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Effective Components on the Forecast of Companies' Dividends using Hybrid Neural Network and Binary Algorithm Model


Affiliations
1 Department of Accounting, Ferdowsi University of Mashhad, Iran, Islamic Republic of
2 Department of Accounting, Science and Research of Hormozgan Branch, Islamic Azad University, Hormozgan, Iran, Islamic Republic of
 

The issue of accounting profit has been noticed from long time by investors, managers, financial analysts and creditors. Due to the importance of dividend per share is disclosed by companies and the role of dividend in decisions and because the most important source of information for investors and managers and other users in the stock, is the forecasted dividend by companies, this study follows to recognize the affecting factors on 23 chemical companies in the Tehran Stock Exchange dividend using genetic algorithms combined with artificial neural network. Finally, the variables affecting the output are used to predict dividends in the model that is by neural network designed. The error is calculated and be the basis of comparison with other methods. The study included chemical companies accepted in Tehran Stock Exchange during 2006-2010. The independent variables in this study are accounting ratios and stock cash dividend is dependent variable.

Keywords

Prediction, Dividends, Neural Network, Binary Algorithm
User

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  • Effective Components on the Forecast of Companies' Dividends using Hybrid Neural Network and Binary Algorithm Model

Abstract Views: 398  |  PDF Views: 110

Authors

Mahdi Salehi
Department of Accounting, Ferdowsi University of Mashhad, Iran, Islamic Republic of
Behad Kardan
Department of Accounting, Ferdowsi University of Mashhad, Iran, Islamic Republic of
Zohresh Aminifard
Department of Accounting, Science and Research of Hormozgan Branch, Islamic Azad University, Hormozgan, Iran, Islamic Republic of

Abstract


The issue of accounting profit has been noticed from long time by investors, managers, financial analysts and creditors. Due to the importance of dividend per share is disclosed by companies and the role of dividend in decisions and because the most important source of information for investors and managers and other users in the stock, is the forecasted dividend by companies, this study follows to recognize the affecting factors on 23 chemical companies in the Tehran Stock Exchange dividend using genetic algorithms combined with artificial neural network. Finally, the variables affecting the output are used to predict dividends in the model that is by neural network designed. The error is calculated and be the basis of comparison with other methods. The study included chemical companies accepted in Tehran Stock Exchange during 2006-2010. The independent variables in this study are accounting ratios and stock cash dividend is dependent variable.

Keywords


Prediction, Dividends, Neural Network, Binary Algorithm

References





DOI: https://doi.org/10.17485/ijst%2F2012%2Fv5i9%2F30680