International Business Management
ISSN: OnlineISSN: Print 1993-5250
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Designing Bankruptcy Prediction System Using Artificial Neural Network Based on Evidence from Iranian Manufacturing Companies
Abbas Ramzanzadeh Zeidi, Seyd Mehdy Fadakar, Keyvan Akbarpoor and Maryam Salimi
Page: 5973-5982 | Received 21 Sep 2022, Published online: 21 Sep 2022
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Abstract
Financial distress and bankruptcy result in a lot of costs. The costs will extend to different groups such as creditors, investors, managers, legal institutions and eventually capital owners. Bankruptcy prediction is a way that significantly can avoid financial distress. The purpose of the study is to design a system using artificial neural network to predict bankruptcy of companies listed in Tehran Stock Exchange before occurring bankruptcy, this system should be designed in a way that can predict the financial situation of company within the next three years. The research method is ex-post facto or survey and the statistical population of research including companies listed in Tehran Stock Exchange during 2001-2010. The data of 54 companies (30 bankrupt companies and 24 companies with Tobin Q above one) was tested by two parameters: 0.15 and 03% accuracy (optimism and pessimism).
How to cite this article:
Abbas Ramzanzadeh Zeidi, Seyd Mehdy Fadakar, Keyvan Akbarpoor and Maryam Salimi. Designing Bankruptcy Prediction System Using Artificial Neural Network
Based on Evidence from Iranian Manufacturing Companies.
DOI: https://doi.org/10.36478/ibm.2016.5973.5982
URL: https://www.makhillpublications.co/view-article/1993-5250/ibm.2016.5973.5982