我国制造业上市公司信用风险评估的实证研究

his paper selects 90 manufacturing listed companies from stock markets of Shanghai and Shenzhen to form research samples and conducts an empirical analysis on the credit risk assessment of China\'s manufacturing listed companies. Firstly, this paper reduces the dimension of primarily selected indicator variables based on principal component analysis, and obtains 8 principal components to build Logistic model. Then, the default distance calculated by KMV model is introduced into the original model and the Logistic-KMV model is formed. Based on the regression, the effect of this model on the credit risk assessment of China\'s manufacturing listed companies is observed. Finally, it is found that the combination analysis of non-financial indicator and financial indicator is effective; the profitability and solvency of the company have a great impact on its credit risk; it is feasible to introduce the default distance as an assessment indicator into the mixed model; the Logistic-KMV model constructed has good prediction effect.