacturing industry has been expanding,which has promoted the vigorous development of the pharmaceutical industry.At the same time,the pharmaceutical management department has carried out regular and institutionalized reforms in the pharmaceutical industry.In terms of pharmaceuticals,the relevant departments have accelerated drug approval and strictly implemented consistent evaluation of drug quality and efficacy,which has improved the concentration of the industry and avoided wasting R&D resources.However,the implementation of policies such as "procurement with quantity" and "health insurance catalogue negotiation" has also intensified the competition among pharmaceutical enterprises.Companies significantly lowered their drug prices to gain market share,while companies that did not win the bidding faced the double pressure of lower drug prices and competition for remaining market share.In addition,the high-income pharmaceutical industry is also accompanied by a series of risks such as financing risk,R&D risk,and policy risk.Therefore,in the context of national policy regulation and the high-risk characteristics of the pharmaceutical industry,finding a suitable method to measure credit risk for listed pharmaceutical companies and identifying risk prevention by quantifying risk has certain significance for both the companies themselves and investors.In this study,13 listed pharmaceutical companies that were ST during 2017-2021 were selected as default samples,and accordingly 39 control samples in the same industry were selected in the ratio of 1:3.The empirical study on the effect of credit default risk measurement by three different methods,KMV model,Logistic model and KMV-Logistic model,was conducted in conjunction with the annual financial data of the companies Firstly,the default distance of each enterprise is calculated with the KMV model.Then,the16 financial indicators reflecting the enterprise’s profitability,solvency,operation ability and growth ability are synthesized into four principal components by the principal component analysis method to establish the Logistic model.Finally,the default distance calculated by the KMV model was added into the Logistic regression model as explanatory variable to build a comprehensive KMV-Logistic model,and the goodness of fit of different models and the discrimination accuracy of default risk were compared and analyzed.The following conclusions are drawn from the empirical study:(1)The default distance calculated by the KMV model can well distinguish the default sample from the control sample,and the mean value of the default distance of the default sample is significantly smaller than that of the control sample,indicating that the KMV model has a better measure of default risk.(2)The volatility of equity value affects the default distance to a large extent,but the change of stock price is often affected by multiple factors,so it is reasonable to construct KMV-Logistic model for a comprehensive analysis.(3)Compared with the Logistic model,the KMV-Logistic model with default distance has better goodness of fit and risk discriminant accuracy,which is suitable for the default risk measurement of Chinese pharmaceutical listed enterprises.