Research On Credit Risk Of Listed Companies In Supply Chain Finance Of Automobile Industry Based On Modified KMV Model

In recent years,China's automobile industry has achieved rapid development and formed a relatively complete industrial chain.SMEs in the industrial chain still have problems such as small scale and unstable operation,which makes such enterprises have certain resistance when they make financing loans to financial institutions such as banks.Therefore,in order to solve the problem of financing difficulties for some SMEs in the supply chain,a new financing model,namely supply chain financial business,has been formed.The supply chain financial model can provide more credit guarantees for financial institutions such as banks by introducing third-party logistics companies to supervise and transport collateral.However,in our country,the quantitative identification of supply chain financial risks and effective prevention management system are still not perfect.Therefore,the identification of credit risk in supply chain enterprises is one of the major problems facing the development of supply chain finance.Taking the supply chain finance of the automobile industry as an example,this paper clarifies the theoretical concepts related to financial risk of supply chain through literature review,and compares and analyzes the existing credit risk models,and selects the risk quantification model suitable for China's financial market.Firstly,according to the research content and the availability of data,16 listed companies in the automotive industry supply chain were selected as test sample samples,and the data was processed and verified.The RARCH model is used to construct the GARCH(1,1)model for the logarithmic rate of return data of these enterprises,and the fluctuation data of the equity value of each enterprise is obtained.Then the modified KMV model is obtained by correcting the default point and default probability calculation of the classic KMV model,and using this model to obtain the default distance of each enterprise.Since there is no complete enterprise credit risk mapping database in China,this paper draws on the Brownian distribution of the enterprise value proposed by Moody's,and obtains the default probability of each enterprise.The order of default risk of the three types of enterprises in the supply chain finance of the automobile industry is: automobile dealers> parts suppliers> automobile core manufacturing enterprises,and the difference in credit risk among different types of enterprises is more obvious.Then,12 enterprises that did not pass the GARCH test were randomly selected as the comparison set samples to construct the classic KMV model.By comparing and analyzing the corrected KMV model and the classic KMV model,the modified KMV model can more effectively identify the credit risk and is more suitable for the credit risk analysis of enterprises in China's automotive industry supply chain finance.According to this,the enterprises in different positions in the supply chain of China's automobile industry make corresponding suggestions based on the default distance and the probability of credit risk.Finally,in order to reduce the financial risk of supply chain and establish a sound credit risk management system,a corresponding strategy is proposed.