The Prediction Model Of Enterprise Financial Crisis Based On The Rough Sets Theory And The Study

The conclusions elicited by so many studies at home and abroad indicated that the financial data and financial index can be used to predict the financial crisis or bankruptcy risk of an enterprise, and in case of the methods in the field of financial risk prediction has inclined to be stability, and no important breakthrough in recent years. Correlated studies are only inconstant to mature in technical details, and some existing problems, for instance the selection of prediction variables, multicollinearlity etc, still remain unsolved effectively up to today. To settle the involved problems virtually, the decisive breakthrough in the study methods is needed! The correlated study methods of our home country are primarily following the abroad, and the innovations are limited! This paper introduces the idea of rough sets theory and information entropy to build up a model, which can be used to predict the financial risk of an enterprise, in case some correlated affairs occur in some degree. Concerning the chosen of the prediction variable, firstly, this paper employs statistical technic to elementarily filter the financial indexes, then plan an attribute reduction arithmetic based on the property of information entropy to simplify it, so as to elicit the variables involved in the model. The technic which I use to elicit the coefficient of the prediction variable is that I firstly compute the dependance of condition attribute and decision attribute, then work out the importance of condition property(financial index), finally unify this importance and get the coefficient of prediction variable. Different from the former' verifying method of the model, this paper employ a two-step checkup mode to show the prediction effect of this model. In the first step, I check it with the small sample set, then collect samples as many as possible to check it again to testify the stability. Accompanied by each step, Fisher discriminant analysis is employed to make contrast analysis to the prediction result. Study result has indicated that, the result of this model is well enough. With the same financial information, it does better than Fisher discriminantanalysis. By the small sample checked, this model reach a correct differentiation ratio of 100ï¼… before one year of the financial risk(ST) happens; and by the large sample checked, I choose the data come from 878 stock market corporations, and the number of miscarriage of justice is only 9. Even before 4 years of ST, with small sample checking, the miscarriage of justice ratio is only 21ï¼…. Selecting 273 enterprises randomly to proceed large sample check, the number of miscarriage of justice is 22.The paper consists of five part: the first part mainly introduces the background and research situation in the home and abroad; and the second part reviews and analyses traditional models on financial crisis prediction; then inducts two correlated concept, named rough sets theory and information entropy; and in the first part the paper builds up the prediction model based on rough sets theory, and especially describe the filtering technic based on the information entropy; finally the fifth part analyses the model with the study.