(function(){
var COOKIE_NAME = 'menthorq_utm_params';
var LS_KEY = 'menthorq_utm_params';
var UTM_KEYS = ['utm_source','utm_medium','utm_campaign','utm_term','utm_content','utm_id'];
var CLICK_ID_KEYS = ['gclid','fbclid','msclkid','ttclid'];
var COOKIE_DAYS = 30;// Read UTM parameters and click IDs from current URL
var params = new URLSearchParams(window.location.search);
var trackingData = {};
var hasData = false;
var allKeys = UTM_KEYS.concat(CLICK_ID_KEYS);
for (var i = 0; i < allKeys.length; i++) {
var val = params.get(allKeys[i]);
if (val) {
trackingData[allKeys[i]] = val;
hasData = true;
}
}if (hasData) {
// Fresh tracking data found in URL — store it (overwrites previous attribution)
trackingData.captured_at = new Date().toISOString();
setCookie(COOKIE_NAME, JSON.stringify(trackingData), COOKIE_DAYS);
try { localStorage.setItem(LS_KEY, JSON.stringify(trackingData)); } catch(e) {}
return;
}// No tracking params in URL — check if cookie exists
if (getCookie(COOKIE_NAME)) return;// Cookie is missing (expired or first visit) — try to restore from localStorage
try {
var stored = localStorage.getItem(LS_KEY);
if (stored) {
var parsed = JSON.parse(stored);
if (parsed && (parsed.utm_source || parsed.gclid || parsed.fbclid || parsed.msclkid || parsed.ttclid)) {
setCookie(COOKIE_NAME, stored, COOKIE_DAYS);
}
}
} catch(e) {}// Helper: set cookie
function setCookie(name, value, days) {
var expires = new Date(Date.now() + days * 864e5).toUTCString();
var cookie = name + '=' + encodeURIComponent(value) + ';expires=' + expires + ';path=/;SameSite=Lax';
if (location.protocol === 'https:') cookie += ';Secure';
document.cookie = cookie;
}// Helper: get cookie value (returns empty string if not found)
function getCookie(name) {
var match = document.cookie.match(new RegExp('(?:^|; )' + name + '=([^;]*)'));
return match ? decodeURIComponent(match[1]) : '';
}
})();
var breeze_prefetch = {"local_url":"https://menthorq.com","ignore_remote_prefetch":"1","ignore_list":["/wp-json/openid-connect/userinfo","wp-admin","wp-login.php"]};
//# sourceURL=breeze-prefetch-js-extra
Calculating Historical Volatility with Log Returns
In this article we will go from Straddle Price to Expected Move. This is a foundational metric for quantitative teams at firms like Citadel and is essential for anyone trading options at a professional level. Begin with daily closes, convert them into log returns, subtract the mean, square, average, and square-root. Multiply the resulting daily sigma by √252 to annualize. MenthorQ offers several estimators. When you see that SPX’s one-month historical has drifted from eight per cent to twelve per cent over two weeks, you have an empirical anchor for judging option prices.
Extracting Implied Volatility from a Straddle
Option markets quote uncertainty via premiums. A rule of thumb is that the next-Friday at-the-money straddle equals roughly 0.8 σ √T S, where σ is annualised implied vol and T is time in years. Rearranged, annualized implied volatility is
σ ≈ (Straddle Price ÷ 1.25 ÷ Spot) × √252.
The 1.25 factor converts premium into an expected one-sigma move; the division by spot expresses that move as a percentage; √252 rescales from weekly to annual. Suppose SPX trades at 5750 and the one-week ATM straddle costs $24. Plugging in yields about eight per cent implied vol—far beneath the long-term mean, could be a red flag.
From Percentage to Dollar Expected Move
Traders care about dollars. Multiply the weekly implied sigma by spot and divide by √52 to convert to a weekly band. A quicker shortcut on MenthorQ’s charts multiplies the straddle by 1.25, printing an expected move of roughly ±$30 around 5750 for the coming week. These bands overlay the price chart so users can gauge whether a given day’s move is extraordinary or merely noise inside the option market’s forecast.
Volatility Risk Premium
If implied volatility exceeds realized volatility by, say, four points, sellers of premium are paid, on average, for taking risk. When the gap is negative, buyers of options enjoy cheap convexity. MenthorQ’s Main chart can help you track that. Seeing SPX with a +4% VRP while NDX sits at –1% would suggest short-gamma structures on the former and potential long-gamma grabs on the latter.
From Straddle Price to Expected Move 5
Actionable Uses
Short-Straddle Fade: If implied volatility is historically high relative to realized and no major catalyst looms, selling the front-week straddle can be attractive. MenthorQ’s GEX overlay shows whether gamma positioning might pin price inside the straddle’s break-even levels, adding confidence.
Directional Call Spread: If the implied move band lies directly below a positive-gamma support zone on MenthorQ’s Tradingview levels, a modest debit call spread may capture upside with limited theta risk.
Calendar into Event: When realized volatility is low but a known catalyst approaches, buying a longer-dated straddle while shorting the event week captures the likely IV pop. MenthorQ’s Term-Structure plot highlights which tenor is mispriced.
Reading the Crush
After earnings or a macro release implied volatility collapses toward realized. MenthorQ tracks pre- and post-event IV so traders can time exits ahead of the crush. If the data show that a stock’s earnings straddle consistently over-prices the move by two points of vol, selling that straddle one day before earnings becomes a rinse-and-repeat tactic.
Practical Desk Workflow
Start every morning by noting where the spot price sits relative to the MenthorQ expected-move bands. Scan the VRP table for large positive or negative gaps. Check whether GEX clusters align with those bands to spot likely pins or breakouts. Then pick structures—straddles, flies, calendars—that best exploit the relationship between implied and realized.
Conclusion
Historical volatility is the footprint of past uncertainty; implied volatility is the crowd’s bet on the future. Converting an at-the-money straddle into sigma and dollars lets you compare the two, size trades, and monitor risk. MenthorQ automates the math, it also has a 1Day extected move calculated using implied volatility. But the edge comes from understanding what the numbers imply about probable price paths and positioning accordingly. By translating premiums into expected moves and pitting them against realized behaviour, traders gain a disciplined template for exploiting the volatility risk premium day after day.
To dig deeper into expected moves, volatility risk premium, and how to apply them in practice, chat with QUIN for guidance.
Join us today
Access daily Market Research and our interactive Dashboard. Make better trading decisions.