Prediction of economic value added of Iranian listed companies

Mousavi Shiri Mahmoud, Salehi Mehdi and Bahrami Mostafa
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Mousavi Shiri Mahmoud: Payame Noor University
Salehi Mehdi: Ferdowsi University of Mashhad
Bahrami Mostafa: Hidaj Branch, Islamic Azad University

Sovremennaa ekonomika: problemy, tendencii, perspektivy Современная экономика: проблемы, тенденции, перспективы, 2013, issue 9 (2), 45-55

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.

Keywords: НЕЙРОННЫЕ СЕТИ; ЭКОНОМИЧЕСКАЯ ДОБАВЛЕННАЯ СТОИМОСТЬ; ФИНАНСОВЫЕ КОЭФФИЦИЕНТЫ; ТЕГЕРАНСКАЯ ФОНДОВАЯ БИРЖА; ИРАН (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:scn:018798:14507724

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