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Forecasting bank failures and stress testing: A machine learning approach
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- Jean-Armand Gnagne & Kevin Moran, 2020. "Forecasting Bank Failures in a Data-Rich Environment," Working Papers 20-13, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
- Plakandaras, Vasilios & Gogas, Periklis & Papadimitriou, Theophilos & Gupta, Rangan, 2019. "A re-evaluation of the term spread as a leading indicator," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 476-492.
- Andrés Giovanni Camacho Ardila & Federico Hernández Álvarez & Luis Ignacio Román de la Sancha, 2023. "Ciclos en el Sector Bancario Mexicano: un Índice Coincidente (CP1G7) vía ACP," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 18(4), pages 1-25, Octubre -.
- Kea BARET, 2021. "Fiscal rules’ compliance and Social Welfare," Working Papers of BETA 2021-38, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
- Małgorzata Iwanicz-Drozdowska & Krzysztof Jackowicz & Maciej Karczmarczyk, 2021. "“The Crooked Smile of TCR†: Banks’ Solvency and Restructuring Costs in the European Banking Industry," SAGE Open, , vol. 11(3), pages 21582440211, September.
- Yi Cao & Xiaoquan Liu & Jia Zhai & Shan Hua, 2022. "A two‐stage Bayesian network model for corporate bankruptcy prediction," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 455-472, January.
- Theophilos Papadimitriou & Periklis Gogas & Anna Agrapetidou, 2022. "The resilience of the U.S. banking system," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 2819-2835, July.
- Kea BARET & Theophilos PAPADIMITRIOU, 2019. "On the Stability and Growth Pact compliance: what is predictable with machine learning?," Working Papers of BETA 2019-48, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
- Marcus Buckmann & Andy Haldane & Anne-Caroline Hüser, 2021.
"Comparing minds and machines: implications for financial stability,"
Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 37(3), pages 479-508.
- Buckmann, Marcus & Haldane, Andy & Hüser, Anne-Caroline, 2021. "Comparing minds and machines: implications for financial stability," Bank of England working papers 937, Bank of England.
- 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.
- Anton Gerunov, 2023. "Modern Approaches To Forecasting Firm Default Rates Over The Short To Medium Term: An Application To A Panel Of Polish Companies," Yearbook of the Faculty of Economics and Business Administration, Sofia University, Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski - Bulgaria, vol. 22(1), pages 5-15, October.
- Manthoulis, Georgios & Doumpos, Michalis & Zopounidis, Constantin & Galariotis, Emilios, 2020. "An ordinal classification framework for bank failure prediction: Methodology and empirical evidence for US banks," European Journal of Operational Research, Elsevier, vol. 282(2), pages 786-801.
- Veganzones, David & Séverin, Eric & Chlibi, Souhir, 2023. "Influence of earnings management on forecasting corporate failure," International Journal of Forecasting, Elsevier, vol. 39(1), pages 123-143.
- Polyzos, Stathis & Samitas, Aristeidis & Katsaiti, Marina-Selini, 2020. "Who is unhappy for Brexit? A machine-learning, agent-based study on financial instability," International Review of Financial Analysis, Elsevier, vol. 72(C).
- Cullen F. Goenner, 2020. "Uncertain times and early predictions of bank failure," The Financial Review, Eastern Finance Association, vol. 55(4), pages 583-601, November.
- Caifeng Liu & Wenfeng Pan & Hongcheng Zhou, 2023. "RCML: A Novel Algorithm for Regressing Price Movement during Commodity Futures Stress Testing Based on Machine Learning," JRFM, MDPI, vol. 16(6), pages 1-12, May.
- Petropoulos, Anastasios & Siakoulis, Vasilis & Stavroulakis, Evangelos & Vlachogiannakis, Nikolaos E., 2020. "Predicting bank insolvencies using machine learning techniques," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1092-1113.
- Citterio, Alberto, 2024. "Bank failure prediction models: Review and outlook," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
- Katsafados, Apostolos G. & Androutsopoulos, Ion & Chalkidis, Ilias & Fergadiotis, Manos & Leledakis, George N. & Pyrgiotakis, Emmanouil G., 2020. "Textual Information and IPO Underpricing: A Machine Learning Approach," MPRA Paper 103813, University Library of Munich, Germany.
- Periklis Gogas & Theophilos Papadimitriou & Maria-Artemis Matthaiou, 2022. "Supervision of Banking Networks Using the Multivariate Threshold-Minimum Dominating Set (mT-MDS)," JRFM, MDPI, vol. 15(6), pages 1-13, June.
- Jean Armand Gnagne & Kevin Moran, 2018. "Monitoring Bank Failures in a Data-Rich Environment," Cahiers de recherche 1815, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
- Bracke, Philippe & Datta, Anupam & Jung, Carsten & Sen, Shayak, 2019. "Machine learning explainability in finance: an application to default risk analysis," Bank of England working papers 816, Bank of England.
- Li Xian Liu & Shuangzhe Liu & Milind Sathye, 2021. "Predicting Bank Failures: A Synthesis of Literature and Directions for Future Research," JRFM, MDPI, vol. 14(10), pages 1-24, October.
- 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).
- Samitas, Aristeidis & Kampouris, Elias & Kenourgios, Dimitris, 2020. "Machine learning as an early warning system to predict financial crisis," International Review of Financial Analysis, Elsevier, vol. 71(C).
- Suss, Joel & Treitel, Henry, 2019. "Predicting bank distress in the UK with machine learning," Bank of England working papers 831, Bank of England.
- Wang, Gang-Jin & Chen, Yan & Zhu, You & Xie, Chi, 2024. "Systemic risk prediction using machine learning: Does network connectedness help prediction?," International Review of Financial Analysis, Elsevier, vol. 93(C).