Research On Early-warning Of Financial Distress In Listed Companies Of High-tech Industries

With the continuous deepening of the knowledge economy, high-tech industry play an increasingly significant role in the nation economic development process. the development of high-tech enterprises increasingly become a social force to be reckoned. But high-risk nature of high-tech enterprises means that their production and business activities will be faced with many uncertainties. these factors constitute obstacles and difficulties to the production and management of high-tech enterprises, which will affect their survival and development, and increase the possibility of a financial distress, or even go bankrupt. If exert scientific analysis of the financial situation to high-tech companies in recent years, it can be predicted in time and solved to financial problems. so as to ensure sustained, rapid and healthy development of listed high-tech companies.Basing on the research situation and tendency at present, this thesis mainly emphasizes two aspects: setting up a scientific and reasonable prediction index system and establishing a prediction model of Chinese listed high-tech industry companies. More especially, this thesis ,firstly, concerning the characteristics of listed high-tech companies, we choose 48 A-share listed high-tech enterprises of Shenzhen and shanghai stock market , 25 primary financial early warning indicators were selected .used SPSS software to carry on the paired samples T-test, 17 characteristics of effective application of variable indicators were ultimately selected. the principal components analysis and binary logistic regression were used to build early warning model. Test the ability to predict accuracy of the model by the use of the training samples. The empirical results show that the principal components analysis and binary logistic regression can effectively improve the rate of correct discrimination. It will contribute to the financial prediction theory, investment and management.