Author/Authors
Mousavi Shiri، Mahmoud نويسنده Department accounting, Payame Noor University, Mashhad, KhorasanRazavi , , Salehi، Mehdi نويسنده , , Bahrami، Mostafa نويسنده Hidaj Branch, Islamic Azad University Bahrami, Mostafa
DocumentNumber
2444687
Title Of Article
Prediction of Economic Value Added of Iranian Listed Companies
شماره ركورد
13124
Latin Abstract
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.
SubTitle
Прогнозирование экономической добавленной стоимости компаний Ирана, котирующихся на бирже
From Page
45
JournalTitle
Studia Iranica
To Page
55
To Page
55
Serial Year
2013
Link To Document