IDEAS home Printed from https://ideas.repec.org/a/ukb/journl/y2020i250p33-44.html
   My bibliography  Save this article

Predicting Bank Defaults in Ukraine: A Macro-Micro Perspective

Author

Listed:
  • Anatolii Hlazunov

    (National Bank of Ukraine)

  • Olesia Verchenko

    (Kyiv School of Economics)

Abstract

This paper develops an early warning model (EWM) for a micro-macro analysis of individual and aggregated bank vulnerabilities in Ukraine. We applied a stepwise logit for predicting defaults at Ukrainian banks based on a panel bank and macro-level data from Q1 2009 to Q3 2019. Next, we aggregated individual bank default probabilities to provide policymakers with information about the general state of the financial system with a particular focus on generating a signal for countercyclical capital buffer (CCB) activation. Our key findings suggest that the probability of default exceeding 11% could signal about a vulnerable state in a bank and, in the aggregated model, in a financial system in general. The aggregated model successfully issues an out-of-sample signal of a systemic crisis four periods ahead of the start of the 2014-2015 turmoil.

Suggested Citation

  • Anatolii Hlazunov & Olesia Verchenko, 2020. "Predicting Bank Defaults in Ukraine: A Macro-Micro Perspective," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 250, pages 33-44.
  • Handle: RePEc:ukb:journl:y:2020:i:250:p:33-44
    DOI: 10.26531/vnbu2020.250.03
    as

    Download full text from publisher

    File URL: https://journal.bank.gov.ua/en/article/2020/250/03
    Download Restriction: no

    File URL: https://libkey.io/10.26531/vnbu2020.250.03?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
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Altman, Edward I., 1977. "Predicting performance in the savings and loan association industry," Journal of Monetary Economics, Elsevier, vol. 3(4), pages 443-466, October.
    3. Arena, Marco, 2008. "Bank failures and bank fundamentals: A comparative analysis of Latin America and East Asia during the nineties using bank-level data," Journal of Banking & Finance, Elsevier, vol. 32(2), pages 299-310, February.
    4. Carsten Detken & Olaf Weeken & Lucia Alessi & Diana Bonfim & Miguel M. Boucinha & Christian Castro & Sebastian Frontczak & Gaston Giordana & Julia Giese & Nadya Jahn & Jan Kakes & Benjamin Klaus & Jan, 2014. "Operationalising the countercyclical capital buffer: indicator selection, threshold identification and calibration options," ESRB Occasional Paper Series 05, European Systemic Risk Board.
    5. Mathias Drehmann & Claudio Borio & Kostas Tsatsaronis, 2011. "Anchoring Countercyclical Capital Buffers: The role of Credit Aggregates," International Journal of Central Banking, International Journal of Central Banking, vol. 7(4), pages 189-240, December.
    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. Sahut, Jean-Michel & Mili, Mehdi, 2011. "Banking distress in MENA countries and the role of mergers as a strategic policy to resolve distress," Economic Modelling, Elsevier, vol. 28(1-2), pages 138-146, January.
    2. 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.
    3. 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.
    4. Fazelina Sahul Hamid, 2013. "The Effect of Reliance on International Funding on Banking Fragility: Evidence from East Asia," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 7(1), pages 29-60, February.
    5. repec:erf:erfstu:78 is not listed on IDEAS
    6. Jorge E. Galán, 2021. "CREWS: a CAMELS-based early warning system of systemic risk in the banking sector," Occasional Papers 2132, Banco de España.
    7. Guo, Lin, 1999. "When and why did FSLIC resolve insolvent thrifts?," Journal of Banking & Finance, Elsevier, vol. 23(6), pages 955-990, June.
    8. Gutiérrez López, Cristina & Abad González, Julio, 2014. "¿Permitían los estados financieros predecir los resultados de los tests de estrés de la banca española? Una aplicación del modelo logit," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 17(1), pages 58-70.
    9. Martínez, Juan Francisco & Oda, Daniel, 2021. "Characterization of the Chilean financial cycle, early warning indicators and implications for macro-prudential policies," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 2(1).
    10. Paola Bongini & Stijn Claessens & Giovanni Ferri, 2001. "The Political Economy of Distress in East Asian Financial Institutions," Journal of Financial Services Research, Springer;Western Finance Association, vol. 19(1), pages 5-25, February.
    11. Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2018. "An evaluation of early warning models for systemic banking crises: Does machine learning improve predictions?," Discussion Papers 48/2018, Deutsche Bundesbank.
    12. Kick, Thomas & Koetter, Michael, 2007. "Slippery slopes of stress: Ordered failure events in German banking," Journal of Financial Stability, Elsevier, vol. 3(2), pages 132-148, July.
    13. Thomas B. King & Daniel A. Nuxoll & Timothy J. Yeager, 2006. "Are the causes of bank distress changing? can researchers keep up?," Review, Federal Reserve Bank of St. Louis, vol. 88(Jan), pages 57-80.
    14. Paola Cerchiello & Paolo Giudici, 2014. "Conditional graphical models for systemic risk measurement," DEM Working Papers Series 087, University of Pavia, Department of Economics and Management.
    15. repec:mth:ijafr8:v:8:y:2018:i:3:p:39-50 is not listed on IDEAS
    16. Bianchi, Benedetta, 2018. "Structural credit ratios," ESRB Working Paper Series 85, European Systemic Risk Board.
    17. Maghyereh, Aktham I. & Awartani, Basel, 2014. "Bank distress prediction: Empirical evidence from the Gulf Cooperation Council countries," Research in International Business and Finance, Elsevier, vol. 30(C), pages 126-147.
    18. Schudel, Willem, 2015. "Shifting horizons: assessing macro trends before, during, and following systemic banking crises," Working Paper Series 1766, European Central Bank.
    19. Swami, Onkar Shivraj & Vishnu Kumar, N. Arun & Baruah, Palash, 2012. "Determinants of the exit decision of foreign banks in India," MPRA Paper 38722, University Library of Munich, Germany.
    20. Lo Duca, Marco & Koban, Anne & Basten, Marisa & Bengtsson, Elias & Klaus, Benjamin & Kusmierczyk, Piotr & Lang, Jan Hannes & Detken, Carsten & Peltonen, Tuomas, 2017. "A new database for financial crises in European countries," ESRB Occasional Paper Series 13, European Systemic Risk Board.
    21. Mathias Drehmann & Mikael Juselius & Anton Korinek, 2017. "Accounting for debt service: the painful legacy of credit booms," BIS Working Papers 645, Bank for International Settlements.
    22. Iñaki Aldasoro & Claudio Borio & Mathias Drehmann, 2018. "Early warning indicators of banking crises: expanding the family," BIS Quarterly Review, Bank for International Settlements, March.

    More about this item

    Keywords

    early warning models (EWM); bank default probability; countercyclical capital buffer;
    All these keywords.

    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • G01 - Financial Economics - - General - - - Financial Crises

    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:ukb:journl:y:2020:i:250:p:33-44. 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: Research Unit (email available below). General contact details of provider: https://edirc.repec.org/data/nbugvua.html .

    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.