Credit rating of manufacturing corporations in Tehran stock exchange withmulti-criteriadecision-makingandartificial neural network models

Document Type : Original Article

Authors
Maghsoud Amiri 1
Morteza Bakyhoskoie 2
Mehdi Biglari Kami 3
1 Associate Professor, Allametabatabaie university
2 Assistant Professor, Allametabatabaie university
3 Institution Raja University, Qazvin , Corresponding Author's
Abstract
This paper is investigated the credit rating of manufacturing firms in Tehran Stock Exchange. In this regard, have been extracted  financial ratios of  public stock companies during the three years from the financial statements. This financial ratios indicates the ability to pay principal and interest of loan. Initially, 50 companies were selected and ranked by the TOPSIS method. Financial ratios are as a criterion and weight of the each criterion are determined by using Shannon entropy method. Then the ranking, companies are classified into four categories. The artificial neural network is trained to classify and after training the neural network are tested. Statistical results show robust classification of neural network. Then all the companies included in this study are classified by neural network.
Keywords
Financial Ratios
TOPSIS
Artificial Neural Network