The Global Risks Alliance (GRA)
The methods Private Equity Nexus relies on, the assumptions they carry and the limits of what they can show.
GRA · Established · service level R0
The Private Equity Nexus methods page sets out the methods the platform relies on, among them financial economics and macro-finance, financial and risk engineering, and scenario design and stress testing, with their assumptions, validation and limits. Each analysis lists its assumptions and data, reports ranges and confidence beside central estimates, is checked against observations or other models, and states what it cannot show.
Fig.How a finding is reviewed before it is published. Design, not a record.
For analysis and uncertainty, in GRA's spatial-finance reading, the map opens on population density and night lights with built-up and settlement extent from NASA GIBS, framed on the contiguous United States; every other NASA layer, live feed and forecast waits in the layer list.
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For analysis and uncertainty, in GRA's spatial-finance reading, the map opens on population density and night lights with built-up and settlement extent from NASA GIBS, framed on the contiguous United States; every other NASA layer, live feed and forecast waits in the layer list.Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.
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Private assets are valued at fair value under IFRS 13 or ASC 820, usually at Level 3 with unobservable inputs, following the IPEV guidelines. Climate and hazard risk enter through cash-flow assumptions, discount rates and exit multiples. Research examines how sensitive those valuations are to stated scenarios, never the value of any company.
| Input | How hazard or transition risk enters |
|---|---|
| Cash flows | Interruption, repair capex, insurance cost, carbon cost |
| Discount rate | Risk premium for exposure, if markets price it |
| Exit multiple | Buyer's view of long-horizon risk |
Private-market returns are reported infrequently and smoothed, which hides volatility and correlation with public markets. Methods for sparse data are discussed at credibility and sparse data.
Each analysis lists its assumptions and the data it depends on.
Ranges and confidence are reported alongside central estimates.
Models are checked against observations and, where possible, against other models.
What an analysis cannot show is stated beside what it can.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Uncertainty quantification | Characterising and propagating the uncertainties in a model to state confidence in its outputs. |
| Sensitivity analysis | Repeating an analysis under different assumptions to show how much the result depends on them. |
| Model validation | Independent testing that a model performs as intended and is fit for a stated use. |
| Financial economics and macro-finance | Financial economics and macro-finance study how asset prices, credit and financial institutions interact with the real economy. |
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.