Macro-financial scenario design
Adverse scenarios set paths for growth, unemployment, rates and asset prices, with the narrative and historical calibration stated.
GRA · Financial Stability
Spatial financeWhere capital meets hazard, exposure and transition
Scenario design and stress testing for financial stability
Scenario analysis and stress testing explore how institutions and the system would fare under severe but plausible conditions. On this platform they are explained as tools for testing resilience, with attention to scenario choice, behavioural responses and second-round effects.
01Register
Scenario design and stress testing for financial stability on the record.
Method recordSTEM method
- MethodScenario design and stress testing
- StewardSystemic Risk Management
- Applied inFinancial Stability
- Data4 inputs
- Checks3 validation steps
- Canonical pageSTEM Commons
02Application
What scenario design and stress testing does here.
Scenario design and stress testing construct plausible, severe future conditions to examine how systems and institutions would perform. They complement probabilistic analysis where data are scarce or futures are deeply uncertain. In financial stability, risk management and systemic risk and capital markets and investment, stress tests reveal vulnerabilities that arise when several risks materialise together. They inform capital, contingency and coordination plans across sectors. The canonical description is on the STEM Commons.
System-wide exercises
Banks, funds, insurers and central counterparties respond to a common shock, and their combined actions are traced to market prices.
Reverse stress tests
Firms identify scenarios that would breach capital or liquidity thresholds, revealing vulnerabilities that standard scenarios miss.
03Stress test
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.
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
04Data
What the method consumes.
Datasets and records used by scenario design and stress testing on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.
| Data | Role | Label |
|---|---|---|
| Supervisory scenarios | Shock paths | Published statistics |
| Bank and insurer balance sheets | Starting positions | Published statistics |
| Satellite models | Loss translation | MODELLED |
| NGFS scenarios | Climate pathways | MODELLED |
05Exposure, loss and capital
What it 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 scenario design and stress testing for financial stability reaches credit, market, underwriting, liquidity and operational risk, and feeds back.
NGFS climate scenarios · Network for Greening the Financial SystemIFRS S2 Climate-related Disclosures · ISSBTCFD recommendations · Financial Stability Board TCFDPrinciples for the effective management of climate-related financial risks · Basel Committee on Banking Supervision
06Validation
How results are checked.
Scenarios are reviewed for plausibility, internal consistency and severity relative to history. Exercise outcomes are compared with actual events when they occur.
| Check | How it is done |
|---|---|
| Severity benchmarking | Scenarios are compared with historical stress episodes |
| Model challenge | Loss models are independently reviewed and back-tested |
| Conditional framing | Results are presented as conditional on the scenario, never as forecasts |
Scenario choice can reflect prevailing assumptions and miss novel combinations. Results depend on how participants and models represent responses.
07Connections
Topics that rely on this method.
08Stewardship
Who maintains the method.
Systemic Risk Management stewards scenario design and stress testing for the Consortium and reviews how it is applied across platforms.
09Connected
Where this page leads across the Consortium.
10Questions
Questions and answers.
What are the limits of scenario design and stress testing in this field?
Scenario choice can reflect prevailing assumptions and miss novel combinations. Results depend on how participants and models represent responses.
How are results checked?
Scenarios are reviewed for plausibility, internal consistency and severity relative to history. Exercise outcomes are compared with actual events when they occur.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method's use, not a run; no result is reported here.
Where else is this method applied?
The canonical method page lists every platform that applies it.
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