GRA · Financial Stability
Spatial financeWhere capital meets hazard, exposure and transition
Liquidity and market stress
Markets need buyers and sellers willing to trade at reasonable prices, and firms need funding they can roll. In stress, both kinds of liquidity can vanish together: dealers pull back, margins rise, and investors sell what they can. This page sets out how liquidity stress develops in core markets such as government bonds and repo, how it is measured, and which central banks, regulators and boards decide.
Liquidity and market stress on the record.
Liquidity and market stress: how the risk develops.
Funding shortages and correlated behaviour. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Funding and market liquidity spiral
When funding gets harder, intermediaries cut positions, which reduces market liquidity, which raises margins and haircuts, which tightens funding further.
Dealer capacity is limited
Dealers' balance sheets and risk limits cap how much they can absorb. When everyone sells the same safe assets for cash, intermediation capacity runs out.
Procyclical margins
Margin models that respond sharply to volatility raise calls when liquidity is scarcest. Calls force sales, which raise volatility again.
Central banks become backstop
In core market dysfunction, central banks may buy assets or lend against them. Their facilities restore functioning and raise questions about moral hazard and exit.
Settlement dependencies, and what fails with a node.
How a failure at one financial centre can spread through settlement links. Design links, not real dependencies.
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Government bond bid-ask spreads | basis points | daily | Market data | OBSERVED |
| Market depth | currency volume at best quotes | daily | Market data | OBSERVED |
| Repo rate spreads to policy rate | basis points | daily | Central bank and market data | OBSERVED |
| Initial margin requirements at central counterparties | currency | quarterly | CCP public quantitative disclosures | Published statistics |
| Liquidity coverage ratio | percent | monthly or quarterly | Bank Pillar 3 disclosures | Published statistics |
| Central bank liquidity facility use | currency outstanding | weekly | Central bank balance sheets | Published statistics |
Systemic risk dashboard.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Systemic risk dashboard
Liquidity and market stress · Financial system · Committee meeting 3
Vulnerabilities heat map
percentile vs history, 0 to 100
Exposure network
red: most connected node
Credit-to-GDP gap
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| Federal Reserve H.4.1 and facility data | Central bank balance sheet and facility use | Public domain |
| CCP public quantitative disclosures under CPMI-IOSCO standards | Margin, default fund and liquidity data | Public, terms per CCP |
| BIS Quarterly Review | Analysis of market functioning episodes | Free, BIS terms |
| Bank Pillar 3 disclosures | Liquidity and funding ratios | Public records, terms per bank |
| FSB report on liquidity preparedness for margin and collateral calls | Policy recommendations for nonbank liquidity preparedness | Free, FSB terms |
How a shock to assets becomes a system loss.
The equity the system loses after interbank contagion, against the initial hit, as leverage, interconnection and recovery rates change, the core of a macroprudential stress test. Teaching model with stated illustrative values, not a prediction. The map on this page shows Europe; the model itself is not tied to a place.
Controls
- Fall in external assets
- 2.0%
- Leverage (assets over equity)
- 10 times
- Interbank share of assets
- 10%
- Recovery on interbank claims
- 40%
- Banks in the system
- 20
- Core banks
- 20% of banks
Readouts
- Equity lost to the initial shock
- 18.0%
- Equity lost after contagion
- 45.0%
- Added by contagion (DebtRank)
- 27.0 points
- Banks in default
- 0
Numbers, methods and sources
| Round | System equity lost (%) | Banks in default |
|---|---|---|
| 0 | 18.00 | 0 |
| 1 | 28.80 | 0 |
| 2 | 35.28 | 0 |
| 3 | 39.17 | 0 |
| 4 | 41.50 | 0 |
| 5 | 42.90 | 0 |
| 6 | 43.74 | 0 |
| 7 | 44.24 | 0 |
| 8 | 44.55 | 0 |
| 9 | 44.73 | 0 |
| 10 | 44.84 | 0 |
| 11 | 44.90 | 0 |
| 12 | 44.94 | 0 |
| 13 | 44.96 | 0 |
| 14 | 44.98 | 0 |
| 15 | 44.99 | 0 |
| 16 | 44.99 | 0 |
| 17 | 45.00 | 0 |
| 18 | 45.00 | 0 |
| 19 | 45.00 | 0 |
| 20 | 45.00 | 0 |
| 21 | 45.00 | 0 |
| 22 | 45.00 | 0 |
| 23 | 45.00 | 0 |
| 24 | 45.00 | 0 |
| 25 | 45.00 | 0 |
| 26 | 45.00 | 0 |
| 27 | 45.00 | 0 |
| 28 | 45.00 | 0 |
| 29 | 45.00 | 0 |
| 30 | 45.00 | 0 |
Methods
- DebtRank Battiston and others (2012), Scientific Reports 2:541
- Differential DebtRank Bardoscia and others (2015), PLOS ONE 10
- Contagion in financial networks Gai and Kapadia (2010), Proc. R. Soc. A 466
- Clearing in financial networks Eisenberg and Noe (2001), Management Science 47
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
No observed data enters this model: it runs on the teaching values set by the controls, to be replaced with a programme's own evidence.
