IDEAS home Printed from https://ideas.repec.org/a/bla/scandj/v120y2018i1p31-62.html
   My bibliography  Save this article

Predicting Banking Crises with Artificial Neural Networks: The Role of Nonlinearity and Heterogeneity

Author

Listed:
  • Kim Ristolainen

Abstract

Studies of the early warning systems (EWSs) for banking crises usually rely on linear classifiers, estimated with international datasets. I construct an EWS based on an artificial neural network (ANN) model, and I also account for regional heterogeneity in order to improve the generalization ability of EWS models. All of the banking crises in my test set are then predictable at a 24‐month horizon, using information from earlier crises. For some countries, estimation with a regional dataset significantly improves the predictions. The ANN outperforms the usual logit regression, assessed by the area under the receiver operating characteristics curve.

Suggested Citation

  • Kim Ristolainen, 2018. "Predicting Banking Crises with Artificial Neural Networks: The Role of Nonlinearity and Heterogeneity," Scandinavian Journal of Economics, Wiley Blackwell, vol. 120(1), pages 31-62, January.
    • Handle: RePEc:bla:scandj:v:120:y:2018:i:1:p:31-62
    DOI: 10.1111/sjoe.12216
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/sjoe.12216
    Download Restriction: no
    File URL: https://libkey.io/10.1111/sjoe.12216?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Carmen M. Reinhart & Kenneth S. Rogoff, 2014. "This Time is Different: A Panoramic View of Eight Centuries of Financial Crises," Annals of Economics and Finance, Society for AEF, vol. 15(2), pages 215-268, November.
    2. Reinhart, Carmen & Rogoff, Kenneth, 2009. "This Time It’s Different: Eight Centuries of Financial Folly-Preface," MPRA Paper 17451, University Library of Munich, Germany.
    3. Carmen M. Reinhart & Graciela L. Kaminsky, 1999. "The Twin Crises: The Causes of Banking and Balance-of-Payments Problems," American Economic Review, American Economic Association, vol. 89(3), pages 473-500, June.
    4. Carmen M. Reinhart & Kenneth S. Rogoff, 2009. "Varieties of Crises and Their Dates," Introductory Chapters, in: This Time Is Different: Eight Centuries of Financial Folly, Princeton University Press.
    5. Reinhart, Carmen & Rogoff, Kenneth, 2009. "This Time It’s Different: Eight Centuries of Financial Folly-Chapter 1," MPRA Paper 17452, University Library of Munich, Germany.
    6. Mr. Axel Schimmelpfennig & Nouriel Roubini & Paolo Manasse, 2003. "Predicting Sovereign Debt Crises," IMF Working Papers 2003/221, International Monetary Fund.
    7. Demirgüç-Kunt, Asli & Detragiache, Enrica, 2005. "Cross-Country Empirical Studies of Systemic Bank Distress: A Survey," National Institute Economic Review, National Institute of Economic and Social Research, vol. 192, pages 68-83, April.
    8. Knedlik, Tobias, 2012. "The European Commission’s Scoreboard of Macroeconomic Imbalances – The Impact of Preferences on an Early Warning System," IWH Discussion Papers 10/2012, Halle Institute for Economic Research (IWH).
    9. Graciela Kaminsky & Saul Lizondo & Carmen M. Reinhart, 1998. "Leading Indicators of Currency Crises," IMF Staff Papers, Palgrave Macmillan, vol. 45(1), pages 1-48, March.
    10. Hoggarth, Glenn & Reis, Ricardo & Saporta, Victoria, 2002. "Costs of banking system instability: Some empirical evidence," Journal of Banking & Finance, Elsevier, vol. 26(5), pages 825-855, May.
    11. Davis, E. Philip & Karim, Dilruba, 2008. "Comparing early warning systems for banking crises," Journal of Financial Stability, Elsevier, vol. 4(2), pages 89-120, June.
    12. Mr. Edward J Frydl, 1999. "The Length and Cost of Banking Crises," IMF Working Papers 1999/030, International Monetary Fund.
