The Market Value Added Forecast Capacity Analysis Based on the Capital Structure and Profitability Using Artificial Neural Network Technique in Companies Accepted in Tehran Stock Exchange
Journal Title: Journal of Science and today’s world - Year 2018, Vol 7, Issue 8
Abstract
The central role of capital in the world of today's trade is not covered to anyone, and this is a very significant role. Meanwhile, the criteria, indices and financial ratios derived from accounting figures are also influenced by the accounting methods adopted and therefore, they will not be able to transfer the correct information related to the investment. In this case, we need a standard that can familiarize investors with the real value of the company. One of the newest criteria that stockholders use to evaluate corporate performance and rewarding to management, is value added. The main objective of this study is to help managers in deciding on the capital structure and combining the use of various sources of finance by them, as well as to clarify the effects of the capital structure and its changes on the market value of companies using artificial neural networks. The neural network used in this study is a generalized feedforward neural network and Elman neural network. The statistical population of this study, including companies accepted in Tehran Stock Exchange, were selected by the elimination method (screening). The time domain of this study is from 2001 to 2010. The collected data was analyzed by using MATLAB 2012. The results showed that a generalized feedforward neural network with 3 neurons in the hidden layer is more optimal than Elman neural network to predict market value added.
Authors and Affiliations
Saeed Zarei, Ahmad Reza Peyravi
Keywords
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