Data sources, anchors and assumptions

Every numeric input in the code is tagged [REAL] (anchored on a September–October 2026 disclosure), [HIST] (historical record) or [ASSUMED] (a modelling judgment, varied in the Monte Carlo). This page lists where the main anchors come from and which judgments matter most. Nothing here is investment advice.

Real anchors named in the code and paper

• AI capital stock: cumulative gross AI capex 2024–26 of $400B / $650B / $1,000B (2026 per Goldman Sachs); planned 2027–28 capex $1.35T / $1.6T from the same path; 2029 extrapolated.
• CoreWeave (calibration anchor for the neocloud): 2026 revenue guidance $12.4–13.2B, total debt $35.1B (June 2026), interest about $2.56B a year, 2027 principal $6.2B, property and equipment $36.4B, a $104B contract backlog, a term loan at SOFR+550bp, a 5-year CDS peak of 8.8% (Dec 2025).
• Oracle 5-year CDS 227bp (28 Sep 2026). 3-month bill 4.4%, 10-year Treasury 5.29% (about the highest since 2007).
• SOX +181% over twelve months to June 2026; volatility near dot-com levels; NVDA 30-day implied volatility 32.2% and realised 38.9% (3 Oct 2026).
• Revenue growth for Model G: OpenAI booked revenue about +94% annualised (Q1→Q2 2026), hyperscaler AI run-rates about ×2.4 a year, Google Cloud +63%.
• External cross-checks: Polymarket "AI industry downturn" contracts (7.1% by 31 Dec 2026; 18% by 30 Jun 2027, thin market); NY Fed 12-month recession probability 13.9%; a fund-manager survey naming chips the most crowded trade.

Academic sources

• Greenwood, Shleifer and You (2019), Bubbles for Fama, JFE 131(1): crash probabilities after sector run-ups (the crash definition and the run-up tables used in Part I).
• Greenwood, Hanson, Shleifer and Sørensen (2022), Predictable Financial Crises, JF 77(2): the "R-zone" indicator.
• Battiston et al. (2012), DebtRank, Scientific Reports 2: the contagion-network idea behind Model D.

The judgment calls that matter most

1. When the AI boom started (history estimate): mid-2023 to mid-2024. Dating it to 2025–26 lowers that estimate a lot.
2. How lenient the plan path is, and the 15% bust line.
3. How a Model G shortfall maps onto Model F's demand shock (central: it is the input shock; alternative: it is the realised bottom).
4. Whether a demand stall ends hypergrowth for good (here growth restarts at the long-run rate).
5. How strongly the Fed, sovereign buyers, the power grid and CFOs respond in Model F.
6. How much option and credit prices overstate real-world odds (the physical-over-risk-neutral haircuts).

Each is stated, varied in a sensitivity, and none can be measured precisely. See docs/paper.md (sections 17 and Appendix A) for the full parameter tables and docs/03-…, docs/04-… for how each enters the equations.

Data you must fetch yourself

The repository ships derived results and one recorded snapshot of the paper's own inputs. It does not ship raw feeds or the live history database. The live pipeline downloads public data from the U.S. Treasury, SEC EDGAR, FRED and Yahoo Finance at your request; check each provider's terms before redistributing what you download.