The Application Of Logistic Regression Model In Financial Crisis Prediction Of China’s Listed Company

With the development of the economics and the keen competition between different enterprises, the possibility of financial crisis for enterprise is increasing rapidly, which bring the enterprise risk prediction to an urgent place. In 2009,the Gem is opened in Shenzhen stock exchange, provide IPO and financing services for the medium-sized company(specially the hi-tech enterprise in a growth period).The kind of enterprises mentioned before mostly trapped in the situation where the performance of the business is not steadily, thus lead to a huge risk in both financing and operation function. To give a solution for the above status, this article constructs a financial risk prediction model combing with the actual situation for the listed company.We analysis the characteristics of the listed companies to state the necessity of financial risk crisis prediction for such companies first. Based on reviewing the national and the abroad relevant financial risk prediction articles, we summary the theory and characteristics of financial crisis prediction. To illustrate the problem, we select 484 companies’(year 2013-2015,GEM listed company) financial statement to process the empirical study, and classify them into three different groups(good financial condition, volatile financial condition, financial crisis condition) based on the performance of the financial statements. Using the factor analysis and Logistic regression model, we construct a trinomial ordered logistic model and a binomial logistic financial crisis prediction model. Comparing the above two models in forecast accuracy analysis. The results show that its prediction accuracy is higher than binomial logistic prediction model 1.89%.The misclassification of the trinomial ordered model mainly occurs between financial crisis and financial instability. It has a certain relationship with classification standard in this paper. Finally, according to the paper research conclusion, we can make relevant policies and suggestions for financial crisis prediction of China’s Gem listed companies.