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 Nasdaq 100's highest-probability month 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.
Latest Snapshot
- Updated
- 2026-07-17
the 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 | +60% |
| September | +55% |
| October | +63% |
| November | +68% |
| December | +53% |
Showing the full record (12 rows). Raw series: https://historyofmarket.com/api/ndx/monthly.json
Static Preview
Data & Source
GET /api/ndx/monthly.json — Canonical dataset endpoint.
Yahoo Finance · Macrotrends · Robert Shiller · FRED · S&P Global · Nasdaq · 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 including Yahoo Finance, Macrotrends, Robert Shiller, FRED, S&P Global, Nasdaq, and NBER. 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.