July’s Seasonal Analysis in the S&P 500

Why July Matters for Seasonal Traders

July occupies a unique position in the seasonal calendar. It marks the start of Q3, the beginning of a major earnings season, and sits at the heart of the summer trading lull. For traders using thinkorswim indicators to track market behavior, July presents reliable patterns alongside notable traps that require careful study.

The S&P 500 has posted gains in July roughly 58% of the time since 1950, making it an above-average month. That win rate, paired with an average return of +1.2%, places July among the stronger months in the seasonal rotation. The distribution of returns within the month is uneven, and understanding these intra-month dynamics is critical for building a viable trading plan.

Historical Win Rates and Return Distribution

S&P 500 data spanning seven decades reveals that July ranks as the fifth-best performer by average returns, trailing November, April, December, and January.

The modern era win rate of nearly 63% gives seasonal traders a statistical edge when paired with proper risk management and confirmation from thinkorswim scanners.

Intra-Month Patterns: The July Roadmap

July's price action is not evenly distributed. The first five trading days carry the bulk of the month's gains, driven by the Independence Day holiday effect. This window has posted an average gain of +0.7%, accounting for more than half of July's total average return.

The middle of the month (trading days 6 through 14) brings consolidation as earnings season ramps up. Volatility increases as major financial names report, and the market digests corporate guidance.

The final week delivers a secondary push higher, powered by positive earnings surprises from mega-cap technology companies. This late-month rally has become more pronounced as mega-cap tech has grown to dominate index weightings.

Earnings Season Impact on July Volatility

Roughly 35% to 40% of S&P 500 companies report during the last two weeks of July. This creates a distinctive pattern where implied volatility builds through mid-month and collapses rapidly after major reports are released.

The VIX typically trades between 13 and 17 during July, with an average near 14.8. Intra-month VIX swings of 3 to 5 points are common as the market transitions from the calm pre-holiday period into the earnings volatility window. Tracking VIX term structure using the Volatility Box provides additional context for timing entries during these transitions.

Sector Rotation Patterns in July

Technology and Consumer Discretionary lead during July, driven by earnings catalysts and seasonal consumer spending. Defensive sectors underperform as risk-on sentiment favors growth. Use thinkorswim scanners to filter for high relative strength stocks within the leading sectors.

ThinkOrSwim Seasonal Overlay for July

This ThinkScript creates a visual overlay highlighting the historically bullish and consolidation windows within July on your chart.

# July Seasonal Bias Overlay
def isJuly = GetMonth() == 7;
def dayOfMonth = GetDayOfMonth(GetYYYYMMDD());
def earlyBullish = isJuly and dayOfMonth >= 1 and dayOfMonth <= 8;
def midConsolidation = isJuly and dayOfMonth >= 9 and dayOfMonth <= 18;
def lateBullish = isJuly and dayOfMonth >= 19 and dayOfMonth <= 31;

AssignBackgroundColor(
    if earlyBullish then Color.DARK_GREEN
    else if midConsolidation then Color.DARK_ORANGE
    else if lateBullish then Color.DARK_GREEN
    else Color.CURRENT);

AddLabel(earlyBullish, "JULY EARLY BULLISH", Color.GREEN);
AddLabel(midConsolidation, "JULY CONSOLIDATION", Color.ORANGE);
AddLabel(lateBullish, "JULY EARNINGS RALLY", Color.GREEN);

Using the TTM Squeeze ThinkOrSwim Setup for July Entries

Combining seasonal bias with volatility compression signals is one of the most effective approaches for July trading. The TTM Squeeze ThinkOrSwim indicator fits naturally here because July's early-month holiday period compresses price action into tight ranges. When the squeeze releases upward during a seasonally bullish window, the resulting move tends to be clean and tradeable.

Traders who rely on the TTM Squeeze ThinkOrSwim setup should focus on the first five trading days and the final week of July. These are the windows where squeeze releases most frequently align with the seasonal directional bias.

# July Squeeze Entry Scanner
def isJuly = GetMonth() == 7;
def dom = GetDayOfMonth(GetYYYYMMDD());
def julyWindow = isJuly and (dom <= 8 or dom >= 19);

def bbUpper = BollingerBands(close, 20, 2.0).UpperBand;
def bbLower = BollingerBands(close, 20, 2.0).LowerBand;
def kcAvg = Average(TrueRange(high, close, low), 20);
def kcMid = Average(close, 20);
def kcUpper = kcMid + 1.5 * kcAvg;
def kcLower = kcMid - 1.5 * kcAvg;

def squeezeOn = bbLower > kcLower and bbUpper < kcUpper;
def squeezeRelease = !squeezeOn and squeezeOn[1];
def momentum = close - Average(close, 20);

plot signal = julyWindow and squeezeRelease and momentum > 0;
signal.SetPaintingStrategy(PaintingStrategy.BOOLEAN_ARROW_UP);
signal.SetDefaultColor(Color.CYAN);

Pair this scanner with Volatility Box levels to identify entries where squeeze releases align with expected move support and resistance.

