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Predicting failure in the U.S. banking sector: An extreme gradient boosting approach

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Cited by:

  1. Citterio, Alberto & King, Timothy, 2023. "The role of Environmental, Social, and Governance (ESG) in predicting bank financial distress," Finance Research Letters, Elsevier, vol. 51(C).
  2. Khudri, Md Mohsan & Hussey, Andrew, 2024. "Breastfeeding and Child Development Outcomes across Early Childhood and Adolescence: Doubly Robust Estimation with Machine Learning," IZA Discussion Papers 17080, Institute of Labor Economics (IZA).
  3. Buckmann, Marcus & Gallego Marquez, Paula & Gimpelewicz, Mariana & Kapadia, Sujit & Rismanchi, Katie, 2023. "The more the merrier? Evidence on the value of multiple requirements in bank regulation," Journal of Banking & Finance, Elsevier, vol. 149(C).
  4. Matthew Harding & Gabriel F. R. Vasconcelos, 2022. "Managers versus Machines: Do Algorithms Replicate Human Intuition in Credit Ratings?," Papers 2202.04218, arXiv.org.
  5. Citterio, Alberto, 2024. "Bank failure prediction models: Review and outlook," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
  6. Carmona, Pedro & Dwekat, Aladdin & Mardawi, Zeena, 2022. "No more black boxes! Explaining the predictions of a machine learning XGBoost classifier algorithm in business failure," Research in International Business and Finance, Elsevier, vol. 61(C).
  7. Ismail, I. & Stam, P.J.A. & Portrait, F.R.M. & van Witteloostuijn, A. & Koolman, X., 2024. "Addressing unanticipated interactions in risk equalization: A machine learning approach to modeling medical expenditure risk," Economic Modelling, Elsevier, vol. 130(C).
  8. Zhang, Xuan & Zhao, Yang & Yao, Xiao, 2022. "Forecasting corporate default risk in China," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1054-1070.
  9. Evžen Kočenda & Ichiro Iwasaki, 2022. "Bank survival around the world: A meta‐analytic review," Journal of Economic Surveys, Wiley Blackwell, vol. 36(1), pages 108-156, February.
  10. Silviu-IonuÈ› BÄ‚BÈšAN, 2024. "AUTOMATED EVALUATION MODELS in real estate market: A comparative analysis between linear regression and XGBoost," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 2(26), pages 1-3.
  11. Kočenda, Evžen & Iwasaki, Ichiro, 2020. "Bank survival in Central and Eastern Europe," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 860-878.
  12. 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).
  13. 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.
  14. Jakub Horak, 2021. "Sanctions as a Catalyst for Russia’s and China’s Balance of Trade: Business Opportunity," JRFM, MDPI, vol. 14(1), pages 1-26, January.
  15. Daria S. Leonteva, 2022. "Using Market Indicators to Refine Estimates of Corporate Bankruptcy Probabilities," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 6, pages 74-90, December.
  16. Xi, Haomeng & Wang, Jizhou, 2024. "Social governance, family happiness, and financial inclusion," Finance Research Letters, Elsevier, vol. 61(C).
  17. Bluwstein, Kristina & Buckmann, Marcus & Joseph, Andreas & Kapadia, Sujit & Şimşek, Özgür, 2023. "Credit growth, the yield curve and financial crisis prediction: Evidence from a machine learning approach," Journal of International Economics, Elsevier, vol. 145(C).
  18. Alexander Ryota Keeley & Ken’ichi Matsumoto & Kenta Tanaka & Yogi Sugiawan & Shunsuke Managi, 2021. "The Impact of Renewable Energy Generation on the Spot Market Price in Germany: Ex-Post Analysis using Boosting Method," The Energy Journal, , vol. 42(1_suppl), pages 1-22, June.
  19. 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.
  20. Ren, Tingting & Li, Shaofang & Zhang, Siying, 2024. "Stock market extreme risk prediction based on machine learning: Evidence from the American market," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
  21. Cohen, Gil & Aiche, Avishay, 2023. "Forecasting gold price using machine learning methodologies," Chaos, Solitons & Fractals, Elsevier, vol. 175(P2).
  22. Resce, Giuliano & Vaquero-Piñeiro, Cristina, 2022. "Predicting agri-food quality across space: A Machine Learning model for the acknowledgment of Geographical Indications," Food Policy, Elsevier, vol. 112(C).
  23. Delogu, Marco & Lagravinese, Raffaele & Paolini, Dimitri & Resce, Giuliano, 2024. "Predicting dropout from higher education: Evidence from Italy," Economic Modelling, Elsevier, vol. 130(C).
  24. Samuel Opoku & Kingsley Opoku Appiah & Prince Gyimah, 2024. "Can We Predict the Financial Distress of Banks in Sub-Saharan Africa?," SAGE Open, , vol. 14(3), pages 21582440241, August.
