Day TradingUpdated daily after close · as of 2026-06-26
Stock Market Seasonality: SPY & QQQ Average Returns by Month
How the S&P 500 (SPY) and Nasdaq-100 (QQQ) have traded by calendar month and across the average trading year — full history, the past 20 years and the past 10 years, with win rates. A base-rate tendency measured over decades, not a forecast.
The reading · SPY
Since 1993, the strongest calendar month for the S&P 500 (SPY) has been November (+2.44% average) and the weakest September (-0.90%). June — the current month — has averaged -0.03% with a 53% positive rate across 34 years. Seasonality is a base-rate tendency measured over decades, not a forecast for any single year.
Source
SPY (1993–present) & QQQ (1999–present) daily closes from our price database
Methodology
Month-end-to-month-end returns by calendar month over full / 20Y / 10Y; seasonal path = each year normalized to prior year-end, averaged across the window
Updates
Daily after US market close (~1pm PT)Last: 2026-06-26
Maintained & reviewed by Yuriy Matso — methodology shown on the page.
Current monthSPY · 2026-06-26
Jun
-0.0%
June avg · 53% positive over 34 years
Best month
Nov
+2.4%
Worst month
Sep
-0.9%
Best 6mo
Nov–Apr
Strongest stretch of the year has historically been November through April; the “worst six months” (May–October) sit behind the “sell in May” adage. SPY daily (1993–present).
Symbol:S&P 500 (SPY)
01
Average return by month — S&P 500 (SPY)
The average return for each calendar month, compared across three lookbacks. The shaded column is the current month (June). Watch whether a month is strong across all three windows (structural) or only recently (a newer regime).
Full history Past 20Y Past 10Y
02
The average trading year — S&P 500 (SPY)
Each year's cumulative return, normalized to the prior year-end and averaged across the window — the shape of a typical year. The green band marks the current month.
Window:20 years averaged
03
Monthly statistics — S&P 500 (SPY)
| Month | Full avg | Full win% | 20Y avg | 10Y avg | Years |
|---|---|---|---|---|---|
| January | +0.76% | 61% | +0.27% | +2.11% | 33 |
| February | -0.02% | 52% | +0.15% | -0.40% | 33 |
| March | +0.54% | 59% | +0.53% | -1.22% | 34 |
| April | +1.96% | 74% | +2.45% | +2.20% | 34 |
| May | +1.21% | 74% | +1.18% | +2.02% | 34 |
| June(current) | -0.03% | 53% | -0.33% | +1.20% | 34 |
| July | +1.48% | 64% | +2.67% | +3.51% | 33 |
| August | -0.04% | 64% | +0.23% | +1.16% | 33 |
| September | -0.90% | 52% | -0.99% | -1.73% | 33 |
| October | +1.68% | 64% | +1.01% | +1.07% | 33 |
| November | +2.44% | 76% | +2.35% | +4.38% | 33 |
| December | +0.46% | 64% | +0.17% | -0.41% | 33 |
Strongest: November (+2.44%). Weakest: September (-0.90%).
How Stock Market Seasonality Works
- 1Compute a return for every calendar monthFrom each symbol's daily history we take month-end closing prices and measure the return from one month-end to the next. SPY history goes back to 1993 and QQQ to 1999, giving 30+ and 25+ observations for each calendar month.
- 2Average each month over three lookbacksFor every calendar month we report the average return and win rate (% of years positive) over the full history, the trailing 20 years and the trailing 10 years. Comparing the three reveals whether a seasonal tendency is structural or has only shown up recently.
- 3Build the average seasonal pathFor each year we normalize the close to the prior year-end and track the cumulative return through the year, then average those paths across every year in the selected window (10, 15, 20 years or all history). The result is the shape of a typical trading year — the slow summer, the autumn dip, the year-end rally.
- 4Mark the current monthBoth charts highlight the calendar month you are in now, so you can read this month's historical tendency at a glance — its average return, its win rate, and where it sits on the average year's path.
Who Uses Stock Market Seasonality
Swing Traders
Frame entries and exits with the calendar. Knowing that November has been the strongest month and September the weakest — and how strong the tendency is over the last decade — adds context to a position you are sizing.
Long-Term Investors
Sanity-check timing decisions. The "best six months" (Nov–Apr) vs "worst six months" (May–Oct) split behind "sell in May" is visible directly in the seasonal path.
Systematic Traders
A clean base rate for calendar filters. Test whether a monthly tendency is stable across the full / 20Y / 10Y windows before wiring it into a rule.
Skeptics
See the sample size next to every average. A 100%-positive month over 10 years is only ten observations — the tool keeps the counts in view so you can weigh them honestly.
Pro Tips
01
Compare the three windows
A month that is strong across full history, 20Y and 10Y is a structural tendency; one that only shows up in the 10Y column may be a recent regime, not a rule. Watch how the bars line up.
02
Read the average path, not just the months
The seasonal path shows the journey — flat-to-down summers, the late-September weakness, and the November–December rally — which the month-by-month bars alone can hide.
03
Average hides the spread
A +1.5% average month can still be down hard in any single year. Seasonality is a tendency across decades, not a forecast; pair it with the win rate to see how reliable the average is.
04
QQQ swings harder than SPY
The Nasdaq-100 amplifies the same seasonal shape — bigger best months and deeper worst months — because it is more concentrated and higher-beta. Toggle between the two to compare.
Common Issues & Solutions
Can I trade on seasonality alone?▾
No. Seasonality is context, not a signal. Averages mask wide year-to-year variation, and a strong macro or news regime overrides the calendar. Use it alongside trend, breadth and valuation.
Why does the path end in December near +10%, not the index's actual return?▾
The path is the average of every year's normalized cumulative return, so it reflects the typical year — not any single year and not the compounded multi-decade return. It is a shape, not a price target.
Why is the current month's average based on fewer years?▾
The 10-year and 20-year columns use only the most recent years, so their sample counts are 10 and 20. The full-history column uses every year since 1993 (SPY) or 1999 (QQQ).
Why SPY and QQQ specifically?▾
They are the canonical S&P 500 and Nasdaq-100 proxies with long, clean daily histories — the two indices most traders benchmark against. The same method extends to any symbol with enough history.
Frequently Asked Questions
What is stock market seasonality?▾
Seasonality is the tendency for returns to follow recurring calendar patterns — certain months or parts of the year that have, on average, been stronger or weaker than others. It is a base-rate tendency measured over decades, not a guarantee for any single year.
Which months are historically best and worst for the S&P 500?▾
Over the full SPY history since 1993, November has been the strongest calendar month and September the weakest on average. The "best six months" (November–April) have historically outperformed the "worst six months" (May–October) — the basis of the "sell in May" adage.
How is the seasonal path calculated?▾
For each year we normalize the close to the prior year-end and track the cumulative return through the year, then average those paths across every year in the selected window (10, 15, 20 years or all history). The result is the shape of a typical trading year — not a forecast.
Does QQQ have the same seasonality as SPY?▾
The Nasdaq-100 (QQQ) follows a broadly similar seasonal shape but with larger swings — stronger best months and deeper worst months — because it is more concentrated and higher-beta than the S&P 500. The tool lets you toggle between the two.
Can I trade on seasonality alone?▾
No. Seasonality is context, not a signal. Averages hide wide year-to-year variation, and a strong macro or news regime overrides the calendar. Use it alongside trend, breadth and valuation rather than in isolation.
How often is it updated?▾
Daily after the US market close, from the same SPY and QQQ price history that powers the rest of the site. All statistics reflect data through the most recent close.
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Last updated: 2026-06-26