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S&P 500 · § IV
S&P 500 · Monthly Heatmap

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.

View the interactive chart Download raw JSON

What this page answers

Across a 27 year sample, the S&P 500's highest-probability month 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.

Latest Snapshot

Updated
2026-07-17

the S&P 500 monthly win rates

the S&P 500 monthly win rates
MonthShare of positive months
January+52%
February+48%
March+59%
April+70%
May+74%
June+59%
July+70%
August+62%
September+50%
October+62%
November+77%
December+65%

Showing the full record (12 rows). Raw series: https://historyofmarket.com/api/sp500/monthly.json

Static Preview

Twelve Months of Seasonality Chart

Data & Source

GET /api/sp500/monthly.json — Canonical dataset endpoint.

Yahoo Finance · Macrotrends · Robert Shiller · FRED · S&P Global · Nasdaq · 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 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.