Banking Stability Measures

TLDR

The BSMD captures banks’ default inter‑dependence, modeling linear and nonlinear distress dependencies that vary across economic cycles. The paper introduces banking stability measures that account for distress dependence, enabling assessment of common distress, pairwise distress, and system distress linked to individual banks. By treating the banking system as a portfolio, the authors estimate a multivariate density (BSMD) using the CIMDO approach, which improves density specification under restricted data without imposing parametric forms. These measures can be derived from limited publicly available data and applied to both developing and developed countries.

Abstract

This paper defines a set of banking stability measures which take account of distress dependence among the banks in a system, thereby providing a set of tools to analyze stability from complementary perspectives by allowing the measurement of (i) common distress of the banks in a system, (ii) distress between specific banks, and (iii) distress in the system associated with a specific bank. Our approach defines the banking system as a portfolio of banks and infers the system's multivariate density (BSMD) from which the proposed measures are estimated. The BSMD embeds the banks' default inter-dependence structure that captures linear and non-linear distress dependencies among the banks in the system, and its changes at different times of the economic cycle. The BSMD is recovered using the CIMDO-approach, a new approach that in the presence of restricted data, improves density specification without explicitly imposing parametric forms that, under restricted data sets, are difficult to model. Thus, the proposed measures can be constructed from a very limited set of publicly available data and can be provided for a wide range of both developing and developed countries.