Application of Neural Networks In Corporate’s Proﬁtability Prediction

Abstract This study aims at profitability prediction of listed companies in Tehran Stocks Exchange (TSE), using Artificial Neural Network. The respected sample consists of 90 firms from 2002 to 2009 (720 firm/years). Attention to the framework of study reduced the number of 720 firm/years to 630 fi...

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Autores principales:	Hossein Etemadi, Adel Azar, Vahid Baghaee
Formato:	article
Lenguaje:	FA
Publicado:	Shahid Bahonar University of Kerman 2012
Materias:	Accounting. Bookkeeping HF5601-5689
Acceso en línea:	https://doaj.org/article/b97341e2bfb84cf3846f23829dc267da
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spelling	oai:doaj.org-article:b97341e2bfb84cf3846f23829dc267da2021-11-04T19:42:36ZApplication of Neural Networks In Corporate’s Proﬁtability Prediction2008-89142476-292X10.22103/jak.2012.444https://doaj.org/article/b97341e2bfb84cf3846f23829dc267da2012-11-01T00:00:00Zhttps://jak.uk.ac.ir/article_444_5170d4dcadb143dc1ea729c58a76a95f.pdfhttps://doaj.org/toc/2008-8914https://doaj.org/toc/2476-292XAbstract This study aims at profitability prediction of listed companies in Tehran Stocks Exchange (TSE), using Artificial Neural Network. The respected sample consists of 90 firms from 2002 to 2009 (720 firm/years). Attention to the framework of study reduced the number of 720 firm/years to 630 firm/years. These firms separated in two groups of learning sample (540 firm/years) and test sample (90 firm/years) to test generalization of the technique. To develop profitability prediction, first, we needed to determine predictor variables. Profitability prediction literature was reviewed and a complete list of financial ratios for successful prediction in the past studies was prepared. Then, we reduced the list from a theoretical point of view, and we used SDA technique to select final financial ratios. Finally, we took 9 financial ratios to develop profitability prediction. Using Artificial Neural Network (ANN) and applying 9 selected financial ratios, achieved 99% accuracy rate in the learning sample and 86% accuracy rate in the test sample for correct classification of the firms into profitability and nonprofitability groups one year before the real state.Hossein EtemadiAdel AzarVahid BaghaeeShahid Bahonar University of KermanarticleAccounting. BookkeepingHF5601-5689FAمجله دانش حسابداری, Vol 3, Iss 10, Pp 51-70 (2012)
institution	DOAJ
collection	DOAJ
language	FA
topic	Accounting. Bookkeeping HF5601-5689
spellingShingle	Accounting. Bookkeeping HF5601-5689 Hossein Etemadi Adel Azar Vahid Baghaee Application of Neural Networks In Corporate’s Proﬁtability Prediction
description	Abstract This study aims at profitability prediction of listed companies in Tehran Stocks Exchange (TSE), using Artificial Neural Network. The respected sample consists of 90 firms from 2002 to 2009 (720 firm/years). Attention to the framework of study reduced the number of 720 firm/years to 630 firm/years. These firms separated in two groups of learning sample (540 firm/years) and test sample (90 firm/years) to test generalization of the technique. To develop profitability prediction, first, we needed to determine predictor variables. Profitability prediction literature was reviewed and a complete list of financial ratios for successful prediction in the past studies was prepared. Then, we reduced the list from a theoretical point of view, and we used SDA technique to select final financial ratios. Finally, we took 9 financial ratios to develop profitability prediction. Using Artificial Neural Network (ANN) and applying 9 selected financial ratios, achieved 99% accuracy rate in the learning sample and 86% accuracy rate in the test sample for correct classification of the firms into profitability and nonprofitability groups one year before the real state.
format	article
author	Hossein Etemadi Adel Azar Vahid Baghaee
author_facet	Hossein Etemadi Adel Azar Vahid Baghaee
author_sort	Hossein Etemadi
title	Application of Neural Networks In Corporate’s Proﬁtability Prediction
title_short	Application of Neural Networks In Corporate’s Proﬁtability Prediction
title_full	Application of Neural Networks In Corporate’s Proﬁtability Prediction
title_fullStr	Application of Neural Networks In Corporate’s Proﬁtability Prediction
title_full_unstemmed	Application of Neural Networks In Corporate’s Proﬁtability Prediction
title_sort	application of neural networks in corporate’s proﬁtability prediction
publisher	Shahid Bahonar University of Kerman
publishDate	2012
url	https://doaj.org/article/b97341e2bfb84cf3846f23829dc267da
work_keys_str_mv	AT hosseinetemadi applicationofneuralnetworksincorporatesprofitabilityprediction AT adelazar applicationofneuralnetworksincorporatesprofitabilityprediction AT vahidbaghaee applicationofneuralnetworksincorporatesprofitabilityprediction
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Application of Neural Networks In Corporate’s Proﬁtability Prediction

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