23 Pages Posted: 10 Nov 2015
Date Written: November 10, 2015
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
JEL Classification: C20, C60, G21
Suggested Citation: Suggested Citation
Mare, Davide Salvatore and Moreira, Fernando and Rossi, Roberto, Nonstationary Z-Score Measures (November 10, 2015). Available at SSRN: https://ssrn.com/abstract=2688367 or http://dx.doi.org/10.2139/ssrn.2688367