GRA · Financial Stability
Spatial financeWhere capital meets hazard, exposure and transition
Contagion and fire sales
Contagion is the spread of distress from one institution or market to others beyond what direct losses would explain. Fire sales, runs and confidence effects drive it. A fire sale happens when forced sellers must sell assets quickly at prices below their value, imposing losses on every other holder. This page sets out how contagion and fire sales work, how they are measured, and which authorities decide.
How the work runs.
Systemic risk dashboard
Contagion and fire sales · Financial system · Committee meeting 2
Vulnerabilities heat map
percentile vs history, 0 to 100
Exposure network
red: most connected node
Credit-to-GDP gap
Fig.Systemic risk dashboard: example names and illustrative values, not a record or a live system.
Contagion and fire sales: how the risk develops.
Amplification pathways across markets. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Forced selling moves prices
When leveraged or redeeming investors must sell, prices fall. Mark-to-market losses hit every holder, triggering further sales by those near their limits.
Runs on short-term funding
Uninsured depositors and wholesale funders withdraw at the first sign of trouble. Digital banking and social media can speed runs to hours.
Information contagion
Distress at one firm leads investors to reassess others with similar business models, even without direct links, raising their funding costs.
Amplifiers stack
Leverage, liquidity mismatch, margin practices and accounting rules each amplify. Together they turn a modest shock into a system event.
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 |
|---|---|---|---|---|
| Fire-sale vulnerability measure | estimated losses from forced sales, currency | quarterly | Supervisory models | MODELLED |
| Uninsured deposit share | percent of deposits | quarterly | Bank regulatory reports | Published statistics |
| Deposit outflow speed in stress episodes | share of deposits per day | per episode | Supervisory reviews | REPORTED |
| Credit default swap spreads of financial institutions | basis points | daily | Market data | OBSERVED |
| Conditional value at risk measures | currency or percent | periodic | Academic and central bank estimates | MODELLED |
| Equity return correlation across financial firms | correlation, dimensionless | daily | Market data | OBSERVED |
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
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 review of the supervision of Silicon Valley Bank | Account of a rapid deposit run and supervisory response | Public domain |
| Basel Committee report on the banking turmoil | Lessons from bank failures in a recent stress episode | Free, BIS terms |
| NYU V-Lab SRISK estimates | Market-based systemic risk measures | Free to read, terms to check |
| ECB Financial Stability Review | Analysis of contagion channels in the euro area | Free, ECB terms |
| FDIC quarterly banking profile | Deposit composition and bank condition | Public domain |
Trace a shock in contagion and fire sales 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
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 |
|---|---|---|
| Prudential supervisors | Whether funding concentration and uninsured deposits need action | Funding data and run episode evidence |
| Deposit insurers and legislators | How deposit insurance coverage is set | Deposit composition and run evidence |
| Central banks | How lender of last resort facilities are designed and accessed | Run speed evidence and collateral data |
| Bank boards | How much reliance on uninsured and wholesale funding to accept | Funding structure benchmarks and stress evidence |
Outputs this topic produces
- Guide to contagion channels and their amplifiers
- Method note on market-based systemic risk measures
- Brief on lessons from recent bank runs
- Questions for boards on funding concentration
What contagion and fire sales 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 contagion and fire sales reaches credit, market, underwriting, liquidity and operational risk, and feeds back.
Shared questions the industry asks.
- 01
What forces selling?
Capital limits, margin calls, redemptions and risk limits that compel institutions to sell.
- 02
Who is hit by price falls?
How losses spread to all holders of the assets sold.
- 03
How does fear spread?
Information contagion when uncertainty about exposures causes withdrawal from sound institutions.
- 04
What stops contagion?
Buffers, transparency, resolution tools and backstops.
How the risk arises and transmits.
Fire sales occur when sellers must sell quickly and natural buyers are constrained. Prices fall below fundamental values, imposing mark-to-market losses on everyone holding similar assets and potentially forcing further sales.
Direct contagion runs through bilateral exposures: a failing institution cannot pay its creditors, who then face losses. Research suggests direct exposures alone often explain less contagion than indirect channels.
Indirect contagion runs through common holdings and prices, through funding markets and through information. When investors cannot tell who is exposed, they may withdraw from all similar institutions.
Procyclical rules and practices, such as mark-to-market accounting, value-at-risk limits and margin models, can amplify fire sales by requiring action at the worst moment, even when each rule is sensible on its own.
Breaking contagion requires credible buffers, information that distinguishes sound from unsound institutions, and tools to resolve failing firms without disorderly sales.
How evidence is gathered, and where it stops.
| Method or data | What it shows | Its limit |
|---|---|---|
| Fire-sale models | Price impact of forced selling | Price impact estimates are uncertain |
| Common holdings data | Overlap among investors | Holdings reporting lags |
| Event studies | Market reactions to failures | Confounding events |
| Network simulation | Combined direct and indirect contagion | Assumption-dependent |
How it is studied, and what the methods cannot say.
- 01Complex systems and agent-based modellingAgent-based market models · Early warning of regime shifts · Feedback loop mappingApplied here
- 02Network science and contagionInterbank contagion simulation · Common exposure networks · Multilayer networksApplied here
- 03Financial economics and macro-financeRun incentives in funds and banks · Leverage cycles · Implicit guaranteesApplied here
- 04EconometricsEarly warning indicators · Quantile regression for growth-at-risk · Spillover estimationApplied here
Questions and answers.
What is a fire sale?
Why are bank runs faster now?
What is SRISK?
Is contagion always irrational?
Does GRA identify vulnerable institutions?
What makes a rule procyclical?
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