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Financial Stability in Foundry
- Tested at Financial Stability in Universe
- Codified in Finance, Insurance and the Economy in Standards
- Published in Financial Stability in Reports
- Taught in Faculty of Finance and Economics in Academy
Who decides, and what the evidence serves.
Financial Stability prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Central banks | Whether and how to provide liquidity in market dysfunction | Market functioning indicators and facility records |
| Market regulators | Whether market structure changes, such as central clearing, are needed | Liquidity measures and episode analyses |
| CCP risk committees | How margin models respond to volatility | Margin data and procyclicality analyses |
| Treasury and liquidity managers | What liquidity buffers and contingency plans to hold | Stress episode evidence and regulatory ratios |
Outputs this topic produces
- Guide to funding and market liquidity and how they interact
- Brief on margin procyclicality and transparency
- Method note on market liquidity measures and their limits
- Questions for boards on liquidity preparedness
Trace a shock in liquidity and market stress to the balance sheet.
Assembled from the Nexus Standards area profile Financial stability and prudential risk: the shocks it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Pick an initiating shock and step through the cascade to see which exposures it reaches and where losses could concentrate. The Map view places the run on an example geography with open data. Every weight is a stated assumption. An exercise, not a forecast, a valuation, a rating or investment advice. To model a place of your own choosing, open the full System Builder.
Hazards
- Dam failure
- River flood (set off downstream)
- Flash flood (set off downstream)
- Mass displacement (set off downstream)
- Widespread power outage (set off downstream)
- Water supply shortfall (set off downstream)
Systems and couplings
Controls
NS-0Constitution and principlesNS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-9Contextual UNIs (deployments, instances, programme instances)NS-10Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NS-14Conformance and crosswalk to external standardsNRS-H62Hazard family: Compound and multi-hazard events (NHS-1 sys.compound)NRS-H113Hazard family: Financial-system fragility (NHS-1 soc.financial-system)NRS-H118Hazard family: Organised crime and illicit economies (NHS-1 soc.crime)NRS-H79Hazard family: Mental health crises (NHS-1 health.mental)NRS-U9Universe platform profile: Financial Regulation NexusNRS-C5Scenarios and stress testing
Observation
- BIS Data Portal (credit, debt service, property prices, banking statistics) (listed for reference)
- IMF data services (WEO, IFS, FSI via SDMX) (listed for reference)
- OECD Data Explorer (SDMX API) (listed for reference)
- Financial Soundness Indicators
- Macroeconomic Dashboard
Example geography
- Western Europe: 152 hexagonal cells
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
- Surface soil moisture (SMAP), NASA GIBS
Shared questions the industry asks.
- 01
Why does liquidity disappear?
How uncertainty, losses and risk limits cause market makers and lenders to withdraw.
- 02
How do funding and market liquidity interact?
How tighter funding forces selling and selling tightens funding.
- 03
Which markets are fragile?
Where intermediation capacity is thin relative to the size of potential flows.
- 04
What role do margin and collateral play?
How margin calls in volatile markets drain liquidity.
What liquidity and market stress means for exposure, loss and capital.
The exposure, loss, scenario and capital views a risk officer, supervisor or ministry of finance would ask for, with the frameworks they report against. Structures follow supervisory and actuarial practice. Values are illustrative: never prices, ratings or advice.
Transmission channels
How a shock in liquidity and market stress reaches credit, market, underwriting, liquidity and operational risk, and feeds back.
How the risk arises and transmits.
Liquidity spirals link funding and markets. When asset prices fall, collateral values drop and margins rise, forcing leveraged holders to sell, which lowers prices further and tightens funding again.
Correlated behaviour is the core problem. Many participants use similar risk models, limits and strategies, so they want to sell the same assets at the same time.
Intermediation capacity matters. Dealers hold inventories and make markets, but their balance sheets are finite. In large sell-offs, they may step back, widening spreads and deepening price moves.
Electronic and automated trading provides liquidity in normal times but can withdraw quickly, contributing to sudden, short-lived dislocations. Liquidity that looks deep on screens may not be there when it is most needed.
Central banks act as lenders and sometimes market makers of last resort. Expectations of intervention can stabilise markets and can also encourage risk-taking.
How evidence is gathered, and where it stops.
| Method or data | What it shows | Its limit |
|---|---|---|
| Market microstructure data | Spreads, depth and price impact | High-frequency data is large and complex |
| Funding market data | Repo rates and volumes | Partial coverage |
| Episode studies | Behaviour in past stress events | Each episode differs |
| Agent-based models | Interaction of strategies | Sensitive to behavioural rules |
How it is studied, and what the methods cannot say.
- 01Financial economics and macro-financeRun incentives in funds and banks · Leverage cycles · Implicit guaranteesApplied here
- 02EconometricsEarly warning indicators · Quantile regression for growth-at-risk · Spillover estimationApplied here
- 03Scenario design and stress testingMacro-financial scenario design · System-wide exercises · Reverse stress testsApplied here
- 04Complex systems and agent-based modellingAgent-based market models · Early warning of regime shifts · Feedback loop mappingApplied here
Questions and answers.
What is the difference between market liquidity and funding liquidity?
Why do margin calls amplify stress?
What is the liquidity coverage ratio?
Does GRA predict market dislocations?
Why do liquidity problems appear suddenly?
Is this investment research?
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