The Research Of Stage Forecasting Model Against Financial Distress On The Manufacturing Of Chinese Listed Company

With the rapid development of the securities market and the increasingly fierce competition, the number and the scale of listed companies continue to expand, but they also face growing pressures of survival at the same time. Risk oversight, policy blunders, or management errors and so on, may make enterprise be caught in financial distress. In reality, the cases is common that financial situation of enterprises gradual worsen from normal, forming financial distress, even resulting in bankruptcy. Therefore, it is urgent need to establish a sensitive forecasting model against financial distress.Because it is a developmental process that enterprises fall into financial distress, the characteristic and inducement is different in different stage, so the financial targets and the forecasting model is different too. But at present, the studying of stage forecasting model against financial distress is insufficient. Thus this article intend to divided the stage of financial distress, then choose the corresponding index variable by different stage, attempt to build the stage forecasting model against financial distress.The article makes use of the financial data that already be public audited of listed company in our country, takes manufacturing industry as typical industry, utilizes the methods such as Paired-sample T test and Logistic regression analysis, in virtue of the software of Excel and SPSS, builds the stage forecasting model against financial distress.At present, there are confused concepts about financial distress and financial crisis. So first, the article defines financial distress by distinguish two concepts, and financial distress is measured off three stages, including latent period, evolutive period, and crisis. Second, the data of financial distress are made Paired-sample T test with those of financial normal in manufacturing industry, so the dividing line can be found between significant difference with nonsignificant difference, that is the beginning of financial distress. Therewith three stages can be divided on hypothesis by quantify method. And at the same time the index variable can be made sure. Third, every stage model is set up by corresponding index and Logistic regression method. After testing, the result of the study indicates that the accuracy of judging of this model is high, and has good forecast effect. Finally, the article points out the deficiency and next researching aspect in the future.