Financial Crisis Predicting Of Listed Textile Industry

In2008, the US subprime lending crisis triggered a global financial crisis and a large number of bank bankruptcy and corporate bankruptcy. If the managers and investors carry out the crisis management, the losses of corporate would be less under this global financial crisis. Currently the economic environment is very complicated, predicting the financial crisis is very important to carry out the risk management of our corporate.Financial crisis predicting is based on the characteristics of corporate financial crisis, finding the combination of variables is very important. For China’s listed companies do not have the legal instances of bankruptcy, the article define the financial crisis corporate as the one that began to break the contracts of the debt or cost. Because there is a close relationship between the ratio of bad debt and the credit grade of corporate, the article use the2012corporate credit grade to define the financial crisis corporate of the China’s listed textile industry. Because there is a close relationship between the financial ratios and the credit grade, the article establishes the indicator system of financial crisis predicting base on the indicator system of credit grade. The learning process of BP neural network establishes the financial crisis method based on the training date in2010-2012, the classification process of BP neural network accomplishes the predicting process of financial crisis.The research conclusion indicates that the combination of variables can effectively reflect the characteristics of the financial crisis corporate, and providing the intelligence information for the managers and investors of the corporate.