A multi-industry default prediction model using logistic regression and decision tree
The accurate prediction of corporate bankruptcy for the firms in different industries is of a great concern to investors and creditors, as the reduction of creditors' risk and a considerable amount of saving for an industry economy can be possible. Financial statements vary between industries....
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| Main Authors: | , , |
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| Format: | Article |
| Published: |
Maxwell Science Publications
2015
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/55704/ http://www.maxwellsci.com/jp/abstract.php?jid=RJASET&no=535&abs=10 |
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| Institution: | Universiti Teknologi Malaysia |
| Summary: | The accurate prediction of corporate bankruptcy for the firms in different industries is of a great concern to investors and creditors, as the reduction of creditors' risk and a considerable amount of saving for an industry economy can be possible. Financial statements vary between industries. Therefore, economic intuition suggests that industry effects should be an important component in bankruptcy prediction. This study attempts to detail the characteristics of each industry using sector indicators. The results show significant relationship between probability of default and sector indicators. The results of this study may improve the default prediction models performance and reduce the costs of risk management. |
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