An ordinal classification framework for bank failure prediction: Methodology and empirical evidence for US banks
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Abstract
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DOI: 10.1016/j.ejor.2019.09.040
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Citations
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Cited by:
- Citterio, Alberto, 2024. "Bank failure prediction models: Review and outlook," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
- Julio Cezar Soares Silva & Diogo Ferreira de Lima Silva & Luciano Ferreira & Adiel Teixeira de Almeida-Filho, 2022. "A dominance-based rough set approach applied to evaluate the credit risk of sovereign bonds," 4OR, Springer, vol. 20(1), pages 139-164, March.
- Shi, Yong & Qu, Yi & Chen, Zhensong & Mi, Yunlong & Wang, Yunong, 2024. "Improved credit risk prediction based on an integrated graph representation learning approach with graph transformation," European Journal of Operational Research, Elsevier, vol. 315(2), pages 786-801.
- Martyn, Krzysztof & Kadziński, Miłosz, 2023. "Deep preference learning for multiple criteria decision analysis," European Journal of Operational Research, Elsevier, vol. 305(2), pages 781-805.
- Borchert, Philipp & Coussement, Kristof & De Caigny, Arno & De Weerdt, Jochen, 2023. "Extending business failure prediction models with textual website content using deep learning," European Journal of Operational Research, Elsevier, vol. 306(1), pages 348-357.
- Doumpos, Michalis & Zopounidis, Constantin & Gounopoulos, Dimitrios & Platanakis, Emmanouil & Zhang, Wenke, 2023. "Operational research and artificial intelligence methods in banking," European Journal of Operational Research, Elsevier, vol. 306(1), pages 1-16.
- Katsafados, Apostolos G. & Leledakis, George N. & Pyrgiotakis, Emmanouil G. & Androutsopoulos, Ion & Fergadiotis, Manos, 2024.
"Machine learning in bank merger prediction: A text-based approach,"
European Journal of Operational Research, Elsevier, vol. 312(2), pages 783-797.
- Katsafados, Apostolos G. & Leledakis, George N. & Pyrgiotakis, Emmanouil G. & Androutsopoulos, Ion & Fergadiotis, Manos, 2021. "Machine Learning in U.S. Bank Merger Prediction: A Text-Based Approach," MPRA Paper 108272, University Library of Munich, Germany.
- Zhiyong Li & Chen Feng & Ying Tang, 2022. "Bank efficiency and failure prediction: a nonparametric and dynamic model based on data envelopment analysis," Annals of Operations Research, Springer, vol. 315(1), pages 279-315, August.
- Kristóf, Tamás & Virág, Miklós, 2022. "EU-27 bank failure prediction with C5.0 decision trees and deep learning neural networks," Research in International Business and Finance, Elsevier, vol. 61(C).
- Kadziński, Miłosz & Ciomek, Krzysztof, 2021. "Active learning strategies for interactive elicitation of assignment examples for threshold-based multiple criteria sorting," European Journal of Operational Research, Elsevier, vol. 293(2), pages 658-680.
- Filippopoulou, Chryssanthi & Galariotis, Emilios & Spyrou, Spyros, 2020. "An early warning system for predicting systemic banking crises in the Eurozone: A logit regression approach," Journal of Economic Behavior & Organization, Elsevier, vol. 172(C), pages 344-363.
- Salwa Kessioui & Michalis Doumpos & Constantin Zopounidis, 2023. "A Bibliometric Overview of the State-of-the-Art in Bankruptcy Prediction Methods and Applications," World Scientific Book Chapters, in: Emilios Galariotis & Alexandros Garefalakis & Christos Lemonakis & Marios Menexiadis & Constantin Zo (ed.), Governance and Financial Performance Current Trends and Perspectives, chapter 6, pages 123-153, World Scientific Publishing Co. Pte. Ltd..
- Chrysovalantis Gaganis & Panagiota Papadimitri & Fotios Pasiouras & Menelaos Tasiou, 2023. "Social traits and credit card default: a two-stage prediction framework," Annals of Operations Research, Springer, vol. 325(2), pages 1231-1253, June.
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