Research on Credit Risk Assessment of Strategic Emerging Enterprises from the Perspective of Firm Value Growth
Guiding more funds to invest in advanced manufacturing and strategic emerging enterprises is an important task at present.This study is based on the panel data of 432 sample stocks of strategic emerging companies in 2021-2022,and uses correlation analysis and Lasso regression to screen two-step indicators.In order to supplement the credit risk assessment index system of strategic emerging enterprises,the KMV model is used to measure the default distance DD,and it is added to the CatBoost model as a variable to evaluate the credit risk level of strategic emerging enterprises and analyze the root causes of credit default.It is found that CatBoost algorithm can accurately evaluate the credit risk level of strategic emerging enterprises,and has obvious improvement in forecasting performance and accuracy compared with logistic regression and random forest.In addition,in addition to the financial efficiency index of corporate profits and returns,technological innovation and external macro environment also have a significant impact on credit risk.Based on the perspective of corporate value growth,it provides experience reference and guidance for commercial banks to support the financing practice of strategic emerging enterprises.
Strategic emerging enterprisesEnterprise value growthCredit risk assessmentDefault distanceCatBoost
NETL
NSTL
万方数据
