How Accurately Can Z‐score Predict Bank Failure?
Laura Chiaramonte,
(Frank) Hong Liu,
Federica Poli and
Mingming Zhou
Financial Markets, Institutions & Instruments, 2016, vol. 25, issue 5, 333-360
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.
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://doi.org/10.1111/fmii.12077
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:wly:finmar:v:25:y:2016:i:5:p:333-360
Access Statistics for this article
More articles in Financial Markets, Institutions & Instruments from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().