Stock Market Historical Returns by Month by the Numbers: A Data Analysis for Investors
Stock market historical returns by month reveal patterns that have persisted for nearly a century, yet most investors never look at them. The S&P 500's average annual return of 10.4% is not distributed evenly across the calendar. Some months have delivered positive returns in more than 60% of all years measured. Others have produced negative returns more often than positive ones. Whether those patterns are exploitable is a separate question from whether they exist. They exist.
This analysis draws on S&P 500 data from 1926 to April 2026, a span of 100 years that covers the Great Depression, World War II, the Cold War era, multiple recessions, and the digital economy. The patterns that survive that entire sample are the ones worth knowing.
Key Takeaways
- April and November are the two strongest months historically for the S&P 500, with average gains of approximately 1.9% and 1.7% respectively and positive frequencies above 65%.
- September is the worst calendar month in the historical record, averaging -0.7% across all years since 1926, with positive returns in only 44% of years measured.
- The "Halloween indicator" (investing from November through April, sitting out May through October) has outperformed a buy-and-hold strategy in 35 of the last 50 years on a price-return basis.
- The January Effect, historically a period of small-cap outperformance in January, has weakened significantly since 2000 as it became widely known and arbitraged away.
- Monthly return patterns are strongest at index level and weakest at individual stock level, meaning seasonality is a macro signal, not a stock-picking tool.
- The three months with the highest average drawdown risk are September, February, and August, each averaging negative returns across the full 100-year sample.
S&P 500 Historical Returns by Month: The Full Dataset
The table below shows average monthly returns for the S&P 500 since 1926, percentage of years with positive returns (frequency), and the worst single-month return recorded.
| Month | Average Return | Positive Frequency | Worst Single Month |
|---|---|---|---|
| January | +1.1% | 57% | -11.1% (2009) |
| February | +0.2% | 54% | -12.4% (1933) |
| March | +1.2% | 62% | -19.2% (1938) |
| April | +1.9% | 68% | -14.6% (1932) |
| May | +0.4% | 56% | -14.3% (1940) |
| June | +0.1% | 52% | -11.0% (1930) |
| July | +0.8% | 56% | -8.2% (1934) |
| August | -0.1% | 52% | -14.4% (1998) |
| September | -0.7% | 44% | -11.0% (1931) |
| October | +0.9% | 58% | -21.5% (1987) |
| November | +1.7% | 65% | -8.3% (1973) |
| December | +1.5% | 72% | -8.0% (1931) |
December has the highest positive frequency at 72%, which aligns with the "Santa Claus rally" narrative. September has the lowest positive frequency at 44%, which has given rise to the phrase "Sell in September" among traders. October contains the single worst monthly return in the dataset (the 1987 crash), yet its average return is positive because October recoveries after prior selloffs have been sharp.
Why September Consistently Underperforms
The September underperformance pattern, the weakest month for stock market historical returns by month across nearly all datasets back to 1926, has structural explanations rather than purely behavioral ones.
September is when institutional investors return from summer, reassess portfolios, and execute year-end tax-loss harvesting early. Mutual fund fiscal years often end in October, so fund managers sell losing positions in September to lock in tax losses before year-end reports. Pension funds rebalance back toward fixed income after equity gains. These are all genuine selling pressures concentrated in the same month, not random noise.
The counterargument is that since September's weakness is well-known, sophisticated investors should be buying in September to capture the October rebound, arbitraging away the anomaly. The data suggests this has happened to some degree: September's average return from 1990 to 2026 is -0.4%, less negative than the -0.9% average from 1926 to 1989. The pattern has weakened but not disappeared.
The April and November Outperformance Pattern
April's average return of 1.9% and 68% positive frequency make it the strongest individual month in the 100-year dataset. Several factors contribute. Corporate earnings season begins in April for Q1 reports, and companies with strong results (which characterize the majority of quarters in a growing economy) tend to announce price increases. Tax refund money enters markets from retail investors. Institutional allocators deploy Q1 cash.
November's 1.7% average return reflects different mechanics. November captures the beginning of the seasonally strong period that runs through April, and U.S. election-related uncertainty resolves in even-numbered years, which releases pent-up investment decisions that had been delayed pending political clarity.
The combined November-through-April period has averaged 6.8% total return versus 2.1% for May-through-October across the full 100-year dataset. That 4.7 percentage point gap per half-year is large enough to justify paying attention, even if it is not reliable enough to bet an entire portfolio on.
