S&P 500 · Daily Distribution and Deep Down Days — Daily Return Distribution: Central Clustering and Tail Risk
Daily Return Fat-Tail Distribution — Histogram of over 6,600 daily returns, contrasting Gaussian normal assumptions with actual systemic left-tail extremes.
Top: the complete distribution of 6,600+ trading sessions since 2000, tightly clustered around 0%. Bottom: an enlarged view of down days exceeding -4%, including the -11.98% single-day shock on 2020-03-16, demonstrating that rare tail events exert disproportionate influence on long-term wealth accumulation.
What this page answers
This static page is built to answer searches for S&P 500 · Daily Distribution and Deep Down Days. It summarizes the live dataset behind the Daily Return Distribution: Central Clustering and Tail Risk panel and links to the full interactive chart.
Top: the complete distribution of 6,600+ trading sessions since 2000, tightly clustered around 0%. Bottom: an enlarged view of down days exceeding -4%, including the -11.98% single-day shock on 2020-03-16, demonstrating that rare tail events exert disproportionate influence on long-term wealth accumulation. 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-distribution.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.