IRIS PubliCatt
PubliCatt è il repository istituzionale ad accesso aperto dell'Università Cattolica del Sacro Cuore, dove gli utenti autorizzati afferenti all'Ateneo provvedono direttamente e autonomamente a depositare e a rendere visibili le proprie pubblicazioni, inserendo i dati descrittivi del documento stesso ("metadati", quali il titolo, autore, abstract, etc.) e, laddove possibile, il testo della pubblicazione stessa (full-text).
PubliCatt utilizza la piattaforma IRIS (Institutional Research Information System) sviluppata da CINECA.
EnglishBank 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.
Chiaramonte, L., Liu, F. H., Poli, F., Zhou, M., How Accurately Can Z-score Predict Bank Failure?, <<FINANCIAL MARKETS, INSTITUTIONS & INSTRUMENTS>>, 2016; 25 (5): 333-360. [doi:10.1111/fmii.12077] [http://hdl.handle.net/10807/90590]
| Autori: | |
| Titolo: | How Accurately Can Z-score Predict Bank Failure? |
| Digital Object Identifier (DOI): | http://dx.doi.org/10.1111/fmii.12077 |
| URL: | http://onlinelibrary.wiley.com/doi/10.1111/fmii.2016.25.issue-5/issuetoc |
| Data di pubblicazione: | 2016 |
| 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. |
| Lingua: | Inglese |
| Rivista: | |
| Citazione: | Chiaramonte, L., Liu, F. H., Poli, F., Zhou, M., How Accurately Can Z-score Predict Bank Failure?, <<FINANCIAL MARKETS, INSTITUTIONS & INSTRUMENTS>>, 2016; 25 (5): 333-360. [doi:10.1111/fmii.12077] [http://hdl.handle.net/10807/90590] |
| Appare nelle tipologie: | Articolo in rivista, Nota a sentenza |
File in questo prodotto:
Copyright © 2020