  25. Li, Jing & Li, Nan & Xia, Tongshui & Guo, Jinjin, 2023. "Textual analysis and detection of financial fraud: Evidence from Chinese manufacturing firms," Economic Modelling, Elsevier, vol. 126(C).
  26. Zhao, Shuping & Xu, Kai & Wang, Zhao & Liang, Changyong & Lu, Wenxing & Chen, Bo, 2022. "Financial distress prediction by combining sentiment tone features," Economic Modelling, Elsevier, vol. 106(C).
  27. Enes Gul & Efthymia Staiou & Mir Jafar Sadegh Safari & Babak Vaheddoost, 2023. "Enhancing Meteorological Drought Modeling Accuracy Using Hybrid Boost Regression Models: A Case Study from the Aegean Region, Türkiye," Sustainability, MDPI, vol. 15(15), pages 1-17, July.
  28. Ionuț Nica & Daniela Blană Alexandru & Simona Liliana Paramon Crăciunescu & Ștefan Ionescu, 2021. "Automated Valuation Modelling: Analysing Mortgage Behavioural Life Profile Models Using Machine Learning Techniques," Sustainability, MDPI, vol. 13(9), pages 1-27, May.
  29. Sami Ben Jabeur & Nicolae Stef & Pedro Carmona, 2023. "Bankruptcy Prediction using the XGBoost Algorithm and Variable Importance Feature Engineering," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 715-741, February.
  30. 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.
  31. 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.
  32. Daniel Boos & Nikolaos Karampatsas & Wolfgang Garn & Lampros K. Stergioulas, 2024. "Predicting corporate restructuring and financial distress in banks: The case of the Swiss banking industry," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 47(2), pages 497-533, June.
  33. 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.
  34. Wookjae Heo & Eunchan Kim & Eun Jin Kwak & John E. Grable, 2024. "Identifying Hidden Factors Associated with Household Emergency Fund Holdings: A Machine Learning Application," Mathematics, MDPI, vol. 12(2), pages 1-38, January.
  35. Changju Lee & Sunghoon Lee, 2022. "Exploring the Contributions by Transportation Features to Urban Economy: An Experiment of a Scalable Tree-Boosting Algorithm with Big Data," Land, MDPI, vol. 11(4), pages 1-30, April.
  36. de Haan, Jakob & Fang, Yi & Jing, Zhongbo, 2020. "Does the risk on banks’ balance sheets predict banking crises? New evidence for developing countries," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 254-268.
  37. 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).
  38. Meng‐Feng Yen & Yu‐Pei Huang & Liang‐Chih Yu & Yueh‐Ling Chen, 2022. "A Two-Dimensional Sentiment Analysis of Online Public Opinion and Future Financial Performance of Publicly Listed Companies," Computational Economics, Springer;Society for Computational Economics, vol. 59(4), pages 1677-1698, April.
  39. Shimomura, Mizue & Keeley, Alexander Ryota & Matsumoto, Ken'ichi & Tanaka, Kenta & Managi, Shunsuke, 2024. "Beyond the merit order effect: Impact of the rapid expansion of renewable energy on electricity market price," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
  40. Aykut Ekinci & Safa Sen, 2024. "Forecasting Bank Failure in the U.S.: A Cost-Sensitive Approach," Computational Economics, Springer;Society for Computational Economics, vol. 64(6), pages 3161-3179, December.
  41. Alanis, Emmanuel, 2020. "Is there valuable private information in credit ratings?," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
  42. Jabeur, Sami Ben & Gharib, Cheima & Mefteh-Wali, Salma & Arfi, Wissal Ben, 2021. "CatBoost model and artificial intelligence techniques for corporate failure prediction," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
  43. Herrera, Rubén & Climent, Francisco & Carmona, Pedro & Momparler, Alexandre, 2022. "The manipulation of Euribor: An analysis with machine learning classification techniques," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
  44. Cebula, Richard J. & Xu, Jiay, 2023. "A Brief Survey of Recent Studies of Bank Failures in the U.S," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 76(2), pages 265-274.
  45. Aleksandra Ostrowska, 2023. "Makroekonomiczne determinanty jakości kredytów dla sektora niefinansowego w Polsce," Bank i Kredyt, Narodowy Bank Polski, vol. 54(5), pages 541-556.
  46. Li Yao & He Ni, 2023. "Prediction of patent grant and interpreting the key determinants: an application of interpretable machine learning approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(9), pages 4933-4969, September.
  47. Buckmann, Marcus & Gallego Marquez, Paula & Gimpelewicz, Mariana & Kapadia, Sujit & Rismanchi, Katie, 2021. "The more the merrier? Evidence from the global financial crisis on the value of multiple requirements in bank regulation," Bank of England working papers 905, Bank of England.
  48. 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.
  49. 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.
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