A Hybrid Analysis Approach to Improve Financial Distress Forecasting: Empirical Evidence from Iran
Joint Authors
Khademolqorani, Shakiba
Zeinal Hamadani, Ali
Mokhatab Rafiei, Farimah
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-05-14
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Khademolqorani, Shakiba& Zeinal Hamadani, Ali& Mokhatab Rafiei, Farimah. 2015. A Hybrid Analysis Approach to Improve Financial Distress Forecasting: Empirical Evidence from Iran. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1073125
Modern Language Association (MLA)
Khademolqorani, Shakiba…[et al.]. A Hybrid Analysis Approach to Improve Financial Distress Forecasting: Empirical Evidence from Iran. Mathematical Problems in Engineering No. 2015 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-1073125
American Medical Association (AMA)
Khademolqorani, Shakiba& Zeinal Hamadani, Ali& Mokhatab Rafiei, Farimah. A Hybrid Analysis Approach to Improve Financial Distress Forecasting: Empirical Evidence from Iran. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1073125
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1073125