Markets exhibit seasonal patterns that recur year after year. While no pattern works 100% of the time, understanding seasonality can give traders an edge by identifying periods of historically stronger or weaker returns. Since 1950, the S&P 500 has gained an average of 7.1% from November through April, compared to just 1.9% from May through October.
What Is Market Seasonality?
Market seasonality refers to the tendency of stocks to perform differently at various times of the year. These patterns emerge from a combination of factors: institutional fund flows, tax considerations, earnings cycles, and collective investor psychology. While past performance does not guarantee future results, seasonal patterns have persisted for decades.
Key statistic: According to the Stock Trader's Almanac, the S&P 500 has risen in November 68% of the time since 1950, making it one of the most reliable bullish months. September, by contrast, is the worst month historically with an average decline of -0.5%.
Monthly Seasonality Patterns
Best Months (November - April)
- November: +1.7% average, 68% positive (best month)
- December: +1.5% average, 74% positive (Santa Claus rally)
- January: +1.2% average, 62% positive (January effect)
- April: +1.5% average, 70% positive (strong earnings)
Worst Months (May - October)
- September: -0.5% average, 45% positive (worst month)
- June: +0.1% average, 53% positive
- August: +0.1% average, 55% positive
- February: +0.1% average, 55% positive
Major Seasonal Patterns
The Best Six Months (November - April)
This pattern, popularized by Yale Hirsch, shows that most stock market gains occur between November and April:
- November-April average: +7.1% since 1950
- May-October average: +1.9% since 1950
- Win rate: November-April positive 77% of the time
- Strategy: Be fully invested November-April, reduce exposure May-October
The January Barometer
As January goes, so goes the year. When January is positive, the market tends to be positive for the full year:
- Positive January: Year ends positive 87% of the time
- Negative January: Year ends positive only 57% of the time
- Average gain when January up: +13.4%
- Average gain when January down: +1.3%
September Effect
September has been the worst month for stocks historically:
- Average return: -0.5% since 1950
- Positive years: Only 45% of the time
- Major crashes: 1929, 2001, 2008 all had September declines
- Theory: Post-vacation selling, mutual fund fiscal year-end
Holiday Trading Patterns
Pre-Holiday Effect
The trading day before major holidays tends to be bullish:
- Day before Thanksgiving: +0.35% average
- Day before Independence Day: +0.32% average
- Day before Christmas: +0.30% average
- Why: Short covering, positive sentiment, light volume
Post-Holiday Effect
- First trading day after long weekends often volatile
- Tuesday after holiday weekends: mixed results
- Consider reduced position sizes around holidays
Day-of-Week Patterns
Historical Day-of-Week Returns
- Monday: -0.08% average (worst day historically)
- Tuesday: +0.03% average
- Wednesday: +0.08% average
- Thursday: +0.05% average
- Friday: +0.09% average (best day historically)
Weekend Effect
The tendency for stocks to decline on Mondays:
- Bad news often released over weekends
- Retail investors sell after weekend reflection
- Pattern has weakened in recent decades
- Still evident in some international markets
Options Expiration Patterns
Triple Witching
Third Friday of March, June, September, December when stock options, index options, and index futures expire simultaneously:
- Increased volatility and volume
- Large price swings possible
- Pin risk near strike prices
- Often followed by pullback the next week
Monthly Options Expiration
- Week of expiration tends to be bullish
- Max pain theory: stocks gravitate toward strikes with most open interest
- Volatility often decreases after expiration
Quarter-End Patterns
Window Dressing
Institutional investors buy winners and sell losers at quarter-end to make portfolios look good:
- Last week of quarter: buying pressure in winners
- First week of new quarter: often reversal
- Strongest effect in Q4 (year-end)
Earnings Season Patterns
- Earnings seasons (Jan, Apr, Jul, Oct) bring increased volatility
- Market often rallies into earnings season
- Sell the news effect common after reports
How to Trade Seasonal Patterns
Combining Seasonality with Technical Analysis
- Use seasonality as a tailwind, not the sole reason to trade
- Look for technical confirmation of seasonal patterns
- Better entries when technicals align with seasonal bias
- Avoid fighting strong seasonality without good reason
Risk Management
- Reduce position sizes during historically weak periods
- Tighter stops during September volatility
- Be aware of holiday liquidity issues
- Do not rely solely on seasonal patterns
Track Your Seasonal Trading Performance
Pro Trader Dashboard helps you analyze how your trades perform across different seasons and months.
Summary
Seasonal trading patterns offer a statistical edge that can improve your trading results when used properly. The key patterns to remember: November through April tends to outperform May through October; September is historically the worst month; and pre-holiday trading days tend to be bullish. However, seasonality should be used as one tool among many - combine it with technical and fundamental analysis for best results. Remember that patterns can fail, especially in unusual market environments, so always use proper risk management.
Learn more about specific seasonal patterns: Sell in May, January Effect, and Santa Claus Rally.