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Nonstationary Z-Score measures

Davide Salvatore Mare (), Fernando Moreira and Roberto Rossi

European Journal of Operational Research, 2017, vol. 260, issue 1, 348-358

Abstract: 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 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.

Keywords: Bank stability; Prudential regulation; Insolvency risk; Financial distress; Z-Score (search for similar items in EconPapers)
Date: 2017
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Working Paper: Nonstationary Z-score measures (2015) Downloads
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DOI: 10.1016/j.ejor.2016.12.001

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