The Research On Financial Crisis Early-warning Model For Listed Corporations Of China

Along with our country joining the WTO, our country companies face the exterior environment of competition is more and more vigorous. The quantity of the business sink into the financial crisis and cause bankruptcy increased, the ability of resisting the risk is weak. It's important for companies to raise their anti-risk ability and can make them executive known the latent danger as early as possible and adopt the measure. So the research about financial early-warning model for the listed company becomes the focus of the theoretical and practical research.On the basis of the review of previous empirical results, the article carries on more systematic research and discussion on the theory and model of early-warning on financial distress for the listed companies of our country, and tries to construct financial distress prediction models of Chinese listed firms.Firstly, the article expounds the basic theory of the financial early-warning model, defines the concept of financial crisis, and designs a set of pre-warning index system that includes 6 respects and 20 indexes of financial status. The article chooses 70 financial crisis companies implemented special treatment for the first time and 70 paired non-financial crisis companies between 2003 and 2005 as sample of estimating, selects 12 variables which will enter the model by using independent test, factor analysis and correlation analysis etc. Then using logistic regression analysis method to regress the 12 variables, set up the Logistic Distinguishing Model and certified it. The results shows that among 12 variables, return on equity, overall asset increasing ratio and operating cash flow per share which have important effect on financial condition of the companies. At last, chooses 30 financial crisis companies implemented special treatment for the first time and 30 paired non-financial crisis companies in 2006 as test samples to certify the feasibility and effectiveness of the model. The result demonstrates that the model is both effective and feasible, the model can predict the financial distress 2years in advance, and its accuracy of prediction arrived at 88.33%.