Predicting Bank Defaults in Ukraine: A Macro-Micro Perspective

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 ind...

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Main Authors: Anatolii Hlazunov, Olesia Verchenko
Format: Article
Language:English
Published: National Bank of Ukraine 2020-12-01
Series:Visnyk of the National Bank of Ukraine
Subjects:
Online Access:http://journal.bank.gov.ua/uploads/articles/250-3.pdf
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author Anatolii Hlazunov
Olesia Verchenko
author_facet Anatolii Hlazunov
Olesia Verchenko
author_sort Anatolii Hlazunov
collection DOAJ
description 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.
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spelling doaj.art-7129ad8f78ca48cf931e53f5887bf7912022-12-21T21:55:45ZengNational Bank of UkraineVisnyk of the National Bank of Ukraine2414-987X2020-12-01250334410.26531/vnbu2020.250.03Predicting Bank Defaults in Ukraine: A Macro-Micro PerspectiveAnatolii Hlazunov0Olesia Verchenko1National Bank of UkraineKyiv School of EconomicsThis 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.http://journal.bank.gov.ua/uploads/articles/250-3.pdfearly warning models (ewm)bank default probabilitycountercyclical capital buffer
spellingShingle Anatolii Hlazunov
Olesia Verchenko
Predicting Bank Defaults in Ukraine: A Macro-Micro Perspective
Visnyk of the National Bank of Ukraine
early warning models (ewm)
bank default probability
countercyclical capital buffer
title Predicting Bank Defaults in Ukraine: A Macro-Micro Perspective
title_full Predicting Bank Defaults in Ukraine: A Macro-Micro Perspective
title_fullStr Predicting Bank Defaults in Ukraine: A Macro-Micro Perspective
title_full_unstemmed Predicting Bank Defaults in Ukraine: A Macro-Micro Perspective
title_short Predicting Bank Defaults in Ukraine: A Macro-Micro Perspective
title_sort predicting bank defaults in ukraine a macro micro perspective
topic early warning models (ewm)
bank default probability
countercyclical capital buffer
url http://journal.bank.gov.ua/uploads/articles/250-3.pdf
work_keys_str_mv AT anatoliihlazunov predictingbankdefaultsinukraineamacromicroperspective
AT olesiaverchenko predictingbankdefaultsinukraineamacromicroperspective