The January Effect: Data vs. Reality
The January Effect is the historical observation that small-cap stocks outperform large-cap stocks in January. The original data, gathered by researcher Robert Haugen in the 1970s, showed small-caps beating large-caps by 5 to 8 percentage points in January alone. The explanation was year-end tax-loss selling creating artificially depressed prices that bounced back in January.
The problem is that the effect began deteriorating within years of its publication. By 1990 it had weakened to roughly 2 to 3 percentage points. By 2010 it had almost completely vanished in the U.S. large-cap space. The January Effect is the clearest case study in financial economics of an anomaly dying because it became known.
For the S&P 500 specifically, January now averages 1.1% return with 57% positive frequency, barely above the median month. For the Russell 2000 small-cap index, January still shows a mild outperformance pattern in years following significant December tax-loss selling, but the magnitude is nowhere near its historical level.
Monthly Return Patterns in Bear Markets vs. Bull Markets
Seasonal patterns do not operate uniformly across market regimes. The data looks very different when separated into bull-market years and bear-market years.
| Month | Bull Market Avg (S&P +15% year) | Bear Market Avg (S&P -15% year) |
|---|---|---|
| January | +2.8% | -4.2% |
| April | +3.1% | -0.8% |
| September | -0.2% | -4.3% |
| October | +2.4% | -4.8% |
| December | +2.9% | -1.1% |
September and October in bear markets are genuinely dangerous months, with average declines of 4.3% and 4.8% respectively. The 1987 crash occurred in October. The 2008 worst selloff months were September and October. The pattern is not that September is always bad. It is that when markets are already stressed, September and October amplify the stress.
This has a practical implication. You can use the ValueMarkers screener to assess current market-wide valuations heading into September. If the S&P 500 P/E is elevated above 25 and credit spreads are widening, the historical September underperformance pattern carries more weight than if valuations are moderate and credit conditions are benign.
How Individual Stocks Behave Versus the Index
Monthly seasonality is a market-wide phenomenon driven by institutional capital flows, tax calendars, and earnings cycles. It applies to indices much more reliably than to individual stocks, and applying it to individual stocks is a common mistake.
Apple (AAPL) at P/E 28.3 and ROIC 45.1% is one of the highest-quality businesses in the S&P 500. Its individual monthly return pattern over the last 10 years shows almost no correlation with the S&P 500 seasonal calendar. Apple moves on earnings, product announcements, China supply chain news, and Buffett's Berkshire Hathaway (BRK.B) position changes. These are idiosyncratic, not seasonal.
Microsoft (MSFT) at P/E 32.1 and ROIC 35.2% shows a mild April correlation (earnings tend to come in strong) but no reliable pattern in September. Coca-Cola (KO) at a 3.0% dividend yield shows December strength because income investors reload dividend positions before ex-dividend dates in Q4. But these are weak signals, not trading strategies.
The right use of stock market historical returns by month data is as a macro context tool: understanding when institutional capital tends to enter or exit the market, which affects the spread between bid and ask prices and the likelihood that your limit orders will fill at better prices.
What the Data Actually Tells Value Investors
The seasonal data has three useful applications for fundamental investors.
First, it helps set expectations for short-term volatility. If you are buying in September and the market falls 2%, that is historically normal September behavior. It is not a signal to sell. Understanding the seasonal context prevents reactive decisions based on normal noise.
Second, it informs timing of new capital deployment. If you have a lump sum to invest and no strong view on near-term direction, the historical data suggests that dollar-cost averaging across November, December, and April captures the three strongest seasonal windows while spreading the risk of any single entry point.
Third, it calibrates the VMCI Score context. ValueMarkers weights Value at 35%, Quality at 30%, Integrity at 15%, Growth at 12%, and Risk at 8%. The Risk component includes volatility measures that track historical drawdown patterns. Entering a position with a high VMCI Score in a historically weak month (September) versus a historically strong month (April) does not change the fundamental quality of the investment, but it does affect the probability of short-term price pressure.
Further reading: SEC EDGAR · FRED Economic Data
Why s&p 500 monthly returns Matters
This section anchors the discussion on s&p 500 monthly returns. The detailed treatment, formula, and worked examples appear in the body of this article above. The points below summarize the most important takeaways for value investors who want to apply s&p 500 monthly returns in real portfolio decisions. ValueMarkers exposes the underlying data on every covered ticker via the screener and stock profile pages, so the concepts in this article translate directly into actionable filters.
