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Article Information:
A Multi-industry Default Prediction Model using Logistic Regression and Decision Tree
Suresh Ramakrishnan, Maryam Mirzaei and Mahmoud Bekri
Corresponding Author: Maryam Mirzaei
Submitted: November 19, 2014
Accepted: January 8, 2015
Published: April 05, 2015 |
Abstract:
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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.
Key words: Decision tree, default prediction, industry effects, logistic regression, , ,
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Cite this Reference:
Suresh Ramakrishnan, Maryam Mirzaei and Mahmoud Bekri, . A Multi-industry Default Prediction Model using Logistic Regression and Decision Tree . Research Journal of Applied Sciences, Engineering and Technology, (10): 856-861.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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