Combining TTM SQUEEZE Signals with SEASONAL ANALYSIS for a Bullish Setup

TTM Squeeze is one of the most widely used thinkorswim indicators for identifying volatility compression and the directional moves that follow. But raw squeeze signals alone leave money on the table. Seasonal analysis offers a statistical overlay that filters out low-probability setups and amplifies the ones worth taking. This research breaks down how seasonal market patterns interact with TTM Squeeze compression and expansion phases, complete with backtesting data and ready-to-use ThinkScript code for your thinkorswim scripts for day trading.

Why Seasonal Patterns Matter for TTM Squeeze Traders

Markets do not behave uniformly across the calendar year. Decades of data confirm recurring tendencies tied to specific months, holiday periods, earnings seasons, and quarterly cycles. These patterns directly affect volatility, the core input driving every TTM Squeeze thinkorswim signal.

Volatility compression tends to cluster during certain calendar windows. Expansion phases also show measurable seasonal bias. Traders who ignore this context treat January squeezes the same as October squeezes despite fundamentally different conditions.

Understanding Seasonal Volatility Cycles

The table below summarizes average monthly VIX readings and squeeze signal frequency on SPY across 20+ years of data.

October and September produce the most frequent squeeze signals with the shortest compression periods. April, November, and December show the highest directional accuracy. July and August produce fewer squeezes with lower accuracy.

The Monthly Squeeze Bias Framework

Months are categorized into three tiers based on historical squeeze performance:

Tier 1 (High Confidence): April, November, December. Accuracy above 70% with clean squeeze-to-expansion transitions. Full position sizing and extended targets.

Tier 2 (Standard Confidence): January, March, June, October. Accuracy between 62% and 69%. Standard position sizing.

Tier 3 (Reduced Confidence): February, May, July, August, September. Accuracy below 62%. Reduce position sizes by 25% to 50%.

Holiday Effects on Squeeze Compression

Pre-holiday squeezes produce false breakouts because volume is thin and institutional traders are absent. Backtesting shows squeeze signals within three trading days of major holidays have only 47.3% directional accuracy.

Post-holiday squeezes are different. The return of full participation after extended breaks creates genuine compression-to-expansion transitions. Squeezes firing in the first three trading days after New Year, Labor Day, and Thanksgiving show 74.8% directional accuracy.

Earnings Season and TTM Squeeze Interactions

During the four annual earnings windows (mid-January, mid-April, mid-July, mid-October), implied volatility expands ahead of announcements and collapses afterward, creating a predictable squeeze cycle.

The post-earnings squeeze is where the real opportunity lies. After the earnings reaction, stocks enter a 3 to 5 day compression phase. The TTM Squeeze signal that fires after this compression shows 76.1% directional accuracy historically. Traders using the volatility box alongside TTM Squeeze thinkorswim during earnings season can identify high-probability compression zones with greater precision.

Backtesting Results: Seasonal Squeeze Filters

We backtested across SPY, QQQ, IWM, and DIA from 2004 through 2024, comparing raw TTM Squeeze, monthly tier filters, and full seasonal filters.

The full seasonal filter reduces total signals by 42.6%. Win rate jumps from 56.3% to 73.2%. Maximum drawdown is cut by more than half. Seasonal filters eliminate losing trades rather than finding more winners.

ThinkScript: Monthly Seasonal Squeeze Scanner

This thinkorswim scanner identifies TTM Squeeze signals aligning with favorable seasonal windows.

# Monthly Seasonal Squeeze Scanner
# Filters TTM Squeeze signals by seasonal tier

def squeeze = TTM_Squeeze().SqueezeAlert;
def momentum = TTM_Squeeze().Histogram;
def momUp = momentum > momentum[1];
def momDown = momentum < momentum[1];
def currentMonth = GetMonth();

# Tier 1: April, November, December
def tier1 = currentMonth == 4 or currentMonth == 11 or currentMonth == 12;
# Tier 2: January, March, June, October
def tier2 = currentMonth == 1 or currentMonth == 3 or currentMonth == 6 or currentMonth == 10;

def seasonalPass = tier1 or tier2;
def squeezeOn = squeeze != 0;

def bullSignal = squeezeOn and seasonalPass and momUp and momentum > 0;
def bearSignal = squeezeOn and seasonalPass and momDown and momentum < 0;

plot scan = bullSignal or bearSignal;

ThinkScript: Seasonal Context Overlay Study

This lower study adds seasonal context to your TTM Squeeze indicator with tier color-coding and holiday warnings.

