| With the further development of Chinese capital market, the listed companies, as its main body, have been attracting an increasing amount of attention from various fields. In recent years, some listed companies, because of financial crisis, have been reduced to Special Treatment Plate, thus facing the growing danger of being kicked out of market. The financial crises not only endanger its own survival and development, but also brought great loss to the investors and debtors. So, to construct an effective and efficient Financial Distress Predicting Model to meet the requirements of the related interest people is not an academic problem any more, but one which may affect the healthy development of our country's capital market, thus of great realistic significance.With the listed company as the main research target, this essay, according to the criterion of listed company's financial distress because of its abnormal financial performance, thus considered as ST companies , intends to provide a effective financial distress predicting tool by utilizing the public financial data and with the help of principal components analysis method, selecting the most explanatory financial data which may be used a variables to construct logistic regression analysis model to predict financial distress.The results are as the following: (1) this essay applies the principal components analysis method to conduct a second screening on the basis of 15 primary financial ratios, among which 6 ratios demonstrate remarkable stringency, which are operating profit ratio, return on investment, total assets turnover, total current liabilities to total liabilities, total assets increase ratio, and ratio of net cash flow to liabilities. (2) this essay provides a reliable logistic regression predicting model to foresee whether the listed companies will be specially treated because of abnormal financial performance in two years' advance, with the accuracy rate reaching 77.5%. |
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