Study On Finance Distress Of Public Corporations

Chinese capital market has been developing for more than ten years and has got prodigious achievement. Its status in domestic economy had been high affirmed in 2004. Recently, more and more corporations seeming good get into insolvent, then finance distress alter become an important field. All circles demand the study on finance fruit and finance distress. Finance distress is not only a learned problem, but has been an important factor to our corporations and capital market's development.This thesis makes public corporations as the study objects, ST stock corporations because of exceptional finance as criterion to class finance distress. Logistic regression analysis and BP neural network are used to find the optimum finance distress alert model and variables with exoteric financial data. SPSS and Matlab are used to implement them. The results demonstrate that using the last year's financial statement, this thesis's models could forecast the ST stock corporations this year. EVA, the assets reward ratio, income from main operation, assets, net assets, net cash flow from operating activities/sales- net income/cost of sale plus financial cost plus overhead cost plus marketing cost are distinct explanative financial index.