    13. Caggiano, Giovanni & Calice, Pietro & Leonida, Leone, 2014. "Early warning systems and systemic banking crises in low income countries: A multinomial logit approach," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 258-269.
    14. E. Davis & Dilruba Karim & Iana Liadze, 2011. "Should multivariate early warning systems for banking crises pool across regions?," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 147(4), pages 693-716, November.
    15. Stein, Roger M., 2005. "The relationship between default prediction and lending profits: Integrating ROC analysis and loan pricing," Journal of Banking & Finance, Elsevier, vol. 29(5), pages 1213-1236, May.
    16. Carmen M. Reinhart & Kenneth S. Rogoff, 2009. "Is the 2007 US Sub-Prime Financial Crisis So Different?: An International Historical Comparison," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 56(3), pages 291-299.
    17. Fioramanti, Marco, 2008. "Predicting sovereign debt crises using artificial neural networks: A comparative approach," Journal of Financial Stability, Elsevier, vol. 4(2), pages 149-164, June.
    18. Khandani, Amir E. & Kim, Adlar J. & Lo, Andrew W., 2010. "Consumer credit-risk models via machine-learning algorithms," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2767-2787, November.
    19. Kaminsky, Graciela L., 2006. "Currency crises: Are they all the same?," Journal of International Money and Finance, Elsevier, vol. 25(3), pages 503-527, April.
    20. Lucia Alessi & Carsten Detken, 2009. "Global liquidity as an early warning indicator for asset price boom/bust cycles," Research Bulletin, European Central Bank, vol. 8, pages 7-9.
    21. Travis J. Berge & Òscar Jordà, 2011. "Evaluating the Classification of Economic Activity into Recessions and Expansions," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(2), pages 246-277, April.
    22. Detken, Carsten & Alessi, Lucia, 2009. "'Real time'early warning indicators for costly asset price boom/bust cycles: a role for global liquidity," Working Paper Series 1039, European Central Bank.
    23. Berg, Andrew & Pattillo, Catherine, 1999. "Predicting currency crises:: The indicators approach and an alternative," Journal of International Money and Finance, Elsevier, vol. 18(4), pages 561-586, August.
    24. Asli Demirgüç-Kunt & Enrica Detragiache, 1998. "The Determinants of Banking Crises in Developing and Developed Countries," IMF Staff Papers, Palgrave Macmillan, vol. 45(1), pages 81-109, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tölö, Eero, 2019. "Predicting systemic financial crises with recurrent neural networks," Bank of Finland Research Discussion Papers 14/2019, Bank of Finland.
    2. Alexandr Patalaha & Maria A. Shchepeleva, 2023. "Bank Crisis Management Policies and the New Instability," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 6, pages 43-60, December.
    3. Dany-Knedlik, Geraldine & Kämpfe, Martina & Knedlik, Tobias, 2021. "The appropriateness of the macroeconomic imbalance procedure for Central and Eastern European Countries," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 48(1), pages 123-139.
    4. Söhnke M. Bartram & Jürgen Branke & Mehrshad Motahari, 2020. "Artificial intelligence in asset management," Working Papers 20202001, Cambridge Judge Business School, University of Cambridge.
    5. Tölö, Eero, 2019. "Predicting systemic financial crises with recurrent neural networks," Research Discussion Papers 14/2019, Bank of Finland.
    6. Maximilian Gobel & Tanya Araújo, 2020. "Indicators of Economic Crises: A Data-Driven Clustering Approach," Working Papers REM 2020/0128, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    7. Tölö, Eero, 2020. "Predicting systemic financial crises with recurrent neural networks," Journal of Financial Stability, Elsevier, vol. 49(C).
    8. repec:zbw:bofrdp:2019_014 is not listed on IDEAS
    9. 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.

