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How Accurately Can Z‐score Predict Bank Failure?

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  • Laura Chiaramonte
  • (Frank) Hong Liu
  • Federica Poli
  • Mingming Zhou

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.

Suggested Citation

  • Laura Chiaramonte & (Frank) Hong Liu & Federica Poli & Mingming Zhou, 2016. "How Accurately Can Z‐score Predict Bank Failure?," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 25(5), pages 333-360, December.
    • Handle: RePEc:wly:finmar:v:25:y:2016:i:5:p:333-360
    DOI: 10.1111/fmii.12077
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