A comparison of corporate distress prediction models in Brazil: hybrid neural networks, logit models and discriminant analysis
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| Formato: | Artículo científico |
| Lenguaje: | es |
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Universidade Federal de Minas Gerais
2005
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| _version_ | 1876441212593897472 |
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| author | Juliana Yim |
| author_facet | Juliana Yim |
| contents | A comparison of corporate distress prediction models in Brazil: hybrid neural networks, logit models and discriminant analysis Juliana Yim Heather Mitchell Economía y Finanzas corporate failures Hybrid neural networks This paper looks at the ability of a relatively new technique, hybrid ANN’s, to predict corporate distress in Brazil. These models are compared with traditional statistical techniques and conventional ANN models. The results suggest that hybrid neural networks outperform all other models in predicting firms in financial distress one year prior to the event. This suggests that for researchers, policymakers and others interested in early warning systems, hybrid networks may be a useful tool for predicting firm failure. 2005 artículo científico 0103-6351 https://www.redalyc.org/articulo.oa?id=400437538003 es http://www.redalyc.org/revista.oa?id=4004 Nova Economia application/pdf Universidade Federal de Minas Gerais Nova Economia (Brasil) Num.1 Vol.15 |
| format | Artículo científico |
| id | redalyc_400437538003 |
| institution | Redalyc |
| language | es |
| publishDate | 2005 |
| publisher | Universidade Federal de Minas Gerais |
| spellingShingle | A comparison of corporate distress prediction models in Brazil: hybrid neural networks, logit models and discriminant analysis Juliana Yim Economía y Finanzas corporate failures Hybrid neural networks A comparison of corporate distress prediction models in Brazil: hybrid neural networks, logit models and discriminant analysis Juliana Yim Heather Mitchell Economía y Finanzas corporate failures Hybrid neural networks This paper looks at the ability of a relatively new technique, hybrid ANN’s, to predict corporate distress in Brazil. These models are compared with traditional statistical techniques and conventional ANN models. The results suggest that hybrid neural networks outperform all other models in predicting firms in financial distress one year prior to the event. This suggests that for researchers, policymakers and others interested in early warning systems, hybrid networks may be a useful tool for predicting firm failure. 2005 artículo científico 0103-6351 https://www.redalyc.org/articulo.oa?id=400437538003 es http://www.redalyc.org/revista.oa?id=4004 Nova Economia application/pdf Universidade Federal de Minas Gerais Nova Economia (Brasil) Num.1 Vol.15 |
| title | A comparison of corporate distress prediction models in Brazil: hybrid neural networks, logit models and discriminant analysis |
| topic | Economía y Finanzas corporate failures Hybrid neural networks |
| url | https://www.redalyc.org/articulo.oa?id=400437538003 |