| Corporate financial distress predicting is an important and widely studied topic since it has significant impact on bank lending decisions and profitability. With the rapid development of China's capital market, this research topic is significant, not only in academic research, but also in the practice of financial management.Financial distress predicting forecasts the possibility of a firm's financial failure in a future period by synthesizing financial ratios that are computed from the public audited accounting statements. This thesis tries to develop a general corporate financial distress predicting method, which can be applied to judge the financial status of a corporate without any limitation on its industry sector, size or ownership structure. On the base of reviewing current researches on financial distress predicting, the definition of financial distress and the general process of how and why financial distress occurs are described. It is then suggested that short term prediction is different from median or long term prediction on their cause factors and thus their feature subsets. Variables and feature subsets for short term and median/long term prediction are then proposed by various statistic tests. Experimental results on financial dataset of companies listed in Shanghai and Shenzhen Stock Exchange show the feasibility and rationality of the selected feature subsets and the described forecasting approach.Main contributions of this thesis are summarized as follows: 1. A suggested definition of financial distress is presented, and the general process about how financial distress occurs is described. It is believed that financial distress is a kind of abnormal financial status, which occurs when the firm has chronic and serious losses and/or when the firm becomes insolvent with liabilities that are disproportionate to assets. Without exogenous intervene, a firm in financial distress status will inevitably go bankrupt. Widely identified causes and symptoms of financial...
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