S&P 500 · Multiplicative Contribution by Extreme Days — The Geometry of Compounding: How Extreme Days Multiply Capital
Extreme Day Multiplier Decomposition — Quantifying the multiplicative compounding impact of the best and worst outlier trading days on long-term terminal wealth.
[Ex-post attribution, not timing advice] Long-term wealth compounds multiplicatively rather than additively: the top 50 sessions multiply capital by 13.37×, the middle ≈6,500 days contribute a modest 1.80×, while the worst 30 days degrade capital to 0.15×, leaving an initial $1 at an ending value of $5.10.
What this page answers
This static page is built to answer searches for S&P 500 · Multiplicative Contribution by Extreme Days. It summarizes the live dataset behind the The Geometry of Compounding: How Extreme Days Multiply Capital panel and links to the full interactive chart.
[Ex-post attribution, not timing advice] Long-term wealth compounds multiplicatively rather than additively: the top 50 sessions multiply capital by 13.37×, the middle ≈6,500 days contribute a modest 1.80×, while the worst 30 days degrade capital to 0.15×, leaving an initial $1 at an ending value of $5.10. The data is refreshed by the History of Market pipeline and published as a stable JSON endpoint for research, citation, and AI-agent use.
The plate
Latest Snapshot
- Updated
- 2026-09-08
Data & Source
GET /api/sp500/daily-extremes.json — Canonical dataset endpoint.
Exchange closing prices · Company filings · Robert Shiller · FRED · NBER.
FAQ
Where does this data come from?
History of Market combines public market and macro datasets — exchange closing prices, company filings, Robert Shiller, FRED, NBER, and the UBS Global Investment Returns Yearbook (Dimson–Marsh–Staunton). The exact endpoint for this panel is linked below.
How often is it updated?
Daily-tier datasets refresh after the U.S. market close, with a broader weekly refresh on Sunday. The timestamp shown on this page comes from the JSON payload.
Can I use the data?
Yes, for research and education with attribution to History of Market. Upstream data sources retain their own terms.