How Accurately Can Z-score Predict Bank Failure?

Laura Chiaramonte, Frank Hong Liu, F Poli, Mingming Zhou

Research output: Contribution to journalArticle

16 Citations (Scopus)

Abstract

Bank risk is not directly observable, so empirical research relies on indirect measures. We evaluate how well Z-score, the widely used accounting-based measure of bank distance to default, can predict bank failure. Using the U.S. commercial banks’ data from 2004 to 2012, we find that on average, Z-score can predict 76% of bank failure, and additional set of other bank- and macro-level variables do not increase this predictability level. We also find that the prediction power of Z-score to predict bank default remains stable within the three-year forward window.
Original languageEnglish
Pages (from-to)333-360
Number of pages28
JournalFinancial Markets, Institutions & Instruments
Volume25
Issue number5
Early online date14 Nov 2016
DOIs
Publication statusPublished - Dec 2016

Keywords

  • z-score
  • bank failure
  • financial crisis
  • E37
  • G01
  • G21

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