A Hybrid Analysis Approach to Improve Financial Distress Forecasting: Empirical Evidence from Iran

A Hybrid Analysis Approach to Improve Financial Distress Forecasting: Empirical Evidence from Iran

Bankruptcy prediction is an important problem facing financial decision support for stakeholders of firms, including auditors, managers, shareholders, debt-holders, and potential investors, as well as academic researchers. Popular discourse on financial distress forecasting focuses on developing the...

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Main Authors: Shakiba Khademolqorani, Ali Zeinal Hamadani, Farimah Mokhatab Rafiei
Format: Article
Language:English
Published: Hindawi Limited 2015-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2015/178197
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spelling doaj-a81edb8092c04231b114f7120affa6b52020-11-24T23:42:25ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472015-01-01201510.1155/2015/178197178197A Hybrid Analysis Approach to Improve Financial Distress Forecasting: Empirical Evidence from IranShakiba Khademolqorani0Ali Zeinal Hamadani1Farimah Mokhatab Rafiei2Department of Industrial & Systems Engineering, Isfahan University of Technology, Isfahan 84156 83111, IranDepartment of Industrial & Systems Engineering, Isfahan University of Technology, Isfahan 84156 83111, IranDepartment of Industrial & Systems Engineering, Isfahan University of Technology, Isfahan 84156 83111, IranBankruptcy prediction is an important problem facing financial decision support for stakeholders of firms, including auditors, managers, shareholders, debt-holders, and potential investors, as well as academic researchers. Popular discourse on financial distress forecasting focuses on developing the discrete models to improve the prediction. The aim of this paper is to develop a novel hybrid financial distress model based on combining various statistical and machine learning methods. Then multiple attribute decision making method is exploited to choose the optimized model from the implemented ones. Proposed approaches have also been applied in Iranian companies that performed previous models and it can be consolidated with the help of the hybrid approach.http://dx.doi.org/10.1155/2015/178197
collection DOAJ
language English
format Article
sources DOAJ
author Shakiba Khademolqorani
Ali Zeinal Hamadani
Farimah Mokhatab Rafiei
spellingShingle Shakiba Khademolqorani
Ali Zeinal Hamadani
Farimah Mokhatab Rafiei
A Hybrid Analysis Approach to Improve Financial Distress Forecasting: Empirical Evidence from Iran
Mathematical Problems in Engineering
author_facet Shakiba Khademolqorani
Ali Zeinal Hamadani
Farimah Mokhatab Rafiei
author_sort Shakiba Khademolqorani
title A Hybrid Analysis Approach to Improve Financial Distress Forecasting: Empirical Evidence from Iran
title_short A Hybrid Analysis Approach to Improve Financial Distress Forecasting: Empirical Evidence from Iran
title_full A Hybrid Analysis Approach to Improve Financial Distress Forecasting: Empirical Evidence from Iran
title_fullStr A Hybrid Analysis Approach to Improve Financial Distress Forecasting: Empirical Evidence from Iran
title_full_unstemmed A Hybrid Analysis Approach to Improve Financial Distress Forecasting: Empirical Evidence from Iran
title_sort hybrid analysis approach to improve financial distress forecasting: empirical evidence from iran
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2015-01-01
description Bankruptcy prediction is an important problem facing financial decision support for stakeholders of firms, including auditors, managers, shareholders, debt-holders, and potential investors, as well as academic researchers. Popular discourse on financial distress forecasting focuses on developing the discrete models to improve the prediction. The aim of this paper is to develop a novel hybrid financial distress model based on combining various statistical and machine learning methods. Then multiple attribute decision making method is exploited to choose the optimized model from the implemented ones. Proposed approaches have also been applied in Iranian companies that performed previous models and it can be consolidated with the help of the hybrid approach.
url http://dx.doi.org/10.1155/2015/178197
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