# Seasonal Squeeze Context Overlay
declare lower;

def currentMonth = GetMonth();
def currentDay = GetDayOfMonth();

def tier1 = currentMonth == 4 or currentMonth == 11 or currentMonth == 12;
def tier2 = currentMonth == 1 or currentMonth == 3 or currentMonth == 6 or currentMonth == 10;
def tier3 = currentMonth == 2 or currentMonth == 5 or currentMonth == 7
            or currentMonth == 8 or currentMonth == 9;

def thanksgivingZone = currentMonth == 11 and currentDay >= 22 and currentDay <= 28;
def christmasZone = currentMonth == 12 and currentDay >= 22;
def july4Zone = currentMonth == 7 and currentDay >= 1 and currentDay <= 7;
def laborDayZone = currentMonth == 9 and currentDay >= 1 and currentDay <= 7;
def holidayWarning = thanksgivingZone or christmasZone or july4Zone or laborDayZone;

plot SeasonalTier = if tier1 then 3 else if tier2 then 2 else 1;
SeasonalTier.SetPaintingStrategy(PaintingStrategy.HISTOGRAM);
SeasonalTier.AssignValueColor(
    if holidayWarning then Color.YELLOW
    else if tier1 then Color.GREEN
    else if tier2 then Color.CYAN
    else Color.DARK_RED
);

AddLabel(holidayWarning, "HOLIDAY ZONE - AVOID ENTRIES", Color.YELLOW);
AddLabel(tier1, "TIER 1 SEASONAL WINDOW", Color.GREEN);
AddLabel(tier2 and !holidayWarning, "TIER 2 SEASONAL WINDOW", Color.CYAN);
AddLabel(tier3 and !holidayWarning, "TIER 3 - REDUCE SIZE", Color.DARK_RED);

ThinkScript: Post-Earnings Squeeze Filter

This script targets stocks entering compression 5 to 10 days after an earnings reaction.

# Post-Earnings Squeeze Filter

def squeeze = TTM_Squeeze().SqueezeAlert;
def momentum = TTM_Squeeze().Histogram;

def avgRange = Average(AbsValue(close - open), 20);
def earningsBar = AbsValue(close - open) > avgRange * 2.5
                  or AbsValue(open - close[1]) > avgRange * 2;

def recentEarnings = Highest(earningsBar, 10) == 1
                     and Highest(earningsBar, 4) == 0;

def postEarningsSqueeze = squeeze != 0 and recentEarnings;
def bullBias = momentum > 0 and momentum > momentum[1];
def bearBias = momentum < 0 and momentum < momentum[1];

plot bullPostEarnings = postEarningsSqueeze and bullBias;
plot bearPostEarnings = postEarningsSqueeze and bearBias;

bullPostEarnings.SetPaintingStrategy(PaintingStrategy.BOOLEAN_ARROW_UP);
bullPostEarnings.SetDefaultColor(Color.GREEN);
bearPostEarnings.SetPaintingStrategy(PaintingStrategy.BOOLEAN_ARROW_DOWN);
bearPostEarnings.SetDefaultColor(Color.RED);

Seasonal Squeeze Scoring System

This scoring system assigns points based on multiple seasonal factors. Monthly Tier (1 to 3 points) + Holiday Proximity (-2 to +1) + Earnings Cycle (-1 to +2) + OPEX Timing (-1 to +2). Scores of 5+ get full position sizing. Scores below 1 mean no trade.

