S&P 500 · Monthly Heatmap — Twelve Months of Seasonality
Monthly seasonality — Which months tend to rise or fall: a year-by-month return heatmap.
Monthly return colours since 2000. November and April carry the highest win rates; September has the longest history of negative months.
What this page answers
Across a 27 year sample, the highest-probability month for the S&P 500 is November (positive +77% of the time) and the weakest is February (+48%). Seasonality is a statistical lean, not a trading guarantee — any single year can deviate wildly.
Monthly return colours since 2000. November and April carry the highest win rates; September has the longest history of negative months. 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
- 2026-09-03
S&P 500 — monthly win rates
| Month | Share of positive months |
|---|---|
| January | +52% |
| February | +48% |
| March | +59% |
| April | +70% |
| May | +74% |
| June | +59% |
| July | +67% |
| August | +63% |
| September | +48% |
| October | +62% |
| November | +77% |
| December | +65% |
Showing the full record (12 rows). Raw series: https://historyofmarket.com/api/sp500/monthly.json
Data & Source
GET /api/sp500/monthly.json — Canonical dataset endpoint.
Exchange closing prices · Company filings · Robert Shiller · FRED · NBER.
FAQ
Which month is historically strongest for the S&P 500?
November, positive in +77% of sampled years; the weakest is February (+48%).
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.