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How accurately can Z-score predict bank failure?

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posted on 06.02.2020 by Laura Chiaramonte, Hong Liu, Federica Poli, Mingming Zhou
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.

History

School

  • Business and Economics

Department

  • Business

Published in

Financial Markets, Institutions & Instruments

Volume

25

Issue

5

Pages

333 - 360

Publisher

Wiley

Version

AM (Accepted Manuscript)

Rights holder

© New York University Salomon Center and Wiley Periodicals, Inc.

Publisher statement

This is the peer reviewed version of the following article: Chiaramonte, L., Liu, H., Poli, F. and Zhou, M. (2016), How Accurately Can Z‐score Predict Bank Failure?. Financial Markets, Institutions & Instruments, 25 (5), pp.333-360, which has been published in final form at https://doi.org/10.1111/fmii.12077. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.

Publication date

2016-11-14

Copyright date

2016

ISSN

0963-8008

eISSN

1468-0416

Language

en

Depositor

Prof Hong Liu. Deposit date: 4 February 2020

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