Study Of Corporate Financial Distress Prediction Model

The research of the company's financial distress forecast at domestic and international, particularly in the nations that has developed capital market, is a lesson causing extensive concern. As an importance part in the economy and the financial early warning system, it not only has the higher academic value, but also has got the enormous social application value. With the our country market economy system deep reforming and the fast development of the capital market, the need in studying the listed company's financial distress forecast is increasingly urgent. It is urgent to perfect economic forecast method and to establish an effectively economic early-warning system. Establishing the listed company's financial distress forecast model can help the subject economic man reduce the operating risk, assure the economic system's reform, and guarantee the smooth and effective movement of the capital market in our country, and allocate excellently the resources. Along with the economic theoretical development and the improvement of its research method, the research is continuously going ahead further, and the strong need in the actual operating field also promotes the research in the academic circles. This text began with analyzing the financial distress theories, on the foundation of many previous datum, in the actual situation of our country listed company, made use of the BP neural network model to establish financial distress forecast model, and studied the application of financial distress forecast theories in our country.1. chapter 1: Generalizing completely the origin, the development and the basic system of the financial distress forecast theories. Explaining the basic concept, the classification, the root of the financial distress forecast and the measure to solve it.2. chapter 2: Reviewing the domestic and foreign previous datum in the financial distress forecast.3. chapter 3: Analyzing the models and finding out the appropriate way to establish the financial distress forecast model.4. chapter 4: At first , analyzing the characteristic and the reason of our country listed company's financial distress forecast. Establishing the finance forecast model. And then, for making the demonstration studies on our country listed company, this text made use nf the BP neural network technique to establish the forecast model that fit to our country listed company, when I picked up 14 variables and chose the 58 stylebooks from manufacturing, t considered our country special situation, noticed the influence coming from the different economic period, and confirmed the stylebooks that I chose match the definition of the finance forecast. The demonstration research showed that the model's success rate is 85%.5. chapter 5: On the foundation of the above chapters, through the studies, the text pointed out the problems that come from the researchand the application of the finance forecast theories exists in our country. This text analyzed deeply the reason and the negative influence, and gave some concrete suggestions.