Bankruptcy Prediction Using Artifical Neural Networks with Camparsion to the Altman Model

This research has been done under title: Bankruptcy Prediction using Artificsl Neural Networks with camparsion to the Altman Model. The goal of this study is to provide exact explanation and presentation of theoretical basis of research and measurement of usefulness bankruptcy financial models. We presented the research hypotheses in order to provide suitable scientific context for the study. Hypothese 1: Artificsl Neural Networks and Altman models are suitable instrumental for prediction of bankruptcy. Hypothese 2: In prediction of bankruptcy one firm, have significant difference the resultsof this two models. The means of the research statements (Balance sheets, Income statement, cash flow statement) of the companies which were accepted in Tehran Stock Exchange. The library method was employed in data gathering. Statistical population of research includes active companies whose financial statements are accessable in Tehran Stock Exchange. The statistical sample of the research includes active companies in productive industries, from 1379 to 1384. In order to analysis data, We used statistical metods of nonparametric binomial, and for cointegration significant difference two models employed wilcoxon signed- rank test and sign test for hypothese 2. After analyzing the data the results gained id confirmed and supported by above tests.