# Seasonal Squeeze Scoring System
declare lower;

def squeeze = TTM_Squeeze().SqueezeAlert;
def squeezeOn = squeeze != 0;
def currentMonth = GetMonth();
def currentDay = GetDayOfMonth();

def monthScore = if currentMonth == 4 or currentMonth == 11
                    or currentMonth == 12 then 3
                 else if currentMonth == 1 or currentMonth == 3
                    or currentMonth == 6 or currentMonth == 10 then 2
                 else 1;

def nearHoliday =
    (currentMonth == 11 and currentDay >= 22 and currentDay <= 28) or
    (currentMonth == 12 and currentDay >= 22) or
    (currentMonth == 7 and currentDay >= 1 and currentDay <= 6) or
    (currentMonth == 9 and currentDay >= 1 and currentDay <= 5);

def postHoliday =
    (currentMonth == 1 and currentDay >= 2 and currentDay <= 6) or
    (currentMonth == 9 and currentDay >= 6 and currentDay <= 10);

def holidayScore = if nearHoliday then -2
                   else if postHoliday then 1 else 0;

def opexWeek = (currentMonth == 3 or currentMonth == 6
                or currentMonth == 9 or currentMonth == 12)
               and currentDay >= 15 and currentDay <= 21;
def postOpex = (currentMonth == 3 or currentMonth == 6
                or currentMonth == 9 or currentMonth == 12)
               and currentDay >= 22 and currentDay <= 25;
def opexScore = if postOpex then 2
                else if opexWeek then -1 else 0;

def totalScore = monthScore + holidayScore + opexScore;

plot ScorePlot = if squeezeOn then totalScore else Double.NaN;
ScorePlot.SetPaintingStrategy(PaintingStrategy.HISTOGRAM);
ScorePlot.AssignValueColor(
    if totalScore >= 5 then Color.GREEN
    else if totalScore >= 3 then Color.CYAN
    else if totalScore >= 1 then Color.YELLOW
    else Color.RED
);

AddLabel(squeezeOn, "SEASONAL SCORE: " + totalScore,
    if totalScore >= 5 then Color.GREEN
    else if totalScore >= 3 then Color.CYAN
    else if totalScore >= 1 then Color.YELLOW
    else Color.RED);

Implementing on Futures with the Volatility Box

Futures traders using /ES, /NQ, /RTY, and /CL can apply seasonal squeeze analysis with modifications. Quarterly OPEX creates a reliable volatility cycle: the week before the third Friday of March, June, September, and December produces squeeze setups as gamma pins prices. The post-OPEX squeeze on /ES shows 77.4% directional accuracy over the past decade.

The volatility box for futures provides real-time volatility levels that complement seasonal squeeze analysis. Crude oil (/CL) has its own seasonal profile: TTM Squeeze signals during September through November show 71.3% accuracy versus 54.8% during April through June.

Common Mistakes to Avoid

Over-fitting to calendar dates: Seasonal patterns are tendencies, not guarantees. Every month has losing squeeze trades regardless of tier.

Ignoring regime changes: A financial crisis or rate shock overrides all seasonal patterns. When VIX is above 35, seasonal analysis becomes secondary.

Applying equity seasonality to all products: Crude oil, gold, and natural gas each have product-specific patterns. Using SPY data to trade /CL squeezes is a category error.

Skipping confirmation timeframes: A daily squeeze during a Tier 1 month needs weekly chart confirmation. Always verify alignment across timeframes.

Daily Workflow: Seasonal Squeeze Routine

Pre-market (15 min): Check the seasonal score. Note tier, holiday proximity, and OPEX status.

Scan phase (10 min): Run the monthly seasonal squeeze scanner. Sort by volume. Combined with other thinkorswim scripts for day trading, this is one of the most practical thinkorswim scanners for filtering seasonal setups.

Analysis (20 min): Check weekly charts for higher-timeframe confirmation. Verify volatility box levels provide good target-to-stop ratios. Filter out setups scoring below 3.

Execution: Size positions by seasonal tier. Use volatility box levels for targets. The squeeze course covers additional integration techniques. These thinkorswim scripts for day trading give you a repeatable seasonal edge.