Futures Market Behavior in July

S&P 500 futures (ES) show their own July tendencies. The ES contract trades with a slight premium into the month due to quarterly roll dynamics. July overnight sessions tend to be calmer than average, with Globex range contracting 10% to 15% versus the full-year average.

This reduced overnight volatility benefits RTH session traders, as moves initiated during regular hours tend to extend further. The Volatility Box for Futures helps adjust expected move calculations for July's compressed overnight ranges.

Combining Seasonal Analysis with Technical Confirmation

Rather than buying blindly on July 1st, use seasonal data as a directional filter and let technical indicators time the entry:

Step 1: Confirm June closed positive. July's win rate jumps to 68.7% after a green June versus roughly 47% after a red June.

Step 2: Use the TTM Squeeze ThinkOrSwim indicator to identify compression setups in the first week of July.

Step 3: Confirm momentum direction using MACD or linear regression slope. The seasonal bias provides context; momentum confirms agreement.

Step 4: Define risk using Volatility Box expected move levels. Place stops below the lower boundary and target the upper boundary.

Step 5: Scale into positions during early July and reduce exposure heading into heavy earnings week.

The Federal Reserve Factor in July

The FOMC schedule often places a decision in late July. When the Fed is neutral or dovish, July's late-month rally is amplified as earnings optimism and accommodative expectations combine. A hawkish surprise can truncate the rally and produce sharp reversals into month-end.

Seasonal traders should reduce exposure ahead of the FOMC announcement or hedge with options structures that benefit from a volatility spike.

ThinkOrSwim Scanner for July Candidates

# July Seasonal Strength Scanner
def isJuly = GetMonth() == 7;
def above50MA = close > Average(close, 50);
def above200MA = close > Average(close, 200);
def risingMomentum = Average(close, 10) > Average(close, 20);

def spyClose = close("SPY");
def rs = (close / close[20]) / (spyClose / spyClose[20]);

plot scan = isJuly and above50MA and above200MA
    and risingMomentum and rs > 1.0;

Use this alongside the full thinkorswim indicators suite to rank candidates by squeeze momentum, relative volume, and proximity to support. Prioritize Technology and Consumer Discretionary names based on the sector rotation data.

Tools for July Seasonal Trading

Frequently Asked Questions

What is the historical win rate for the S&P 500 in July?

The S&P 500 has posted positive returns in July approximately 58.3% of the time since 1950. In the modern era (1990-2024), the win rate increases to 62.9%. The month ranks among the top five by average return at +1.2%. When June closes positive, July's win rate climbs to 68.7%.

How does earnings season affect July trading?

July earnings create a two-phase volatility pattern. The first two weeks are calm with the VIX declining near Independence Day. Mid-month, implied volatility builds as bank earnings begin. The final week brings heavy mega-cap tech reporting, producing large index moves. Traders should plan position sizing around this calendar using volatility box expected move levels.

Which sectors perform best during July?

Technology (XLK) and Consumer Discretionary (XLY) historically lead with average returns of +2.1% and +1.8% respectively. Financials benefit from mid-month bank earnings. Defensive sectors like Utilities underperform as the market favors growth-oriented positioning.

How can I use ThinkOrSwim to trade July seasonal patterns?

Deploy the seasonal overlay ThinkScript to visualize bullish windows on your chart. Use the TTM Squeeze ThinkOrSwim scanner to identify compression setups in early July. Filter with thinkorswim scanners for stocks showing relative strength above 1.0 and rising moving average crossovers. Combine technical signals with Volatility Box levels for entry and exit planning.

Does the July 4th holiday affect stock market returns?

Yes. The two trading days before and after July 4th have historically produced returns exceeding the average four-day window. This pre-holiday drift is attributed to short covering, reduced institutional selling pressure, and general holiday optimism. Position for this by entering long on the last trading day before the break.

What are the biggest risks of trading July seasonal patterns?

Primary risks include earnings gap risk in the second half, FOMC decisions overriding seasonal tendencies, and the false assumption that patterns repeat every year. July has a roughly 42% failure rate, with worst performances during bear markets. Risk no more than 1% to 2% of account equity per seasonal trade and use thinkorswim scripts for day trading to manage intraday exposure.