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var CN = 'menthorq_utm_params';
var LK = 'menthorq_utm_params';
var UK = ['utm_source','utm_medium','utm_campaign','utm_term','utm_content','utm_id'];
var CK = ['gclid','fbclid','msclkid','ttclid','twclid'];
var CD = 30;
var AK = UK.concat(CK);function sC(n,v,d){var e=new Date(Date.now()+d*864e5).toUTCString();var c=n+'='+encodeURIComponent(v)+';expires='+e+';path=/;SameSite=Lax';if(location.protocol==='https:')c+=';Secure';document.cookie=c;}
function gC(n){var m=document.cookie.match(new RegExp('(?:^|; )'+n+'=([^;]*)'));return m?decodeURIComponent(m[1]):'';}
function sv(d){var j=JSON.stringify(d);sC(CN,j,CD);try{localStorage.setItem(LK,j);}catch(e){}}
function hk(o){if(!o)return false;for(var i=0;i<AK.length;i++)if(o[AK[i]])return true;return false;}
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function ld(){var r=gC(CN);if(r){try{var n=nm(JSON.parse(r));if(n)return n;}catch(e){}}try{var s=localStorage.getItem(LK);if(s){var n=nm(JSON.parse(s));if(n)return n;}}catch(e){}return null;}
function mg(p,n){var o={};if(p)for(var k in p)o[k]=p[k];for(var k in n)o[k]=n[k];return o;}var ps = new URLSearchParams(window.location.search);
var fd = {}, has = false;
for (var i = 0; i < AK.length; i++) {
var v = ps.get(AK[i]);
if (v) { fd[AK[i]] = v; has = true; }
}// Click-ID synthesis: when only a click-id is present (no utm_source), derive
// utm_source/utm_medium so downstream analytics groups under the right channel.
var SY = {
gclid: ['google', 'cpc'],
fbclid: ['facebook', 'cpc'],
msclkid: ['bing', 'cpc'],
ttclid: ['tiktok', 'cpc'],
twclid: ['twitter', 'cpc']
};
if (has && !fd.utm_source) {
for (var sk in SY) {
if (fd[sk]) { fd.utm_source = SY[sk][0]; fd.utm_medium = SY[sk][1]; break; }
}
}if (has) {
fd.captured_at = new Date().toISOString();
var ex = ld();
// Last-touch: merge new fields ON TOP of previous last (preserva campi pregressi)
var newLast = ex && ex.last ? mg(ex.last, fd) : fd;
// First-touch: se ex.first ha almeno un UTM, e' completo e sticky.
// Se ex.first esiste ma e' click-id-only (orphan), completa con i campi nuovi.
// Se ex.first non esiste, usa fd come first.
var newFirst;
if (ex && ex.first) {
var firstHasUtm = false;
for (var i = 0; i < UK.length; i++) if (ex.first[UK[i]]) { firstHasUtm = true; break; }
newFirst = firstHasUtm ? ex.first : mg(ex.first, fd);
} else {
newFirst = fd;
}
sv({first: newFirst, last: newLast});
return;
}var raw = gC(CN);
if (raw) {
try {
var p = JSON.parse(raw);
if (!p.first && hk(p)) sv({first: p, last: p});
} catch(e) {}
return;
}try {
var s = localStorage.getItem(LK);
if (s) { var n = nm(JSON.parse(s)); if (n) sv(n); }
} catch(e) {}
})();
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//# sourceURL=breeze-prefetch-js-extra
The Option Q-Score is part of the broader MenthorQ Q-Score framework, which also includes scores for Momentum, Seasonality, and Volatility. Together, they help traders understand market regimes through four distinct lenses. The Option Q-Score specifically focuses on how options traders are positioned and where they expect the asset to go next.
The score ranges from 0 to 5, where:
0 means strong bearish sentiment from the options market.
3 reflects neutral or mixed sentiment.
5 suggests strong bullish sentiment from the options market.
It’s a forward-looking signal based on real-time options data, not past price movement. And unlike pure volatility metrics, this score is designed to detect directional conviction—when traders are leaning aggressively long or short.
