2015
DOI: 10.1016/j.gfj.2015.02.002
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Should we trust the Z-score? Evidence from the European Banking Industry

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Cited by 91 publications
(76 citation statements)
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“…They also assessed the predictive power of the Z-score according to various bank characteristics and found that the Z-score was slightly more effective when the organizational and productive complexity of banks increased along with the public incentives to scrutinize bank riskiness, as it is the case for large banks. Finally, Chiaramonte et al (2015) indicated that, during the financial crisis, the accuracy of the Z-score marginally improved with respect to the whole period.…”
Section: Model Diagnosticsmentioning
confidence: 96%
See 1 more Smart Citation
“…They also assessed the predictive power of the Z-score according to various bank characteristics and found that the Z-score was slightly more effective when the organizational and productive complexity of banks increased along with the public incentives to scrutinize bank riskiness, as it is the case for large banks. Finally, Chiaramonte et al (2015) indicated that, during the financial crisis, the accuracy of the Z-score marginally improved with respect to the whole period.…”
Section: Model Diagnosticsmentioning
confidence: 96%
“…This particular study focused on the empirical attractiveness of the Z-score, as it does not require strong assumptions about the distribution of ROA. In addition, Chiaramonte et al (2015) examined whether the Z-score was an accurate tool to predict bank distress on a sample of banks from 12 European countries.…”
Section: Model Diagnosticsmentioning
confidence: 99%
“…e authors observe that the estimates with accounting data for the Z-score may not generate good results. Chiaramonte, Croci, and Poli (2015) use the Z-score and evaluate that its popularity derives from the simplicity of computing it, requiring few data: Z-score = (ROA + Equity/Assets) /σ ROA . Chiaramonte, Croci, and Poli (2015) apply the Z-score indicator and the CAMELS system for a sample of European banks, concluding that the ability of that indicator is as good as the covariates of this system for identifying nancial distress events and more e ective when sophisticated business models are involved, as in the case of big banks.…”
Section: Financial Institutions and The Camels Systemmentioning
confidence: 99%
“…Chiaramonte, Croci, and Poli (2015) use the Z-score and evaluate that its popularity derives from the simplicity of computing it, requiring few data: Z-score = (ROA + Equity/Assets) /σ ROA . Chiaramonte, Croci, and Poli (2015) apply the Z-score indicator and the CAMELS system for a sample of European banks, concluding that the ability of that indicator is as good as the covariates of this system for identifying nancial distress events and more e ective when sophisticated business models are involved, as in the case of big banks. e authors argue that other measures such as the distance-to-default from Merton (1974) and credit default swaps prices are unviable for use in the presence of banks that are not listed on stock exchanges.…”
Section: Financial Institutions and The Camels Systemmentioning
confidence: 99%
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