S&P 500
The S&P 500 index tracks 500 of the largest U.S. publicly traded companies, weighted by market capitalization. It is widely regarded as the best single gauge of the U.S. equity market.
Seasonal history makes a compelling case for patience over the next quarter. The 30-day window looks soft, with a 40% win rate and an average return of negative 1.09% across the last ten years, but the picture brightens considerably further out. At 90 days, consecutive-year data shows an 80% win rate and an average gain of 3.57%, projecting the index toward 8,975. Midterm election years reinforce that trajectory, delivering a 70.8% win rate over 90 days.
The key pattern here is the slow build. Near-term weakness is historically normal before a stronger second half emerges. Midterm years specifically tend to reward investors who hold through early volatility, with median 90-day returns of 6.12%. Watch whether the index holds current levels over the next month as the critical tell.
Seasonal Price Projections
Select a historical basis and projection horizon to see where seasonal patterns suggest S&P 500 may be headed.
Projection as of Sep 11, 2026 from closing price $7,591.70
How to Use This Data
Seasonal projection data for the S&P 500 reflects how the index has historically performed during this same calendar period across prior years. A 70.0% consecutive win rate means the index finished higher in 70 out of every 100 comparable periods, while the midterm election year pattern shows a 66.7% win rate with a median return of 4.9%.
When both the consecutive and midterm election year bases point in the same direction, the signal carries more weight than either pattern alone. Convergence suggests the tendency is consistent across different historical lenses. The median return is often more informative than the average because it is less distorted by unusually large gains or losses in outlier years.
Seasonal patterns cannot account for unexpected events such as breaking news, policy shifts, earnings surprises, or geopolitical developments. A 70.0% win rate still leaves a meaningful probability of a negative outcome, as the worst historical return in this dataset was negative 5.6%. These projections represent statistical tendencies drawn from the past, not forecasts of future results.
Seasonal data serves as one analytical lens among many. Market participants often weigh it alongside fundamental analysis, technical indicators, and broader macroeconomic context. It can help frame expectations and inform timing discussions without serving as a standalone basis for any decision.
This information is provided for educational purposes only and does not constitute financial advice, a recommendation, or a solicitation to buy or sell any security. Seasonal patterns are based on historical data and do not guarantee future performance. All investment decisions carry risk. Consult a qualified financial advisor before making investment decisions.
Understanding Seasonal Projections
Seasonal projections estimate future price movement based on how S&P 500 has historically performed during the same calendar period. These are statistical baselines derived from decades of market data, not predictions.
Consecutive Years (Last 10)
Uses the most recent 10 years of data regardless of market regime. This captures the broadest recent behavior, including all economic and political environments. Over the next 60 calendar days, this pattern has been positive 7 of 10 times with an average return of +1.8%.
Midterm Election Years (24 Available)
Uses only years that fall in the same position within the 4-year U.S. presidential election cycle. 2026 is a midterm election year. Markets often exhibit distinct patterns tied to fiscal and monetary policy shifts within this cycle. In 24 historical midterm election years, this 60-day window was positive 16 times with an average return of +2.8%.
Seasonal patterns reflect historical tendencies and do not guarantee future results. All projections are based on past performance and should be used as one input among many in your investment decision-making process. Data provided by TradeWave.ai.
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