Predicting US banks bankruptcy: logit versus Canonical Discriminant analysis
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- Zeineb Affes & Rania Hentati-Kaffel, 2016. "Predicting US banks bankruptcy: logit versus Canonical Discriminant analysis," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01281948, HAL.
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- Elena Gregova & Katarina Valaskova & Peter Adamko & Milos Tumpach & Jaroslav Jaros, 2020. "Predicting Financial Distress of Slovak Enterprises: Comparison of Selected Traditional and Learning Algorithms Methods," Sustainability, MDPI, vol. 12(10), pages 1-17, May.
- Youssef Zizi & Amine Jamali-Alaoui & Badreddine El Goumi & Mohamed Oudgou & Abdeslam El Moudden, 2021. "An Optimal Model of Financial Distress Prediction: A Comparative Study between Neural Networks and Logistic Regression," Risks, MDPI, vol. 9(11), pages 1-24, November.
- Zeineb Affes & Rania Hentati-Kaffel, 2016. "Forecast bankruptcy using a blend of clustering and MARS model - Case of US banks," Post-Print halshs-01314553, HAL.
- O. Vasiurenko & V. LYASHENKO, 2020. "Wavelet coherence as a tool for retrospective analysis of bank activities," Economy and Forecasting, Valeriy Heyets, issue 2, pages 43-60.
- Youssef Zizi & Mohamed Oudgou & Abdeslam El Moudden, 2020. "Determinants and Predictors of SMEs’ Financial Failure: A Logistic Regression Approach," Risks, MDPI, vol. 8(4), pages 1-21, October.
- Magdalena Brygała, 2022. "Consumer Bankruptcy Prediction Using Balanced and Imbalanced Data," Risks, MDPI, vol. 10(2), pages 1-13, January.
- Zeineb Affes & Rania Hentati-Kaffel, 2016. "Forecast bankruptcy using a blend of clustering and MARS model - Case of US banks," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01314553, HAL.
- Zeineb Affes & Rania Hentati-Kaffel, 2016. "Forecast bankruptcy using a blend of clustering and MARS model - Case of US banks," Documents de travail du Centre d'Economie de la Sorbonne 16026, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
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More about this item
Keywords
Bankruptcy prediction; Canonical Discriminant Analysis; Logistic regression; CAMELS; ROC curve; Early-warning system;All these keywords.
JEL classification:
- G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
- G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
- C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
NEP fields
This paper has been announced in the following NEP Reports:- NEP-BAN-2016-03-23 (Banking)
- NEP-DCM-2016-03-23 (Discrete Choice Models)
- NEP-FOR-2016-03-23 (Forecasting)
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