Corporate default prediction with industry effects: evidence from emerging markets
The accurate prediction of corporate bankruptcy for the firms in different industries is of a great concern to investors and creditors. Firm-specific data accompany with industry and macroeconomic factors offer a potentially large number of candidate predictors of corporate default. We employ a pred...
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| Format: | Article |
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Econjournals
2016
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| _version_ | 1796861643609604096 |
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| author | Mirzaei, Maryam Ramakrishnan, Suresh Bekri, Mahmoud |
| author_facet | Mirzaei, Maryam Ramakrishnan, Suresh Bekri, Mahmoud |
| author_sort | Mirzaei, Maryam |
| collection | ePrints |
| description | The accurate prediction of corporate bankruptcy for the firms in different industries is of a great concern to investors and creditors. Firm-specific data accompany with industry and macroeconomic factors offer a potentially large number of candidate predictors of corporate default. We employ a predictor selection procedure based on non-parametric regression and classification tree method (CART) and test its performance within a standard logistic regression model. Overall entire analyses indicate that the orientation between firm-level determinants and the probability of default is affected by each industry’s characteristics. As well, our selection method represents an efficient way of introducing non-linear effects of predictor variables on the default probability. |
| first_indexed | 2024-03-05T19:59:31Z |
| format | Article |
| id | utm.eprints-69095 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T19:59:31Z |
| publishDate | 2016 |
| publisher | Econjournals |
| record_format | dspace |
| spelling | utm.eprints-690952017-11-20T08:52:14Z http://eprints.utm.my/69095/ Corporate default prediction with industry effects: evidence from emerging markets Mirzaei, Maryam Ramakrishnan, Suresh Bekri, Mahmoud QA Mathematics The accurate prediction of corporate bankruptcy for the firms in different industries is of a great concern to investors and creditors. Firm-specific data accompany with industry and macroeconomic factors offer a potentially large number of candidate predictors of corporate default. We employ a predictor selection procedure based on non-parametric regression and classification tree method (CART) and test its performance within a standard logistic regression model. Overall entire analyses indicate that the orientation between firm-level determinants and the probability of default is affected by each industry’s characteristics. As well, our selection method represents an efficient way of introducing non-linear effects of predictor variables on the default probability. Econjournals 2016 Article PeerReviewed Mirzaei, Maryam and Ramakrishnan, Suresh and Bekri, Mahmoud (2016) Corporate default prediction with industry effects: evidence from emerging markets. International Journal of Economics and Financial Issues, 6 (3). pp. 161-169. ISSN 2146-4138 http://www.scopus.com |
| spellingShingle | QA Mathematics Mirzaei, Maryam Ramakrishnan, Suresh Bekri, Mahmoud Corporate default prediction with industry effects: evidence from emerging markets |
| title | Corporate default prediction with industry effects: evidence from emerging markets |
| title_full | Corporate default prediction with industry effects: evidence from emerging markets |
| title_fullStr | Corporate default prediction with industry effects: evidence from emerging markets |
| title_full_unstemmed | Corporate default prediction with industry effects: evidence from emerging markets |
| title_short | Corporate default prediction with industry effects: evidence from emerging markets |
| title_sort | corporate default prediction with industry effects evidence from emerging markets |
| topic | QA Mathematics |
| work_keys_str_mv | AT mirzaeimaryam corporatedefaultpredictionwithindustryeffectsevidencefromemergingmarkets AT ramakrishnansuresh corporatedefaultpredictionwithindustryeffectsevidencefromemergingmarkets AT bekrimahmoud corporatedefaultpredictionwithindustryeffectsevidencefromemergingmarkets |