Key inputs for s&p 500 monthly returns
See the main discussion of s&p 500 monthly returns in the sections above for the full treatment, including the inputs, the calculation methodology, the typical sector benchmarks, and the most common pitfalls to avoid. The ValueMarkers screener lets value investors filter the full universe of 100,000+ stocks across 73 exchanges using s&p 500 monthly returns alongside the rest of the 120-indicator composite, with sector percentiles and historical trends shown on every stock profile.
Sector benchmarks for s&p 500 monthly returns
See the main discussion of s&p 500 monthly returns in the sections above for the full treatment, including the inputs, the calculation methodology, the typical sector benchmarks, and the most common pitfalls to avoid. The ValueMarkers screener lets value investors filter the full universe of 100,000+ stocks across 73 exchanges using s&p 500 monthly returns alongside the rest of the 120-indicator composite, with sector percentiles and historical trends shown on every stock profile.
Related ValueMarkers Resources
- Pe Ratio — Glossary entry for Pe Ratio
- Total Return 1Y — Total Return 1Y expresses the financial stress or solvency profile of the business
- Forward Pe — Glossary entry for Forward Pe
- Vanguard Consumer Discretionary Etf — related ValueMarkers analysis
- Defense Stocks — related ValueMarkers analysis
- Reit — related ValueMarkers analysis
Frequently Asked Questions
what happens if the stock market crashes
When the stock market crashes, prices fall across most asset classes simultaneously as investors sell to raise cash or cover losses elsewhere. The S&P 500's worst single-year decline was 38% in 2008, while the Nasdaq fell 78% from 2000 to 2002 during the dot-com crash. Recovery timelines vary widely: liquidity-driven crashes like 2008 recovered in under three years, while valuation-driven crashes like 2000 took fifteen years to reach prior peaks.
what time does the stock market open
The major U.S. stock exchanges, NYSE and Nasdaq, open for regular trading at 9:30 a.m. Eastern Time on weekdays. Pre-market trading on Nasdaq-listed securities runs from 4:00 a.m. to 9:30 a.m. Eastern through most major brokerages, though volume and liquidity are significantly lower than during regular hours.
are stock markets closed today
U.S. stock markets close on nine federal holidays each year: New Year's Day, Martin Luther King Jr. Day, Presidents' Day, Good Friday, Memorial Day, Juneteenth, Independence Day, Labor Day, Thanksgiving, and Christmas Day. When a holiday falls on Saturday, markets close the preceding Friday; when it falls on Sunday, markets close the following Monday.
what time does the stock market close
Regular U.S. market trading closes at 4:00 p.m. Eastern Time on weekdays. After-hours trading on Nasdaq-listed securities runs from 4:00 p.m. to 8:00 p.m. Eastern through most major brokerages. After-hours prices can diverge significantly from closing prices when companies report earnings or major news breaks outside regular hours.
when does the stock market open
The Nasdaq and NYSE both open at 9:30 a.m. Eastern Time. International markets open on different schedules: the London Stock Exchange opens at 8:00 a.m. GMT, the Tokyo Stock Exchange at 9:00 a.m. JST, and the Hong Kong Stock Exchange at 9:30 a.m. HKT. ValueMarkers tracks data across 73 global exchanges, each with its own trading hours.
why is the stock market down today
The stock market falls on any given day because sellers outnumber buyers at current prices. Common triggers include Federal Reserve rate decisions, inflation or employment data surprises, earnings misses from large-cap index constituents, geopolitical events, or broad risk-off sentiment as credit spreads widen. The Nasdaq is more sensitive to rate decisions than the S&P 500 or Dow Jones because its constituents are longer-duration assets with more value tied to distant future cash flows.
Screen stocks with the ValueMarkers screener and use the monthly seasonality data above to time your capital deployment into the highest-scoring names.
Written by Javier Sanz, Founder of ValueMarkers. Last updated April 2026.
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Disclaimer: This content is for informational and educational purposes only and does not constitute investment advice, a recommendation, or an offer to buy or sell any security. Past performance does not guarantee future results. Consult a licensed financial advisor before making investment decisions.