Research On The Effect Of KMV-Logistic Model On Credit Risk Measurement Of Listed Smes

SMEs occupy a very important proportion in the national economy,and they are also one of the important driving forces in alleviating employment pressure and leading innovation.But at the same time,SMEs are in an absolute disadvantaged position compared to large enterprises in China's market due to their small scale and immature operations.Commercial bank loans are the most important financing method for small and medium-sized enterprises.However,SMEs themselves are characterized by poor asset quality,small scale,and poor ability to resist risks.And information asymmetry often exists between commercial banks and enterprises.Commercial banks often cannot reasonably and effectively measure the credit risk of SMEs,which has led to the phenomenon of "poor loans" and makes the development of SMEs increasingly worrying.Therefore,in order to solve the longterm financing problems of SMEs and promote their better and faster development,the key is to find a measurement method that can accurately assess their credit risk.Based on the research background and significance,this article reviews a large number of literatures.First of all,this article makes a conceptual definition of SMEs and credit risk.Then it analyzes the credit risk status,characteristics,and causes of SMEs,and compares various types of credit risk.After measuring the model,a KMV model and a Logistic model were selected to construct a KMV-Logistic model to accurately measure the credit risk of SMEs in China.This article selects a total of42 listed SMEs that have been ST or * ST from 2015 to 2019 as a sample of high credit risk companies,and selects 126 listed SMEs that are not ST as a sample of low credit risk company based on industry and asset size.First,the default distance of each company was calculated using the KMV model.Then,a total of 21 selected financial or non-financial indicators were used to establish a logistic model after extracting the principal component factors.The default distance and these principal component factors were used as independent variables for regression and the KMVLogistic model was established.The goodness of fit and discrimination accuracy of the two models were compared.Based on the analysis of the model,this article draws the following three points:(1)It is reasonable to combine the KMV model and the Logistic model;(2)The KMV-Logistic model established in this paper has a good fit for sample data and The discrimination accuracy is better than the traditional Logistic model,which has been confirmed when the model is tested;(3)The coefficients of the respective variables in the model can better reflect the relationship between the independent variable and the size of credit risk,which is in line with economic significance.Therefore,this article draws the final conclusions based on the above three points.It is feasible to use the KMV-Logistic model to measure the credit risk of listed SMEs,and the discriminative accuracy of the hybrid model is better than the traditional Logistic model,which can more effectively evaluate Credit risk assessment of SMEs.Finally,on the issue of credit risk measurement,policy recommendations were made to SMEs,commercial banks and government.