Supervisory pension stress test
A common adverse market scenario is applied to fund balance sheets, assets and liabilities revalued together, and the effect on funding, sponsor support and cash flows is reported on a comparable basis.
GRA · Institutional Funds Nexus
Spatial financeWhere capital meets hazard, exposure and transition
Stress testing institutional funds
Scenario design and stress testing ask how a fund would fare if several adverse conditions arrived together: rates and markets, inflation and longevity, liquidity and sponsor weakness. For institutional funds they complement the valuation with a view of resilience, and they underpin supervisory stress tests and own-risk assessments.
01Contents
Stress testing institutional funds in five parts.
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 capital markets and investment and society and human development, 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.
Reverse stress test of funding
The board works backward from an outcome it cannot accept, such as benefit cuts or sponsor failure, to identify the combinations of events that would cause it and how plausible they are.
Long-horizon climate scenario analysis
NGFS transition and physical pathways are translated into asset, liability and sponsor effects over decades, and disclosed with the scenario version and its known omissions.
03Monitor
Scenario stress.
The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.
Scenario stress
Institutional funds · Stress testing institutional funds · Run R-7497
Severe case breaches limitGRA · Institutional Funds Nexus
Scenario set
| Baseline | Central | 21 | Within |
| Adverse | 1-in-25 | 54 | Close |
| Severe | 1-in-100 | 81 | Breach |
| Reverse stress | Find the break | 100 | Defines edge |
Method card
- Method
- Scenario design and stress testing
- Narrative
- compound shock
- Horizon
- 5 years
- Label
- MODELLED
Impact build-up, severe case
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 scenario frameworks | Common adverse scenarios and shocks | Published statistics |
| NGFS climate scenarios | Long-horizon transition and physical pathways | MODELLED |
| Historical market stress episodes | Analogues for calibration | OBSERVED |
| Fund balance sheet and cash flow data | Exposure to which shocks are applied | REPORTED |
05Scenario model
Transition and physical risk on a portfolio.
Three scenario families after the NGFS framework move a sector portfolio through carbon costs and warming damages; the transmission view follows the losses to lenders, investors, public finances and households. Scenario: named assumptions about the future, not a forecast.
Controls
- Carbon price at the horizon, orderly path
- 200 per tCO2
- Delay before a disorderly transition
- 50% of horizon
- Cost passed to customers
- 50%
- Warming today above pre-industrial
- 1.30°C
- Warming per decade, current policies
- 0.25°C
- Damage coefficient
- 0.24% per °C²
- Years ahead
- 25 years
Readouts
- Worst scenario at the horizon
- −33.6% of value
Numbers, methods and sources
| Year | Orderly transition (% value) | Delayed, disorderly transition (% value) | Current policies (% value) |
|---|---|---|---|
| 0 | −0.38 | −0.38 | −0.38 |
| 3 | −2.87 | −0.53 | −0.67 |
| 6 | −5.36 | −0.68 | −0.97 |
| 9 | −7.84 | −0.84 | −1.27 |
| 12 | −10.33 | −0.99 | −1.57 |
| 15 | −12.82 | −7.12 | −1.87 |
| 18 | −15.31 | −15.05 | −2.17 |
| 21 | −17.80 | −23.00 | −2.48 |
| 24 | −20.29 | −30.94 | −2.79 |
Methods
- Climate scenario families NGFS (2023), Climate Scenarios for central banks and supervisors, Phase IV
- Climate stress test of the financial system Battiston and others (2017), Nature Climate Change 7
- Damage function Nordhaus (2017), Revisiting the social cost of carbon, PNAS 114
- Transmission channels BCBS (2021), Climate-related risk drivers and their transmission channels
- 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
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:
- Urban extents Natural Earth
- Seaports Natural Earth
- Past year, daily temperature (ERA5 via Open-Meteo) Open-Meteo.com (CC BY 4.0), Copernicus ERA5 (C3S/ECMWF) · register open-meteo.public-pages
- Surface air temperature, daytime (AIRS) NASA AIRS · register nasa.gibs.context-live-layers
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Institutional Funds Nexus in Foundry
- Tested at Institutional Funds Nexus in Universe
- Codified in Finance, Insurance and the Economy in Standards
- Published in Institutional Funds Nexus in Reports
- Taught in Faculty of Finance and Economics in Academy
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 calibration | Shocks are compared with historical extremes and supervisory scenarios so severity is neither trivial nor implausible |
| Internal consistency | Rates, inflation, markets and longevity in each scenario are checked to move together in an economically coherent way |
| Management action review | Assumed responses, such as rebalancing or recapitalisation, are tested for whether they could be carried out in the time and market available |
| Comparison with events | When a real stress occurs, its effects are compared with what the scenario implied and the design is revised |
Scenario choice can reflect prevailing assumptions and miss novel combinations. Results depend on how participants and models represent responses.
07Exposure, loss and capital
What stress testing institutional funds 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.
Scenario pathways
How stress testing institutional funds could be stressed under the scenario families central banks and supervisors use.
| Scenario family | Transition risk | Physical risk | What a stress test asks |
|---|---|---|---|
| Orderly | Early, gradual policy | Lower | Can the book absorb a steady repricing? |
| Disorderly | Late, abrupt policy | Lower to medium | What breaks under a sudden repricing and credit migration? |
| Hot house world | Limited policy | High and rising | Where do physical losses concentrate in collateral and insurance? |
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
09Stewardship
Who maintains the method.
Systemic Risk Management stewards scenario design and stress testing for the Consortium and reviews how it is applied across platforms.
10Connected
Where this page leads across the Consortium.
11Questions
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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