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.
Highlights
The experiences from previous financial crises have shown that it is important to assess a bank’s resilience from a solvency and a liquidity perspective
This paper provides an analytical framework for the ex-ante assessment of the resilience of banks to liquidity shocks
We estimate the counterbalancing capacity of banks to respond to liquidity stress by quantifying their available liquid assets in each stress scenario
Summary
The experiences from previous financial crises have shown that it is important to assess a bank’s resilience from a solvency and a liquidity perspective. Aikman et al [9] developed a macro stress testing framework, in which a liquidity risk arises endogenously as a function of a bank’s solvency, liquidity position, similarity to other banks facing funding difficulties, and other market factors. Funding risk is integrated into their liquidity stress testing framework with mark-to-market losses and asset fire sales, amplifying solvency risk. The indicator integrates the available information of the liquidity condition of individual banks, sectors, clusters, or the market as a whole conditional on a stress scenario The latter metric allows a standardized identification of liquidity-related financial stability risks, facilitating analysis across market segments and through time.
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