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Does machine learning help us predict banking crises?
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Cited by:
- Chris Reimann, 2024. "Predicting financial crises: an evaluation of machine learning algorithms and model explainability for early warning systems," Review of Evolutionary Political Economy, Springer, vol. 5(1), pages 51-83, June.
- Grodecka-Messi, Anna & Kenny, Seán & Ögren, Anders, 2021.
"Predictors of bank distress: The 1907 crisis in Sweden,"
Explorations in Economic History, Elsevier, vol. 80(C).
- Grodecka, Anna & Kenny, Seán & Ögren, Anders, 2018. "Predictors of Bank Distress: The 1907 Crisis in Sweden," Lund Papers in Economic History 180, Lund University, Department of Economic History.
- Grodecka, Anna & Kenny, Seán & Ögren, Anders, 2018. "Predictors of Bank Distress:The 1907 Crisis in Sweden," Working Paper Series 358, Sveriges Riksbank (Central Bank of Sweden).
- Beutel, Johannes & Metiu, Norbert & Stockerl, Valentin, 2021.
"Toothless tiger with claws? Financial stability communication, expectations, and risk-taking,"
Journal of Monetary Economics, Elsevier, vol. 120(C), pages 53-69.
- Beutel, Johannes & Metiu, Norbert & Stockerl, Valentin, 2021. "Toothless tiger with claws? Financial stability communication, expectations, and risk-taking," Discussion Papers 05/2021, Deutsche Bundesbank.
- Casabianca, Elizabeth Jane & Catalano, Michele & Forni, Lorenzo & Giarda, Elena & Passeri, Simone, 2022.
"A machine learning approach to rank the determinants of banking crises over time and across countries,"
Journal of International Money and Finance, Elsevier, vol. 129(C).
- Elizabeth Jane Casabianca & Michele Catalano & Lorenzo Forni & Elena Giarda & Simone Passeri, 2019. "An Early Warning System for banking crises: From regression-based analysis to machine learning techniques," "Marco Fanno" Working Papers 0235, Dipartimento di Scienze Economiche "Marco Fanno".
- Hartwig, Benny & Meinerding, Christoph & Schüler, Yves S., 2021.
"Identifying indicators of systemic risk,"
Journal of International Economics, Elsevier, vol. 132(C).
- Hartwig, Benny & Meinerding, Christoph & Schüler, Yves, 2020. "Identifying indicators of systemic risk," Discussion Papers 33/2020, Deutsche Bundesbank.
- João Gabriel Moraes Souza & Daniel Tavares Castro & Yaohao Peng & Ivan Ricardo Gartner, 2024. "A Machine Learning-Based Analysis on the Causality of Financial Stress in Banking Institutions," Computational Economics, Springer;Society for Computational Economics, vol. 64(3), pages 1857-1890, September.
- Pham, Xuan T.T. & Ho, Tin H., 2021. "Using boosting algorithms to predict bank failure: An untold story," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 40-54.
- Ponomarenko, Alexey & Tatarintsev, Stas, 2023.
"Incorporating financial development indicators into early warning systems,"
The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
- Alexey Ponomarenko & Stas Tatarintsev, 2020. "Incorporating financial development indicators into early warning systems," Bank of Russia Working Paper Series wps58, Bank of Russia.
- Tölö, Eero, 2020. "Predicting systemic financial crises with recurrent neural networks," Journal of Financial Stability, Elsevier, vol. 49(C).
- Huynh, Tran & Uebelmesser, Silke, 2024.
"Early warning models for systemic banking crises: Can political indicators improve prediction?,"
European Journal of Political Economy, Elsevier, vol. 81(C).
- Tran Huynh & Silke Uebelmesser, 2022. "Early warning models for systemic banking crises: can political indicators improve prediction?," Jena Economics Research Papers 2022-007, Friedrich-Schiller-University Jena.
- Ellis, Scott & Sharma, Satish & Brzeszczyński, Janusz, 2022. "Systemic risk measures and regulatory challenges," Journal of Financial Stability, Elsevier, vol. 61(C).
- Wang, Peiwan & Zong, Lu, 2023. "Does machine learning help private sectors to alarm crises? Evidence from China’s currency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).
- Nakatani, Ryota, 2020.
"Macroprudential policy and the probability of a banking crisis,"
Journal of Policy Modeling, Elsevier, vol. 42(6), pages 1169-1186.
- Nakatani, Ryota, 2020. "Macroprudential Policy and the Probability of a Banking Crisis," MPRA Paper 101157, University Library of Munich, Germany.
