S&P 500 Seasonality: Can The First Six Months Predict Performance Of ES Futures?

How Are S&P 500 Returns Distributed Throughout the Year? It is well known that the S&P 500, like US equity indexes more broadly, has a strong long-term bullish bias.

What is less well understood is how this upward tendency is distributed throughout the year.

To explore this question, we can use Bias Finder, our proprietary analysis software, which allows us to examine the behavior of individual markets across different time horizons, including the full 365-day calendar year.

In this case, we want to determine whether E-mini S&P 500 futures (@ES) exhibit seasonal windows that are more profitable than others and, more importantly, whether these windows are connected in some way.

Figure 1 shows the average annual performance of E-mini S&P 500 futures.

Three particularly significant periods are highlighted: the red box marks the seasonal window running from the beginning of the year through the end of June, the green box represents the second half of the year, from July through December, and the blue box covers the period from approximately the second week of October through year-end.

Figure 1 — Average annual performance of E-mini S&P 500 futures and the main seasonal windows analyzed.

At first glance, beyond the underlying bullish bias shared by all the periods analyzed, the second half of the year appears to be generally more bullish than the first, with particularly strong acceleration during the fourth quarter.

This raises an interesting question: could there be a relationship between these seasonal windows that might allow us to outperform a simple buy-and-hold approach? For example, if the market delivers a positive performance during the first six months of the year, does this have any implications for the months that follow? In other words, does the market exhibit a kind of memory effect that could provide useful guidance for the remainder of the year? The Three Seasonal Windows Analyzed on E-mini S&P 500 Futures To answer this question, we will begin by testing the actual performance of the three seasonal windows identified above.

For each window, we will assume that a long position is opened in the futures contract and held for the entire period.

For comparison purposes, we will also test a simple buy-and-hold approach, defined as buying the futures contract at the beginning of January and selling it one year later, for each year included in the backtest: Annual Buy & Hold Enter long on the first trading day of the calendar year and exit on the first trading day of the following year.

Seasonal Window No.

1 — January through June — 6 months Enter long on the first trading day of the year and exit on the first trading day of the second half of the year.

Seasonal Window No.

2 — July through December — 6 months Enter long on the first trading day of the second half of the year and exit on the first trading day after year-end.

Seasonal Window No.

3 — October through December — 3 months Enter long on October 10, or on the first trading day after October 10 if the market is closed, and exit on the first trading day after year-end.

The tests use historical data from 2000 through 2026, analyzed on daily bars.

Top left: Buy and Hold.

Top right: Seasonal Window No.

1, from January through June.

Bottom left: Seasonal Window No.

2, from July through December.

Bottom right: Seasonal Window No.

3, from October through December.

Figure 2 — Equity curves for the buy-and-hold approach and the three seasonal windows.

First Half vs.

Second Half: What Does the Backtest Reveal? Looking at the results shown in Figure 2, we can see that the equity curves for all three seasonal windows are consistent with the patterns identified by Bias Finder.

All three generated positive net profits, but performance improved as we moved toward the seasonal windows in the second half of the year.

Nearly all metrics improved, particularly maximum drawdown.

In fact, when moving from the first six-month window to the final three-month window, from October through December, the maximum drawdown was reduced by more than half, while the average trade increased by nearly 50%.

This result is also reflected in the exceptionally smooth equity curve.

As expected, the Buy and Hold approach outperformed all the other alternatives in terms of net profit because of its significantly longer time in the market.

However, it was also exposed to much greater fluctuations, as demonstrated by its maximum drawdown of -$69,337.50.

This was identical to the drawdown recorded by the least favorable seasonal window, Window No.

1, covering the first six months of the year.