IDEAS home Printed from https://ideas.repec.org/a/eee/intfor/v34y2018i3p440-455.html
   My bibliography  Save this article

Forecasting bank failures and stress testing: A machine learning approach

Author

Listed:
  • Gogas, Periklis
  • Papadimitriou, Theophilos
  • Agrapetidou, Anna

Abstract

This paper presents a forecasting model of bank failures based on machine-learning. The proposed methodology defines a linear decision boundary that separates the solvent banks from those that failed. This setup generates a novel alternative stress-testing tool. Our sample of 1443 U.S. banks includes all 481 banks that failed during the period 2007–2013. The set of explanatory variables is selected using a two-step feature selection procedure. The selected variables were then fed to a support vector machines forecasting model, through a training–testing learning process. The model exhibits a 99.22% overall forecasting accuracy and outperforms the well-established Ohlson’s score.

Suggested Citation

  • Gogas, Periklis & Papadimitriou, Theophilos & Agrapetidou, Anna, 2018. "Forecasting bank failures and stress testing: A machine learning approach," International Journal of Forecasting, Elsevier, vol. 34(3), pages 440-455.
    • Handle: RePEc:eee:intfor:v:34:y:2018:i:3:p:440-455
    DOI: 10.1016/j.ijforecast.2018.01.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0169207018300359
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijforecast.2018.01.009?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Berger, Allen N. & Bouwman, Christa H.S., 2013. "How does capital affect bank performance during financial crises?," Journal of Financial Economics, Elsevier, vol. 109(1), pages 146-176.
    2. Sinkey, Joseph F, Jr, 1975. "A Multivariate Statistical Analysis of the Characteristics of Problem Banks," Journal of Finance, American Finance Association, vol. 30(1), pages 21-36, March.
    3. Rafael Repullo & Javier Suarez, 2013. "The Procyclical Effects of Bank Capital Regulation," The Review of Financial Studies, Society for Financial Studies, vol. 26(2), pages 452-490.
    4. Jon Danielsson & Kevin R. James & Marcela Valenzuela & Ilknur Zer, 2016. "Can We Prove a Bank Guilty of Creating Systemic Risk? A Minority Report," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(4), pages 795-812, June.
    5. Rebel Cole & Lawrence White, 2012. "Déjà Vu All Over Again: The Causes of U.S. Commercial Bank Failures This Time Around," Journal of Financial Services Research, Springer;Western Finance Association, vol. 42(1), pages 5-29, October.
    6. Danielsson, Jon & James, Kevin R. & Valenzuela, Marcela & Zer, Ilknur, 2016. "Model risk of risk models," Journal of Financial Stability, Elsevier, vol. 23(C), pages 79-91.
    7. Theophilos Papadimitriou & Periklis Gogas & Vasilios Plakandaras & John C. Mourmouris, 2013. "Forecasting the insolvency of US banks using support vector machines (SVMs) based on local learning feature selection," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 3(1/2), pages 83-90.
    8. Männasoo, Kadri & Mayes, David G., 2009. "Explaining bank distress in Eastern European transition economies," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 244-253, February.
    9. Martin, Daniel, 1977. "Early warning of bank failure : A logit regression approach," Journal of Banking & Finance, Elsevier, vol. 1(3), pages 249-276, November.
    10. repec:erf:erfstu:78 is not listed on IDEAS
    11. Raymond A.K. Cox & Grace W.-Y. Wang, 2014. "Predicting the US bank failure: A discriminant analysis," Economic Analysis and Policy, Elsevier, vol. 44(2), pages 202-211.
    12. Demyanyk, Yuliya & Hasan, Iftekhar, 2010. "Financial crises and bank failures: A review of prediction methods," Omega, Elsevier, vol. 38(5), pages 315-324, October.
    13. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    14. Rebel Cole & Jeffery Gunther, 1998. "Predicting Bank Failures: A Comparison of On- and Off-Site Monitoring Systems," Journal of Financial Services Research, Springer;Western Finance Association, vol. 13(2), pages 103-117, April.
    15. Kolari, James & Glennon, Dennis & Shin, Hwan & Caputo, Michele, 2002. "Predicting large US commercial bank failures," Journal of Economics and Business, Elsevier, vol. 54(4), pages 361-387.
    16. Curry, Timothy J. & Elmer, Peter J. & Fissel, Gary S., 2007. "Equity market data, bank failures and market efficiency," Journal of Economics and Business, Elsevier, vol. 59(6), pages 536-559.
    17. Arturo Estrella & Sangkyun Park & Stavros Peristiani, 2000. "Capital ratios as predictors of bank failure," Economic Policy Review, Federal Reserve Bank of New York, issue Jul, pages 33-52.
    18. Ravi Kumar, P. & Ravi, V., 2007. "Bankruptcy prediction in banks and firms via statistical and intelligent techniques - A review," European Journal of Operational Research, Elsevier, vol. 180(1), pages 1-28, July.
    19. Gary Whalen, 1991. "A proportional hazards model of bank failure: an examination of its usefulness as an early warning tool," Economic Review, Federal Reserve Bank of Cleveland, vol. 27(Q I), pages 21-31.
    20. Agarwal, Vineet & Taffler, Richard, 2008. "Comparing the performance of market-based and accounting-based bankruptcy prediction models," Journal of Banking & Finance, Elsevier, vol. 32(8), pages 1541-1551, August.
