Nasdaq 100 · Monthly Heatmap — Nasdaq 100 Monthly Return Heatmap
Monthly seasonality — Nasdaq 100 returns as a year-by-month heatmap.
Since 1985. November and December post the highest monthly win rates; January and September register the most frequent declines.
What this page answers
Across a 41 year sample, the highest-probability month for the Nasdaq 100 is January (positive +71% of the time) and the weakest is February (+49%). Seasonality is a statistical lean, not a trading guarantee — any single year can deviate wildly.
Since 1985. November and December post the highest monthly win rates; January and September register the most frequent declines. 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
Nasdaq 100 — monthly win rates
| Month | Share of positive months |
|---|---|
| January | +71% |
| February | +49% |
| March | +66% |
| April | +61% |
| May | +68% |
| June | +51% |
| July | +66% |
| August | +61% |
| September | +54% |
| October | +63% |
| November | +68% |
| December | +53% |
Showing the full record (12 rows). Raw series: https://historyofmarket.com/api/ndx/monthly.json
Data & Source
GET /api/ndx/monthly.json — Canonical dataset endpoint.
Exchange closing prices · Company filings · Robert Shiller · FRED · NBER.
FAQ
Which month is historically strongest for the Nasdaq 100?
January, positive in +71% of sampled years; the weakest is February (+49%).
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.