A framework to run system-wide, balance sheet data-based liquidity stress tests is presented. The liquidity framework includes three elements: (a) a module to simulate the impact of bank run scenarios; (b) a module to assess risks arising from maturity transformation and rollover risks, implemented either in a simplified manner or as a fully-fledged cash flow-based approach; and (c) a framework to link liquidity and solvency risks. The framework also allows the simulation of how banks cope with upcoming regulatory changes (Basel III), and accommodates differences in data availability. A case study shows the impact of a "Lehman" type event for stylized banks.
Bank liquidity was traditionally viewed as of equal importance to their solvency. Liquidity risks are inherent in maturity transformation, i.e., the usual long-term maturity profile of banks’ assets and short-term maturities of liabilities. Banks have commonly relied on retail deposits, and, to some degree, long-term wholesale funding as supposedly stable sources of funding. Yet, attention to liquidity risk diminished in recent decades, was symbolized by the absence of consideration of liquidity risk in the 1988 Basel I framework (Goodhart, 2008).
The global financial crisis has clearly shown that neglecting liquidity risk comes at a substantial price. Over the last decade, large banks d became increasingly reliant on shortterm wholesale funding (especially in interbanking markets) to finance their rapid asset growth. At the same time, funding from non-deposit sources (such as commercial paper placed with money market mutual funds) soared. With the unfolding of the global financial crisis, when uncertainties about the solvency of certain banks emerged, various types of wholesale funding market segments froze, resulting in funding or liquidity challenges for many banks.3 In the light of this experience, there is now a widespread consensus that banks’ extensive reliance on deep and broad unsecured money markets pre-crisis is to be avoided (and in current market conditions there is no appetite for that anyway). Creating substantial liquidity buffers across the board is the explicit aim of a number of regulatory responses to the crisis, such as the CEBS Guidelines on liquidity buffers (CEBS 2009b) as well as the forthcoming Basel III liquidity standards, the Liquidity Coverage Ratio (LCR) and the Net Stable Funding Ratio (NSFR).
The liquidity stress testing framework presented herein was developed in the context of recent Financial Sector Assessment Programs (FSAPs)4 and IMF technical assistance especially in Eastern Europe, extending the seminal work of Čihák (2007), and drawing upon work at the Austrian National Bank (OeNB). While developing the framework, five key facts were accounted for: (i) the availability of data varies widely; (ii) liquidity risk has several dimensions and assessing banks’ resilience vis-à-vis funding risks requires multi-dimensional analysis; (iii) designing and calibrating scenarios is more challenging than for solvency risks, mainly as liquidity crises are relatively rare and originate from different sources; (iv) there is a close link between solvency and liquidity risks; and (v) while the paper and tool present some economic benchmark scenarios, but these scenarios and economic and behavioral assumptions used for the tests should depend on bank- and country-specific circumstances, and current circumsta ces (i.e., the level of stress), among others. More generally speaking, the presented liquidity stress testing framework herein does not substitute for sound economics in designing the tests.
The answer to these multiple dimensions is a framework that is an Excel-based, easy-to-use balance sheet type liquidity stress testing tool that allows running bottom-up tests for hundreds of banks: First, the tool can be used to run some basic tests in circumstances where data is very limited to broad asset and liability items. Likewise, a cash flow based module allows running detailed liquidity analysis like those carried out by banks for the internal purposes but again can be adapted to a more limited data environment. Second, the framework includes three broad dimensions (based on four modules) that allow for complementary views on liquidity risks, including the link to solvency risks. Third, the paper provides benchmark scenarios based on historical evidence on the one hand and common scenarios used by FSAP missions on the other. Fourth, the framework allows assessing the link between liquidity and solvency, albeit additional effort is needed in this context, including work that captures dynamic aspects of this relationship and spillover effects such as dynamically examining the link from liquidity to solvency concerns. As such, the framework is meant to provide users with the possibility to run a meaningful system-wide liquidity stress test within a relatively short period of time, but can also be used for monitoring purposes.
It is vital to bear in mind that the key benefit of system-wide stress tests is to benchmark banks against one another, i.e. to run peer comparisons and thereby assess their relative vulnerability to different shocks. Whether and how a shock materializes depends on the various factors, with behavioral aspects increasingly playing an essential role. Hence, it is also acknowledged that regular liquidity stress testing is not a panacea for a qualitative judgment by policy-makers in order to complement findings even from well-designed liquidity stress tests.
While cash flow data reporting, for instance, will become mandatory in the European Capital Requirements Directive (CRD) IV regulation, it is (for now) still rarely available at regulatory/ supervisory institutions so we follow a two-pronged approach, distinguishing between implied cash flow tests and a “real” cash flow approach, thereby seeking to lift liquidity tests to a next generation level.The framework consists of three elements:
(i) Stress testing funding liquidity based on an implied cash flow approach, with two different components: (a) a tool to simulate bank-run type scenarios while accounting for fire sales of liquid assets and/ or central bank liquidity provision subject to eligible collateral and haircuts; and (b) a liquidity gap analysis module that matches assets and liabilities for different maturity buckets under different stress assumptions, including rollover risk; the tool also allows for calculating (simplified) Basel III liquidity ratios.
(ii) Cash flow-based liquidity tests—running this module ideally requires detailed data on contractual cash flows for different maturity buckets and behavioral data based on banks’ financial/funding plans. If the latter are not available, the tool can be run on contractual cash-flows only and behavioral flows can be modeled based on the stress test assumptions. The calibrated scenarios then denote roll-over assumptions for contractual cash-outflows and cash-inflows. The former focus on funding risk and the latter take into account the banks’ objective to maintain its franchise value even under stress. In addition, market funding risk can be captured through haircuts. Accordingly, the module allows for an intuitive view of each banks’ liquidity risk bearing capacity in the form of the cumulated counterbalancing capacity at the end of each maturity bucket. In addition to stress testing, the module is also meant to be used for liquidity monitoring purposes, for which behavioral cash-flows are particularly informative.
(iii) Tests linking solvency and liquidity risk—the tool allows linking liquidity and solvency risk from three complementary perspectives. The assumptions are crucial for these tests and require sound judgment by the stress tester. First, the module allows simulating the increase in funding costs from a change in solvency, indicated by a change in a bank’s (implied) rating. Second, the tool enables simulating the partial or full closure of funding markets (both long and short-term) depending on the level of capitalization with or without considering solvency stress. Third, it allows examining the potential impact of concentration in funding and a name crisis (e.g., from parent banks) on banks’ liquidity positions.
The output of the tests provides failure and pass rates (in terms of the number of banks and total assets, respectively), and the estimated funding shortfalls for each bank as well as at the system level (or group of banks tested). For instance for the fully-fledged cash flow test, (cumulative) funding gaps and the corresponding (cumulative) counterbalancing capacity for each maturity bucket are provided after haircuts and roll over rates for each bank and the
IMF. Author/Editor:Schmieder, Christian; Hesse,Heiko; Neudorfer, Benjamin; Puhr, Claus; Schmitz, Stefan W.Working Paper No. 12/3
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