Early warning models against bankruptcy risk for Central European and Latin American enterprises
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DOI: 10.1016/j.econmod.2012.11.017
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- Carlos Serrano-Cinca, 1997. "Feedforward neural networks in the classification of financial information," The European Journal of Finance, Taylor & Francis Journals, vol. 3(3), pages 183-202.
- J. C. Neves & A. Vieira, 2006. "Improving bankruptcy prediction with Hidden Layer Learning Vector Quantization," European Accounting Review, Taylor & Francis Journals, vol. 15(2), pages 253-271.
- Zhang, Guoqiang & Y. Hu, Michael & Eddy Patuwo, B. & C. Indro, Daniel, 1999. "Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis," European Journal of Operational Research, Elsevier, vol. 116(1), pages 16-32, July.
- Teija Laitinen & Maria Kankaanpaa, 1999. "Comparative analysis of failure prediction methods: the Finnish case," European Accounting Review, Taylor & Francis Journals, vol. 8(1), pages 67-92.
- Riyaz Sikora & Michael Shaw, 1994. "A Double-Layered Learning Approach to Acquiring Rules for Classification: Integrating Genetic Algorithms with Similarity-Based Learning," INFORMS Journal on Computing, INFORMS, vol. 6(2), pages 174-187, May.
- Chris Charalambous & Andreas Charitou & Froso Kaourou, 2000. "Comparative Analysis of Artificial Neural Network Models: Application in Bankruptcy Prediction," Annals of Operations Research, Springer, vol. 99(1), pages 403-425, December.
- Edward I. Altman & Gabriele Sabato, 2013.
"MODELING CREDIT RISK FOR SMEs: EVIDENCE FROM THE US MARKET,"
World Scientific Book Chapters, in: Oliviero Roggi & Edward I Altman (ed.), Managing and Measuring Risk Emerging Global Standards and Regulations After the Financial Crisis, chapter 9, pages 251-279,
World Scientific Publishing Co. Pte. Ltd..
- Edward I. Altman & Gabriele Sabato, 2007. "Modelling Credit Risk for SMEs: Evidence from the U.S. Market," Abacus, Accounting Foundation, University of Sydney, vol. 43(3), pages 332-357, September.
- Edward I Altman & Tara K N Baidya & Luis Manoel Ribeiro Dias, 1979. "Assessing Potential Financial Problems for Firms in Brazil," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 10(2), pages 9-24, June.
- L. Lin & J. Piesse, 2004. "Identification of corporate distress in UK industrials: a conditional probability analysis approach," Applied Financial Economics, Taylor & Francis Journals, vol. 14(2), pages 73-82.
- Arindam Bandyopadhyay, 2006. "Predicting probability of default of Indian corporate bonds: logistic and Z-score model approaches," Journal of Risk Finance, Emerald Group Publishing, vol. 7(3), pages 255-272, May.
- Emel, Ahmet Burak & Oral, Muhittin & Reisman, Arnold & Yolalan, Reha, 2003. "A credit scoring approach for the commercial banking sector," Socio-Economic Planning Sciences, Elsevier, vol. 37(2), pages 103-123, June.
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Keywords
; ; ; ;JEL classification:
- G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
- F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
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