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| Article Name : | | | Changes Conservatism And Bankruptcy Prediction Model Using Artificial Neural Networks In Tehran Stock Exchange: An Empirical Approach | | Author Name : | | | Solil Jafari , Abedin Barzegar Khanduzi And Roohollah Arab | | Publisher : | | | Ashok Yakkaldevi | | Article Series No. : | | | GRT-2797 | | Article URL : | |  | Author Profile View PDF In browser | | Abstract : | | | Bankrupt firms and commercial establishments make many problems for governments and users of financial information to investors and creditors to load special pin and increase the risk of investment. Better decisions are made and the resulting liquidity problems and financial investors and the company are prevented. One of the most important models is the model which can predict corporate bankruptcy. The bankruptcy prediction models, can help investors exposure to companies that are in bankruptcy, have been identified and their capital to invest in a better place. Hence conservatism as a model to study the rate of change, in this study, 102 companies listed on the Stock Exchange in the form of bankrupt and non-bankrupt companies used. Most of the Altman model and artificial neural network is less than, but of the two models is much less expensive. | | Keywords : | | |
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