What Is the Option Q-Score? 5
What the Score Measures
At its core, the Option Q-Score analyzes trader positioning and sentiment within the options chain. The model looks at several dimensions of the options market, including:
Call vs. put volume
Changes in open interest at key strikes
Skew and slope of implied volatility
Relative strength of short-dated vs long-dated activity
Dealer gamma and delta positioning (where applicable)
The goal is not to predict volatility or time expiry behavior, but to understand what the aggregate of all option flow is implying about the next directional move in the underlying asset.
When the score is high, options market participants are expressing bullish conviction, often via concentrated call buying, bullish risk reversals, or notable open interest build-ups in out-of-the-money calls. When the score is low, traders are either aggressively hedging downside or speculating on a price drop, reflected in put demand, skew steepening, or concentrated flow around lower strikes.
The Option Q-Score helps traders bridge the gap between raw data and actionable insight. Here’s how it can improve your trading process:
Identifying sentiment shifts before they show up in price
Because options markets are often forward-looking, sentiment can shift in the options chain before it’s visible in the underlying asset. A rising Option Q-Score may hint at a breakout or reversal, even while price is still consolidating.
This kind of signal pairing is especially helpful in swing trading or breakout setups.
Scanning for unusual options activity
Instead of watching dozens of tickers and option chains manually, traders can filter assets using the Option Q-Score to surface names with unusual or extreme sentiment. Whether you’re hunting for longs with high conviction or shorts with heavy downside hedging, the score acts as a scanner shortcut.
Timing entries around options flow dynamics
Large shifts in the Option Q-Score can often precede pinning behavior, short gamma dynamics, or volatility expansion, especially into expiry windows. By monitoring the score, traders can prepare for the type of market structure they might face.
Let’s say you’re trading Brent crude, and you notice that the Option Q-Score has spiked from 2 to 4 over the past two days. That jump tells you something important:
Options traders have become more bullish, possibly in response to a shift in geopolitical risk or a structural supply narrative.
There could be concentrated call buying above current price, pushing dealers into short gamma territory.
The market may become more directional, as dealers hedge by buying futures into rising price.
This information helps you:
Align long trades with positive sentiment
Avoid fading price strength prematurely
Adjust size or entry timing if you expect volatility ahead
Even if you don’t trade options directly, the Option Q-Score gives you a lens into a large and influential segment of the market.
What the Option Q-Score Is Not
It’s important to clarify what this score does not do:
It’s not a volatility score, that’s what the Volatility Q-Score is for.
It’s not dealer flow prediction, although dealer positioning may contribute to the reading.
It’s not a guarantee of price movement, but a real-time readout of trader sentiment based on options activity.
Think of it as a temperature gauge for how the options market feels about the asset’s direction.
Integrating the Option Q-Score into Your Routine
The best use of the Option Q-Score comes from contextual layering. Here’s how it fits into a professional trader’s workflow:
Check momentum and trend: Is the underlying asset in a trend or range? How is the Momentum Q-Score behaving?
Scan the Option Q-Score: Has sentiment shifted recently? Is there a new build in call or put interest?
Evaluate seasonality and volatility: Are there known catalysts ahead? What’s the realized vs implied vol environment?
Use for confirmation or contrarian setups: If all factors align (strong momentum, bullish sentiment), the score confirms conviction. If the score is high but momentum is weak, it may be an early signal or a contrarian fade opportunity.
Final Thoughts: Sentiment as an Edge
In the age of algorithms, much of trading has become a game of speed and structure. But sentiment, the collective expectation of traders, remains a powerful edge. The Option Q-Score allows you to measure that sentiment in real time, using actual money flows in the options market.
Whether you’re managing a directional position, planning a volatility play, or just trying to understand how other traders are leaning, the Option Q-Score turns noise into structure. It’s one of the clearest ways to translate options activity into market conviction, without needing to analyze every options chain manually.
And when paired with the full MenthorQ suite of signals, it becomes part of a system that makes institutional-level analysis accessible to every trader.
If you want to learn more about Q-Scores chat with our AI Trading Assistant QUIN.
Join us today
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