Spatial financeWhere capital meets hazard, exposure and transition
Stress testing private portfolios
Scenario design and stress testing ask how portfolio companies, funds and investors would fare under severe but plausible conditions: rate shocks, closed exit markets, physical disasters, supply failures or technology substitution. In private markets, where history is short and prices are estimated, scenarios often carry more information than statistical models.
What scenario design and stress testing does here.
Scenario design and stress testing construct plausible, severe future conditions to examine howسیستەمەکانand institutions would perform. They complement probabilistic analysis where data are scarce or futures are deeply uncertain. In capital markets and investment and industry and robotics, stress tests reveal vulnerabilities that arise when several risks materialise together. They inform capital, contingency and coordination plans across sectors. The canonical description is onthe STEM Commons.
Rate and refinancing stress
Higher rates and tighter credit are applied to each holding’s debt stack and maturity profile, with sponsor and lender actions stated, to show where liquidity and covenants fail first.
Physical event across a portfolio
A flood or heat scenario is applied to geocoded sites and key suppliers of every holding, tracing damage and downtime into earnings, insurance recoveries and covenant headroom.
Exit freeze and investor liquidity
Exits are slowed for a stated period while capital calls continue, showing how distributions, secondary sales and fund-level borrowing interact at limited partners.
03Scenario 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.
کۆنترۆڵەکان
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
ساڵەکانی داهاتوو
25 years
خوێندنەوەکان
Worst scenario at the horizon
−33.6% of value
ژمارە، ڕێگا و سەرچاوەکان
ساڵ
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
ڕێگاکان
Climate scenario familiesNGFS (2023), Climate Scenarios for central banks and supervisors, Phase IV
Climate stress test of the financial systemBattiston and others (2017), Nature Climate Change 7
Damage functionNordhaus (2017), Revisiting the social cost of carbon, PNAS 114
Transmission channelsBCBS (2021), Climate-related risk drivers and their transmission channels
پەنجەی نادڵنیایی (مۆنتی کارلۆی پارامیتەر) Spiegelhalter, Pearson و Short (2011)، Visualising uncertainty about the future، Science 333
هەستیاریی یەک-یەک (تۆرناد) Saltelli و ئەوانی دیکە (2008)، Global Sensitivity Analysis: The Primer، Wiley
داتا
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:
بەرینی شارەکان Natural Earth
بەندەرە دەریاییەکان 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
Transition and physical risk on a portfolio. Illustrative teaching model: it runs on the values set by the controls, not on measured data. 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).
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 inthe source register.
داتا
ڕۆڵ
ناونیشان
Supervisory scenarios (Bank of England, ECB, Federal Reserve)
Severity and macro paths
ئامارە بڵاوکراوەکان
NGFS climate scenarios
Physical and transition pathways
مۆدێلکراو
Historical market episodes
Analogues for severity and timing
چاودێریکراو
Portfolio company and fund data
Exposures and balance sheets
REPORTED
05Exposure, loss and capital
What stress testing private portfolios 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 private portfolios 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
نزم
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?
Scenario families as defined by the NGFS; the curves are an illustrative combined pressure index, not NGFS variables or forecasts.
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
06پشتڕاستکردنەوە
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.
بپشکنە
How it is done
Severity against history
Each scenario is compared with past episodes and its relative severity stated
Internal consistency
Rates, spreads, valuations and exits move together in ways the scenario narrative explains
Stated management actions
Sponsor, lender and investor responses are listed and tested with and without them
Reverse stress testing
The conditions that would breach a stated tolerance are identified, not only the outcome of a chosen scenario
Scenario choice can reflect prevailing assumptions and miss novel combinations. Results depend on how participants and models represent responses.
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.
Reportsis the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
Global Risks AlliancePrivate Equity Nexusئامادەیی دارایی و بیمە
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