Nonstationary Z-score measures
Davide Salvatore Mare (),
Fernando Moreira and
MPRA Paper from University Library of Munich, Germany
In this work we develop advanced techniques for measuring bank insolvency risk. More speciﬁcally, we contribute to the existing body of research on the Z-Score. We develop bias reduction strategies for state-of-the-art Z-Score measures in the literature. We introduce novel estimators whose aim is to eﬀectively capture nonstationary returns; for these estimators, as well as for existing ones in the literature, we discuss analytical conﬁdence regions. We exploit moment-based error measures to assess the eﬀectiveness of these estimators. We carry out an extensive empirical study that contrasts state-of-the-art estimators to our novel ones on over ten thousand banks. Finally, we contrast results obtained by using Z-score estimators against business news on the banking sector obtained from Factiva. Our work has important implications for researchers and practitioners. First, accounting for the degree of nonstationarity in returns yields a more accurate quantiﬁcation of the degree of solvency. Second, our measure allows researchers to factor in the degree of uncertainty in the estimation due to the availability of data while estimating the overall risk of bank insolvency.
Keywords: bank stability; prudential regulation; insolvency risk; ﬁnancial distress; Z-Score (search for similar items in EconPapers)
JEL-codes: C20 C60 G21 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-rmg
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Journal Article: Nonstationary Z-Score measures (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:67840
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