Title : ( Prediction of Economic Value Added of Iranian Listed Companies )
Authors: Mahmoud Mousavi Shiri , Mahdi Salehi , Mostafa Bahrami ,
Full TextAbstract
Economic value added (EVA) is an important issue for economic analysts and investors. This article proposes a method for predicting economic value added of the automotive and steel listed companies on the Tehran Stock Exchange (TSE) using neural networks. The data were collected from the audited financial statements during 2006-2011. EVA was predicted using linear regression and neural networks and the results were compared with actual data. The findings suggested that neural networks method outperforms linear regression in predicting EVA.
Keywords
Neural networks; economic value added; financial ratios; Tehran Stock Exchange; Iran
@article{paperid:1038022,
author = {Mahmoud Mousavi Shiri and Salehi, Mahdi and Mostafa Bahrami},
title = {Prediction of Economic Value Added of Iranian Listed Companies},
journal = {Sovremennaa Ekonomika Problemy Tendencii Perspektivy},
year = {2013},
volume = {9},
number = {2},
month = {October},
issn = {2222-6532},
pages = {45--55},
numpages = {10},
keywords = {Neural networks; economic value added; financial ratios; Tehran Stock Exchange; Iran},
}
%0 Journal Article
%T Prediction of Economic Value Added of Iranian Listed Companies
%A Mahmoud Mousavi Shiri
%A Salehi, Mahdi
%A Mostafa Bahrami
%J Sovremennaa Ekonomika Problemy Tendencii Perspektivy
%@ 2222-6532
%D 2013