    21. Espahbodi, Pouran, 1991. "Identification of problem banks and binary choice models," Journal of Banking & Finance, Elsevier, vol. 15(1), pages 53-71, February.
    22. David C. Wheelock & Paul W. Wilson, 2000. "Why do Banks Disappear? The Determinants of U.S. Bank Failures and Acquisitions," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 127-138, February.
    23. Cleary, Sean & Hebb, Greg, 2016. "An efficient and functional model for predicting bank distress: In and out of sample evidence," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 101-111.
    24. Altman, Edward I. & Haldeman, Robert G. & Narayanan, P., 1977. "ZETATM analysis A new model to identify bankruptcy risk of corporations," Journal of Banking & Finance, Elsevier, vol. 1(1), pages 29-54, June.
    25. Meyer, Paul A & Pifer, Howard W, 1970. "Prediction of Bank Failures," Journal of Finance, American Finance Association, vol. 25(4), pages 853-868, September.
    26. Shumway, Tyler, 2001. "Forecasting Bankruptcy More Accurately: A Simple Hazard Model," The Journal of Business, University of Chicago Press, vol. 74(1), pages 101-124, January.
    27. James B. Thomson, 1991. "Predicting bank failures in the 1980s," Economic Review, Federal Reserve Bank of Cleveland, vol. 27(Q I), pages 9-20.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Papanikolaou, Nikolaos I., 2018. "To be bailed out or to be left to fail? A dynamic competing risks hazard analysis," Journal of Financial Stability, Elsevier, vol. 34(C), pages 61-85.
    2. Citterio, Alberto, 2024. "Bank failure prediction models: Review and outlook," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    3. repec:erf:erfstu:78 is not listed on IDEAS
    4. Fiordelisi, Franco & Mare, Davide Salvatore, 2013. "Probability of default and efficiency in cooperative banking," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 30-45.
    5. Mare, Davide Salvatore, 2015. "Contribution of macroeconomic factors to the prediction of small bank failures," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 25-39.
    6. Koresh Galil & Margalit Samuel & Offer Moshe Shapir & Wolf Wagner, 2023. "Bailouts and the modeling of bank distress," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 46(1), pages 7-30, February.
    7. Sun, Junjie & Wu, Deming & Zhao, Xinlei, 2018. "Systematic risk factors and bank failures," Journal of Economics and Business, Elsevier, vol. 98(C), pages 1-18.
    8. Cleary, Sean & Hebb, Greg, 2016. "An efficient and functional model for predicting bank distress: In and out of sample evidence," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 101-111.
    9. 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.
    10. Santosh Kumar Shrivastav & P. Janaki Ramudu, 2020. "Bankruptcy Prediction and Stress Quantification Using Support Vector Machine: Evidence from Indian Banks," Risks, MDPI, vol. 8(2), pages 1-22, May.
    11. 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.
    12. Gerhard Hambusch & Sherrill Shaffer, 2016. "Forecasting bank leverage: an alternative to regulatory early warning models," Journal of Regulatory Economics, Springer, vol. 50(1), pages 38-69, August.
    13. Mohammad Mahdi Mousavi & Jamal Ouenniche & Kaoru Tone, 2023. "A dynamic performance evaluation of distress prediction models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 756-784, July.
    14. Gerhard Hambusch & Sherrill Shaffer, 2012. "Forecasting Bank Leverage," Working Paper Series 176, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    15. Colvin, Christopher L. & de Jong, Abe & Fliers, Philip T., 2015. "Predicting the past: Understanding the causes of bank distress in the Netherlands in the 1920s," Explorations in Economic History, Elsevier, vol. 55(C), pages 97-121.
    16. fernández, María t. Tascón & gutiérrez, Francisco J. Castaño, 2012. "Variables y Modelos Para La Identificación y Predicción Del Fracaso Empresarial: Revisión de La Investigación Empírica Reciente," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 15(1), pages 7-58.
    17. Suss, Joel & Treitel, Henry, 2019. "Predicting bank distress in the UK with machine learning," Bank of England working papers 831, Bank of England.
    18. Ken B. Cyree & Travis R. Davidson & John D. Stowe, 2020. "Forming appropriate peer groups for bank research: a cluster analysis of bank financial statements," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 44(2), pages 211-237, April.
    19. Cole, Rebel A. & Wu, Qiongbing, 2009. "Is hazard or probit more accurate in predicting financial distress? Evidence from U.S. bank failures," MPRA Paper 24688, University Library of Munich, Germany, revised 01 Aug 2010.
    20. Fabrizio Ferriani & Wanda Cornacchia & Paolo Farroni & Eliana Ferrara & Francesco Guarino & Francesco Pisanti, 2019. "An early warning system for less significant Italian banks," Questioni di Economia e Finanza (Occasional Papers) 480, Bank of Italy, Economic Research and International Relations Area.
    21. Allen N. Berger & Björn Imbierowicz & Christian Rauch, 2016. "The Roles of Corporate Governance in Bank Failures during the Recent Financial Crisis," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(4), pages 729-770, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:intfor:v:34:y:2018:i:3:p:440-455. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijforecast .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.