SPY is the world's most-traded ETF — and its seasonal patterns are some of the most studied in finance. Year-end rallies, September weakness, and summer slowdowns aren't random. They're structural.
Explore SPY's recurring calendar patterns with 20+ years of data. Screen, chart, and backtest every seasonal window.
20-Year Seasonality Profile
Watch the workflow before exploring the use case: discovery, validation, and execution planning in one clear process.
20Y+
Data Depth
Daily resolution
Nov
Best Month
+2.4% avg return
Sep
Worst Month
-1.5% avg return
82%
Year-End Win Rate
Nov–Dec window
SPY is more than an ETF — it's the default barometer for the US equity market. Understanding its calendar tendencies gives you a practical edge.
SPY tracks the S&P 500 — 500 of the largest US companies. Its seasonality reflects the aggregate rhythm of the entire equity market.
With $400B+ in assets and massive daily volume, SPY seasonal patterns are tradable with minimal slippage — even in options.
Use SPY seasonality as a timing overlay. When the calendar favors SPY historically, it favors broad market exposure.
SPY's deep options chain means seasonal tendencies can be expressed as defined-risk trades with precise entry/exit timing.
SPY seasonality behaves differently in bull vs. bear markets. The backtest tool lets you filter by regime to see which patterns survive stress.
Every seasonal window can be backtested with full trade-by-trade results. No guessing — see the equity curve, drawdown, and win rate.
The composite annual curve shows how SPY typically moves through the year. The pattern is clear: strength in Q1 and Q4, weakness in late summer.
20-Year Cumulative Average
Each month has a distinct character. Here's what 20 years of data tells us about SPY's calendar personality.
New-year allocation flows and January effect push SPY higher. Historically positive but volatile.
Post-January cooldown. Often a consolidation month before spring momentum.
Quarter-end rebalancing and fiscal year-end flows for some funds. Mixed but slight positive bias.
Tax refund flows and fresh Q2 allocations. One of SPY's most reliably positive months.
The 'weaker half' of the year. Summer liquidity gaps, vacation-mode trading, and lower conviction create sideways-to-weak action.
The notorious 'worst month.' Mutual fund fiscal year-ends, back-from-summer repositioning, and Q3 anxiety converge.
Historically volatile but often marks the seasonal bottom. October selloffs frequently set up the year-end rally.
The start of SPY's golden season. Thanksgiving rally, holiday spending optimism, and institutional positioning begin.
Santa Claus rally, window-dressing, and year-end pension inflows. The seasonal strength continues through year-end.
SPY isn't the only way to play broad market seasonality. Here's how its calendar profile compares to other major proxies.
QQQ amplifies SPY's seasonal moves due to tech concentration. QQQ tends to rally harder in November and fall harder in September. Higher beta, same rhythm.
Small-cap IWM has a stronger January effect than SPY but weaker mid-year performance. The December–January window is where IWM often outperforms.
DIA tracks the Dow 30 — more industrials, fewer tech names. Its seasonality is similar to SPY but slightly less volatile and with different sector weighting effects.
SPY's strongest seasonal window. Driven by holiday spending, Santa Claus rally, pension rebalancing, and institutional window-dressing. 82% win rate over 20 years.
Tax refund flows, post-Q1 earnings optimism, and fresh quarterly allocations typically push SPY higher in April.
Historically the weakest month for SPY. Mutual fund fiscal year-ends, post-summer liquidity gaps, and Q3 positioning anxiety converge.
The broader year-end seasonal complex — starting from late October lows and running through early January — captures the full institutional rebalancing cycle.
Observing a seasonal tendency is just the beginning. Here's what serious traders validate before acting on SPY seasonality.
Does the year-end rally hold in bear markets?
Filter backtests by market regime. The Nov–Dec rally has historically been weaker but still positive during most bear years.
Is the September effect fading?
Run a rolling-window backtest to see if September weakness is consistent or declining over recent decades.
What's the optimal entry for the year-end rally?
Test different start dates (Oct 15, Nov 1, Nov 15) to find where the risk-adjusted return peaks.
Does SPY seasonality work in options?
Compare a long-SPY seasonal trade vs. a call spread or put sale during the same window. The backtest tool supports direction-neutral analysis.
You've seen SPY's seasonal blueprint. Now move from observation to validated action inside the platform.
Scan all SPY seasonal windows ranked by win rate, average return, and profit factor. Filter by direction and timeframe to find the windows that match your trading style.
Open Screener Step 2Run the Nov 1 – Dec 31 long pattern through the backtest engine. See the equity curve, every individual trade, max drawdown, and whether the pattern survived 2008 and 2020.
Run Backtest Step 3Overlay seasonal profiles of SPY against other market proxies. Spot where they converge — and where divergence creates relative value opportunities.
Compare Proxies Step 4Combine validated SPY seasonal windows with patterns from other markets into a diversified seasonal portfolio with aggregate risk metrics.
Build StrategyAll SPY windows ranked by consistency, return, and risk profile.
| Asset | Window | Dir | Win Rate | Avg Ret | Max DD | PF |
|---|---|---|---|---|---|---|
| SPY | Nov 1 – Dec 31 | Long | 82% | +3.8% | -4.2% | 2.4 |
| SPY | Apr 1 – Apr 30 | Long | 76% | +2.1% | -3.1% | 1.9 |
| SPY | Jul 1 – Jul 31 | Long | 74% | +1.8% | -3.8% | 1.7 |
| SPY | Oct 28 – Jan 5 | Long | 85% | +4.2% | -5.0% | 2.6 |
| SPY | Sep 1 – Sep 30 | Short | 68% | +1.9% | -3.8% | 1.5 |
| SPY | May 1 – Oct 31 | Short | 55% | +0.8% | -8.5% | 1.1 |
82%
Win Rate
+3.8%
Avg Return
20Y
History
76%
Win Rate
+2.1%
Avg Return
20Y
History
74%
Win Rate
+1.8%
Avg Return
20Y
History
68%
Win Rate
+1.9%
Avg Return
20Y
History
85%
Win Rate
+4.2%
Avg Return
20Y
History
60%
Win Rate
+1.2%
Avg Return
20Y
History
Screen, chart, and backtest SPY seasonal patterns — then build them into validated portfolio strategies.