Information Processing in Design and Testing of Financial Early Warning Method of Listed Companies in China - Based on the Logistic Regression Analysis

Information processing is of essential importance for an effective financial early warning model. In order to design the model of financial early warning for listed companies, we selected the 120 listed companies as research samples, chose the necessary information and relatively financial indexes and detected them by K-S normality test, then separately analyzed the results by One-Sample T test and Nonparametric Test. Through the discriminant analysis to the correlation analysis, we can identify the independent variables of logistic analysis, introduce in the quadratic term and cross term for logistic regression analysis. Applied the model in financial crisis prediction of the listed companies in China, the empirical results indicate that the prediction accuracy is 87.4%. The model from relatively information and financial index provides a kind of early warning method, which is simple practicable and scientific, for estimating the business status of a company.