A comparison of corporate distress prediction models in Brazil: hybrid neural networks, logit models and discriminant analysis
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.
Volume (Year): 15 (2005)
Issue (Month): 1 (January-April)
|Contact details of provider:|| Postal: |
Phone: +55 31 3409-7000
Web page: http://www.face.ufmg.br/
More information through EDIRC
|Order Information:|| Postal: Av. Antonio Carlos, 6627 - Predio da FACE Belo Horizonte, 31270-901 Brazil|
Web: http://www.face.ufmg.br/novaeconomia/ Email:
When requesting a correction, please mention this item's handle: RePEc:nov:artigo:v:15:y:2005:i:1:p:73-93. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sibelle Diniz)
If references are entirely missing, you can add them using this form.