A Liquidity Shortfall Analysis Framework for the European Banking Sector

Abstract

This paper presents an analytical framework for the identification of vulnerabilities arising from the liquidity and funding profile of banks. It is composed of two pillars—estimation of liquidity needs and the counterbalancing capacity of the total liquid assets—that determine a liquidity surplus or shortfall and the drivers for a range of plausible scenarios. Granular bank-level data on the structure of liabilities, maturation profile, liquid assets quality composition, and asset encumbrance are used for that purpose, also taking into account associated commonality effects. A new liquidity metric is introduced—the distance to liquidity stress indicator (DLSI)—which measures the required stress factor for banks to become illiquid. The novelty of the approach (i.e., taking into account asset encumbrance to determine counterbalancing capacity) provides empirical evidence that asset encumbrance has a significant impact on a bank’s liquidity position, leading to the non-linear behavior of liquidity shortfalls, even in the case of linear stress factors.

Coupled Price–Volume Equity Models with Auto-Induced Regime Switching

“…In Kont ȗs and Mihanović (2019), the authors considered liquidity level measured by cash to current liabilities ratio and a deterministic arithmetic mathematical model, for calculating net earnings through decreasing the amount of liquid assets. The work by Georgescu et al (2020) introduced an analytical framework in their methodology to identify vulnerabilities arising from the liquidity and funding profiles of banks. They proposed a novel liquidity metric that gauges the stress factor necessary for banks to become illiquid, and they outlined another analytical framework for evaluating the resilience of banks in the face of a liquidity shock.…”