    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. Kauko, Karlo, 2014. "How to foresee banking crises? A survey of the empirical literature," Economic Systems, Elsevier, vol. 38(3), pages 289-308.
    2. 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.
    3. Chung‐Hua Shen & Hsing‐Hua Hsu, 2022. "The determinants of Asian banking crises—Application of the panel threshold logit model," International Review of Finance, International Review of Finance Ltd., vol. 22(1), pages 248-277, March.
    4. Tamadonejad, Alireza & Abdul-Majid, Mariani & Rahman, aisyah & jusoh, mansor & Tabandeh, Razieh, 2016. "Early Warning Systems for Banking Crises: Political and Economic Stability," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 50(2), pages 31-38.
    5. Claudio Borio, 2011. "Rediscovering the Macroeconomic Roots of Financial Stability Policy: Journey, Challenges, and a Way Forward," Annual Review of Financial Economics, Annual Reviews, vol. 3(1), pages 87-117, December.
    6. Bjarni G. Einarsson & Kristófer Gunnlaugsson & Thorvardur Tjörvi Ólafsson & Thórarinn G. Pétursson, 2015. "The long history of financial boom-bust cycles in Iceland - Part I: Financial crises," Economics wp68, Department of Economics, Central bank of Iceland.
    7. Xianglong Liu, 2023. "Towards Better Banking Crisis Prediction: Could an Automatic Variable Selection Process Improve the Performance?," The Economic Record, The Economic Society of Australia, vol. 99(325), pages 288-312, June.
    8. Roy, Saktinil & Kemme, David M., 2012. "Causes of banking crises: Deregulation, credit booms and asset bubbles, then and now," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 270-294.
    9. Thanh C. Nguyen & Vítor Castro & Justine Wood, 2022. "Political environment and financial crises," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 417-438, January.
    10. Tölö, Eero, 2020. "Predicting systemic financial crises with recurrent neural networks," Journal of Financial Stability, Elsevier, vol. 49(C).
    11. Jon Danielsson & Marcela Valenzuela & Ilknur Zer, 2018. "Learning from History: Volatility and Financial Crises," The Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2774-2805.
    12. 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.
    13. 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.
    14. Yusuf Yıldırım & Anirban Sanyal, 2022. "Evaluating the Effectiveness of Early Warning Indicators: An Application of Receiver Operating Characteristic Curve Approach to Panel Data," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 69(4), pages 557-597, December.
    15. Mahir Binici & Aytül Ganioglu, 2021. "Net external position, financial development, and banking crisis," Empirical Economics, Springer, vol. 61(3), pages 1225-1251, September.
    16. Jing, Zhongbo & de Haan, Jakob & Jacobs, Jan & Yang, Haizhen, 2015. "Identifying banking crises using money market pressure: New evidence for a large set of countries," Journal of Macroeconomics, Elsevier, vol. 43(C), pages 1-20.
    17. Rakesh Padhan & K. P. Prabheesh, 2019. "Effectiveness Of Early Warning Models: A Critical Review And New Agenda For Future Direction," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 22(4), pages 457-484.
    18. Qin, Xiao & Luo, Chengying, 2014. "Capital account openness and early warning system for banking crises in G20 countries," Economic Modelling, Elsevier, vol. 39(C), pages 190-194.
    19. du Plessis, Emile, 2022. "Multinomial modeling methods: Predicting four decades of international banking crises," Economic Systems, Elsevier, vol. 46(2).
    20. Nguyen, Thanh Cong & Castro, Vítor & Wood, Justine, 2022. "A new comprehensive database of financial crises: Identification, frequency, and duration," Economic Modelling, Elsevier, vol. 108(C).

    More about this item

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

    Statistics

    Access and download statistics

    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:bla:scandj:v:120:y:2018:i:1:p:31-62. 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: Wiley Content Delivery (email available below). General contact details of provider: http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1467-9442 .

    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.