A Comparison among Artificial Neural Network, Discriminant Analysis and Logestic Regression Techniques for Bankruptcy: A Case Study of Kerman\'s Firms
One of the main issues in financial management is choosing the best way of utilizing investment. Investors would like to invest their capitals in a way to minimize their risks. Bankruptcy is one of the risk factors which affect the decision of investors. Prediction of bankruptcy can help investors t...
| Main Authors: | , , |
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| Format: | Article |
| Language: | fas |
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Tarbiat Modares University
2010-07-01
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| Series: | پژوهشهای اقتصادی |
| Subjects: | |
| Online Access: | http://ecor.modares.ac.ir/article-18-10998-en.pdf |
| _version_ | 1797803200702578688 |
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| author | nezamoddin makyian mohammadtaghi almodaresi salim karimi takloo |
| author_facet | nezamoddin makyian mohammadtaghi almodaresi salim karimi takloo |
| author_sort | nezamoddin makyian |
| collection | DOAJ |
| description | One of the main issues in financial management is choosing the best way of utilizing investment. Investors would like to invest their capitals in a way to minimize their risks. Bankruptcy is one of the risk factors which affect the decision of investors. Prediction of bankruptcy can help investors to reduce the risks in the capital markets and recognize the best opportunities for alternative investment.
This study aims to predict the bankruptcy of companies by using the technique of Artificial Neural Network (ANN). Moreover, discriminant Analysis and logestic regression techniques are employed to compare the results. The data used in this study covers the firms in the Kerman Province of Iran over the period 1975- 2007.
The results show that ANN model perfom much better than the discriminant analysis and logestic regression techniques. Moreover, the results confirm that the accuracy of ANN model is higher than the discriminant analysis and logestic regression techniques for predicting of bankruptcy. The analysis also shows that none of the firms will bankrupt in the year after the period covered in this study. |
| first_indexed | 2024-03-13T05:17:19Z |
| format | Article |
| id | doaj.art-885f740b69d84ad3ba3599f8a65227b0 |
| institution | Directory Open Access Journal |
| issn | 1735-6768 2980-7832 |
| language | fas |
| last_indexed | 2024-03-13T05:17:19Z |
| publishDate | 2010-07-01 |
| publisher | Tarbiat Modares University |
| record_format | Article |
| series | پژوهشهای اقتصادی |
| spelling | doaj.art-885f740b69d84ad3ba3599f8a65227b02023-06-15T20:32:57ZfasTarbiat Modares Universityپژوهشهای اقتصادی1735-67682980-78322010-07-0110200A Comparison among Artificial Neural Network, Discriminant Analysis and Logestic Regression Techniques for Bankruptcy: A Case Study of Kerman\'s Firmsnezamoddin makyian0mohammadtaghi almodaresi1salim karimi takloo2 Yazd University, Economics Faculty yazd university, electrical engineering faculty kerman university One of the main issues in financial management is choosing the best way of utilizing investment. Investors would like to invest their capitals in a way to minimize their risks. Bankruptcy is one of the risk factors which affect the decision of investors. Prediction of bankruptcy can help investors to reduce the risks in the capital markets and recognize the best opportunities for alternative investment. This study aims to predict the bankruptcy of companies by using the technique of Artificial Neural Network (ANN). Moreover, discriminant Analysis and logestic regression techniques are employed to compare the results. The data used in this study covers the firms in the Kerman Province of Iran over the period 1975- 2007. The results show that ANN model perfom much better than the discriminant analysis and logestic regression techniques. Moreover, the results confirm that the accuracy of ANN model is higher than the discriminant analysis and logestic regression techniques for predicting of bankruptcy. The analysis also shows that none of the firms will bankrupt in the year after the period covered in this study.http://ecor.modares.ac.ir/article-18-10998-en.pdfbankruptcy predictionartificial neural networklogestic regressiondiscriminant analysis |
| spellingShingle | nezamoddin makyian mohammadtaghi almodaresi salim karimi takloo A Comparison among Artificial Neural Network, Discriminant Analysis and Logestic Regression Techniques for Bankruptcy: A Case Study of Kerman\'s Firms پژوهشهای اقتصادی bankruptcy prediction artificial neural network logestic regression discriminant analysis |
| title | A Comparison among Artificial Neural Network, Discriminant Analysis and Logestic Regression Techniques for Bankruptcy: A Case Study of Kerman\'s Firms |
| title_full | A Comparison among Artificial Neural Network, Discriminant Analysis and Logestic Regression Techniques for Bankruptcy: A Case Study of Kerman\'s Firms |
| title_fullStr | A Comparison among Artificial Neural Network, Discriminant Analysis and Logestic Regression Techniques for Bankruptcy: A Case Study of Kerman\'s Firms |
| title_full_unstemmed | A Comparison among Artificial Neural Network, Discriminant Analysis and Logestic Regression Techniques for Bankruptcy: A Case Study of Kerman\'s Firms |
| title_short | A Comparison among Artificial Neural Network, Discriminant Analysis and Logestic Regression Techniques for Bankruptcy: A Case Study of Kerman\'s Firms |
| title_sort | comparison among artificial neural network discriminant analysis and logestic regression techniques for bankruptcy a case study of kerman s firms |
| topic | bankruptcy prediction artificial neural network logestic regression discriminant analysis |
| url | http://ecor.modares.ac.ir/article-18-10998-en.pdf |
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