A Firms' Bankruptcy Prediction Model Based on Selected Industries by Using Decision Trees Model
Investors are always looking for information about their investment choices to have a favorable investment and an optimized allocation of their resources. Bankruptcy prediction of the firm is one of the most important subjects that can help investors in this way. Many studies have been done in the f...
| Main Authors: | , , |
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| Format: | Article |
| Language: | fas |
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University of Isfahan
2018-06-01
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| Series: | Journal of Asset Management and Financing |
| Subjects: | |
| Online Access: | https://amf.ui.ac.ir/article_21355_461f9bf4be2914d6db4a90deda5441e5.pdf |
| Summary: | Investors are always looking for information about their investment choices to have a favorable investment and an optimized allocation of their resources. Bankruptcy prediction of the firm is one of the most important subjects that can help investors in this way. Many studies have been done in the field of bankruptcy prediction. However, the majority of them provide a general model for all industries as a unit. The main objective of this study is presenting a bankruptcy prediction model, specific for each industry, for three industries including automobile and parts manufacturing, chemical products, and Food, except for sugar products, using decision trees model. To determine bankruptcy of the firm we used the criteria of Article 141 in Commercial Code. This research was performed from 2002 to 2014. The results show that the designed model has a prediction accuracy of 95.95, 96.83 and 97.83 percent for automobile and parts manufacturing industry, chemical products industry, and Food, except for sugar products industry, respectively. These findings reflect high accuracy of these three models, especially for Food, except for sugar products industry. |
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| ISSN: | 2383-1189 2383-1189 |