Major indices like the S&P 500, Nasdaq, and DAX don't move randomly through the year. They follow recurring seasonal rhythms shaped by institutional flows, economic cycles, and calendar effects.
Understand the broad market pulse before zooming into individual stocks. Index seasonality gives you the macro context for every trading decision.
20-Year Composite Average
Watch the workflow before exploring the use case: discovery, validation, and execution planning in one clear process.
25+
Global Indices
US, Europe, Asia, Emerging
20Y+
Data Depth
Per index
4
Seasonal Layers
Annual · Monthly · Weekly · Intraday
✓
One-Click Backtest
Any window, any index
Each index has its own seasonal fingerprint. Compare them to see where they align and where they diverge.
20-Year Seasonality Profile
Before trading any stock or sector, understand the seasonal backdrop. Is the broad market historically strong or weak in this period?
SPY and QQQ don't always move together seasonally. Finding where they diverge reveals rotation and relative-value opportunities.
US, European, and Asian indices have different seasonal drivers. Comparing them shows where global flows create seasonal edges.
September and October are historically volatile for most indices. Knowing this helps you manage exposure and position sizing.
Index seasonality is often the first filter in a quantitative strategy. Start with the broad market, then drill into sectors and stocks.
If you trade relative to a benchmark, understanding its seasonal tendencies tells you when the benchmark itself is likely to move.
Not all indices follow the same calendar. Different regions, different fiscal calendars, and different investor bases create unique seasonal fingerprints.
The world's most-watched index. Year-end seasonality is remarkably consistent. September weakness is the most reliable seasonal bearish signal.
Amplified S&P seasonality due to tech concentration. Larger November rallies, deeper September drops. Growth sentiment swings are sharper.
European fiscal calendar and ECB meeting schedule create distinct seasonal inflection points. Strong April driven by European fund allocations.
The strongest January effect of any major index. Small caps respond more dramatically to year-end tax-loss selling and January rebalancing.
Japanese fiscal year-end (March 31) and Golden Week create unique seasonal patterns not seen in Western indices.
UK fiscal year (April 6) creates distinct seasonal flows. The FTSE also has commodity-linked seasonality due to mining stock weighting.
The most consistently bullish seasonal window across global indices. Driven by Santa Claus rally, January effect, and institutional rebalancing.
Historically weaker six months. Not necessarily negative, but returns are significantly lower and volatility often higher.
September is historically the weakest month for most indices. October often sees sharp selloffs but also marks bottoms.
Fresh allocations, new-year optimism, and fund rebalancing tend to push indices higher in the first quarter.
All major global indices — screened for seasonal edge, ranked by consistency.
| Asset | Window | Dir | Win Rate | Avg Ret | Max DD | PF |
|---|---|---|---|---|---|---|
| SPY | Nov 1 – Dec 31 | Long | 82% | +3.8% | -4.2% | 2.4 |
| QQQ | Oct 15 – Dec 20 | Long | 80% | +5.2% | -5.8% | 2.1 |
| DAX | Nov 1 – Jan 15 | Long | 77% | +4.1% | -5.5% | 1.8 |
| IWM | Dec 1 – Jan 31 | Long | 78% | +4.8% | -6.2% | 1.9 |
| SPY | Sep 1 – Sep 30 | Short | 68% | +1.9% | -3.8% | 1.5 |
| EEM | Jan 15 – Mar 31 | Long | 70% | +3.5% | -5.0% | 1.6 |
82%
Win Rate
+3.8%
Avg Return
20Y
History
80%
Win Rate
+5.2%
Avg Return
20Y
History
77%
Win Rate
+4.1%
Avg Return
20Y
History
73%
Win Rate
+3.2%
Avg Return
20Y
History
71%
Win Rate
+3.9%
Avg Return
20Y
History
78%
Win Rate
+4.8%
Avg Return
20Y
History
Seasonality360 takes you from a raw seasonal observation to a backtested, portfolio-ready edge — in one integrated workflow.
Step 1
Scan thousands of seasonal patterns across markets, timeframes, and calendar windows.
Step 2
Read seasonality charts, monthly returns, and historical consistency at a glance.
Step 3
Backtest any pattern with real historical data — equity curves, drawdowns, trade-by-trade.
Step 4
Combine validated patterns into diversified portfolios with aggregate risk metrics.
Chart, screen, and backtest seasonal patterns across 25+ global indices — with one integrated platform.