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- W2377170457 abstract "In the discriminant analysis and prediction of corporate financial distress, selections of financial ratios in regression model rely on t-test and F-test, and the retained variables may contain the impact of subjective hypothesis and the problem of collinearity. Factor analysis can reduce many financial ratios to principal components that reflect the comprehensive financial status of enterprises. These components will serve as the input variables for the binary Logistic function of corporate financial distress forecasting. Empirical studies for listed companies found 7 mutually-independent principal components, whose cumulative variances covered (81.427%) of the total variances of 25 financial ratios.The combination of factor analysis with Logit model can avoid the capriciousness and collinearity in the selection of financial ratios. The principal components can maximize the differentiation between sound financial conditions and financial distresses, and make early warnings of corporate financial distresses. " @default.
- W2377170457 created "2016-06-24" @default.
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- W2377170457 date "2005-01-01" @default.
- W2377170457 modified "2023-09-22" @default.
- W2377170457 title "Model of Early Warning for Corporate Financial Distress" @default.
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