- 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.
- Bui, Dien Giau & Chen, Yan-Shing & Hsu, Hsing-Hua & Lin, Chih-Yung, 2020. "Labor unions and bank risk culture: evidence from the financial crisis," Journal of Financial Stability, Elsevier, vol. 51(C).
- Susanna Levantesi & Gabriella Piscopo, 2020. "The Importance of Economic Variables on London Real Estate Market: A Random Forest Approach," Risks, MDPI, vol. 8(4), pages 1-17, October.
- Truong, Chi & Sheen, Jeffrey & Trück, Stefan & Villafuerte, James, 2022. "Early warning systems using dynamic factor models: An application to Asian economies," Journal of Financial Stability, Elsevier, vol. 58(C).
- Evangelos Liaras & Michail Nerantzidis & Antonios Alexandridis, 2024. "Machine learning in accounting and finance research: a literature review," Review of Quantitative Finance and Accounting, Springer, vol. 63(4), pages 1431-1471, November.
- Metiu, Norbert, 2022. "A composite indicator of financial conditions for Germany," Technical Papers 03/2022, Deutsche Bundesbank.
- Antulov-Fantulin, Nino & Lagravinese, Raffaele & Resce, Giuliano, 2021. "Predicting bankruptcy of local government: A machine learning approach," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 681-699.
- Sreenivasulu Puli & Nagaraju Thota & A. C. V. Subrahmanyam, 2024. "Assessing Machine Learning Techniques for Predicting Banking Crises in India," JRFM, MDPI, vol. 17(4), pages 1-16, March.
- Solomon Y. Deku & Alper Kara & Artur Semeyutin, 2021. "The predictive strength of MBS yield spreads during asset bubbles," Review of Quantitative Finance and Accounting, Springer, vol. 56(1), pages 111-142, January.
- Hristov, Nikolay & Roth, Markus, 2022. "Uncertainty shocks and systemic-risk indicators," Journal of International Money and Finance, Elsevier, vol. 122(C).
- Mauro Paoloni & Massimiliano Celli, 2023. "The Covid-19 Pandemic and the Eurozone: A Reconnaissance of E.U. Financial Assistance to Counteract the Coronavirus’s Perfect Storm," International Journal of Business and Management, Canadian Center of Science and Education, vol. 16(7), pages 1-72, February.
- Leonard Sabetti & Ronald Heijmans, 2020. "Shallow or deep? Detecting anomalous flows in the Canadian Automated Clearing and Settlement System using an autoencoder," Working Papers 681, DNB.
- Chau, Michael & Lin, Chih-Yung & Lin, Tse-Chun, 2020. "Wisdom of crowds before the 2007–2009 global financial crisis," Journal of Financial Stability, Elsevier, vol. 48(C).
- Bitetto, Alessandro & Cerchiello, Paola & Mertzanis, Charilaos, 2023. "On the efficient synthesis of short financial time series: A Dynamic Factor Model approach," Finance Research Letters, Elsevier, vol. 53(C).
- Ademmer, Martin & Beckmann, Joscha & Bode, Eckhardt & Boysen-Hogrefe, Jens & Funke, Manuel & Hauber, Philipp & Heidland, Tobias & Hinz, Julian & Jannsen, Nils & Kooths, Stefan & Söder, Mareike & Stame, 2021. "Big Data in der makroökonomischen Analyse," Kieler Beiträge zur Wirtschaftspolitik 32, Kiel Institute for the World Economy (IfW Kiel).
- 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.
- Zongxin Zhang & Ying Chen, 2022. "Tail Risk Early Warning System for Capital Markets Based on Machine Learning Algorithms," Computational Economics, Springer;Society for Computational Economics, vol. 60(3), pages 901-923, 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).
- Lanbiao Liu & Chen Chen & Bo Wang, 2022. "Predicting financial crises with machine learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 871-910, August.
- Magnus Saß, 2024. "Detecting excessive credit growth: An approach based on structural counterfactuals," Berlin School of Economics Discussion Papers 0046, Berlin School of Economics.
- du Plessis, Emile, 2022. "Multinomial modeling methods: Predicting four decades of international banking crises," Economic Systems, Elsevier, vol. 46(2).
- Dichtl, Hubert & Drobetz, Wolfgang & Otto, Tizian, 2023. "Forecasting Stock Market Crashes via Machine Learning," Journal of Financial Stability, Elsevier, vol. 65(C).