Comparison of the performance ratings of listed companies in the securities and neural models securities exchange

Ranking companies based on transparency of financial information can help better decision making in the stock market. In this study, by examining the financial statements of companies and measuring the transparency of financial information, their ranking is based on neural and fuzzy models. Another purpose of the present study is to compare neural and fuzzy models for ranking the transparency of corporate financial information. This is an applied research based on descriptive-analytical method. The statistical population includes the stock exchange companies during the years 2008-2009 and 198 companies were selected and analyzed by systematic elimination method. Company information was obtained through stock exchange software. Artificial intelligence algorithms were used for ranking and fuzzy and neural models were used. The results showed that among the fuzzy and neural models, the best method for ranking is the neural models and the results of the neural models method give the best results. Given that in fuzzy model, fuzzy method has the most errors and in some estimations it has unacceptable errors.