Studies of Discriminant Analysis and Logistic Regression Model Application in Credit Risk for China’s Listed Companies

Konglai ZHU, Jingjing LI

Abstract


With the appearance of listed companies’ credit issues and frequent credit crisis, investors are increasingly concerned about credit risk analysis for listed companies. In view of the current development methods of credit risk analysis and the importance of identifying corporate financial risk, this paper designed an effective indicator system and established the credit evaluation models of China’s listed companies by taking advantage of their 2009 financial data. Combined with the reality of China's listed companies, we use the established models to discriminate and analyze. The result of empirical research on the credit risk analysis for listed companies is that Logistic regression model is superior to discriminant analysis model. Key words: Credit Risk; Discriminant Analysis; Logistic Regression Model; Principal Component Analysis

Keywords


Credit Risk; Discriminant Analysis; Logistic Regression Model; Principal Component Analysis

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DOI: http://dx.doi.org/10.3968/j.mse.1913035X20100404.004

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