(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":["/account/","/login/","/thank-you/","/wp-json/openid-connect/userinfo","wp-admin","wp-login.php"]};
//# sourceURL=breeze-prefetch-js-extra
In this guide we will go over a step by step process on how to use the new MenthorQ VRP Models.
Step 1: Use VRP to Screen Premium Bias
The Volatility Risk Premium (VRP) measures the spread between Implied Volatility (IV) and Historical Volatility (HV), then ranks that spread against the past year’s data. It helps identify whether options are generally expensive or cheap.
High VRP (Rank > 50%): IV is high relative to HV
→ Sell premium bias
Low VRP (Rank ≤ 50%): HV is high relative to IV
→ Buy premium bias
Current VRP Observations
From the latest VRP Cross Asset Monitor, the following assets have elevated VRP (options potentially overpriced):
SPX
QQQ
XLF
XLI
XLK
On the other hand, these assets show suppressed VRP, implying cheap premium:
TLT
XHB
XLU
SLV
IWM
This is your first screen. The next step is validation, to see if IV and HV percentile rankings agree.
Volatility Playbook: VRP Models 8
Step 2: Validate With HV vs IV Percentile Plot
The HV vs IV scatter plot maps each asset by its percentile rank of realized (HV) and implied (IV) volatility.
Interpretation Rules:
Above the diagonal line → IV > HV → Options are overpriced → Sell premium
Below the diagonal line
→ HV > IV → Options are underpriced → Buy premium
Confirmed Sell Setups
These assets sit well above the diagonal:
XLF: IV at 95th percentile, HV at 65th
XLI: IV in 90s, HV closer to 40th
These confirm the VRP signal: not only is IV high relative to HV, but also to its own historical levels. These are textbook premium selling candidates.
Confirmed Buy Setups
These assets fall well below the diagonal:
TLT: HV in the 80s, IV in the 40s
XHB: HV in the 80s, IV in the 20s
IWM: HV in 60s, IV in the 10s
In all cases, realized volatility is high, but the market is discounting future volatility, underpricing optionality. These are strong premium buying setups.
Volatility Playbook: VRP Models 9
Trade Structure Ideas (Educational Only)
Once VRP and HV-IV percentile agree, apply the appropriate structure:
Selling Premium
1. SPX / QQQ
Structure: Iron Condors, Call or Put Credit Spreads
Rationale: Options are rich, and price action is constrained, optimal for income strategies.
2. XLF / XLI
Structure: Short vertical spreads
Rationale: Both VRP and IV percentiles confirm overpricing. Controlled risk with high expectancy.
Buying Premium
1. TLT / XHB
Structure: Long straddles, debit spreads
Rationale: Cheap IV with high realized movement, directional or non-directional plays work well.
2. SLV / XLU
Structure: Diagonal spreads, long calls or puts
Rationale: Asymmetric reward for little upfront cost if volatility reverts higher.
How To Build This Into Your Workflow
Here’s a simple daily process using these two models:
1. Start With VRP Cross Asset Monitor
Pull the latest VRP ranks in the VRP Cross Asset Monitor. Mark all names with VRP > 50% as potential premium sells, and VRP ≤ 50% as premium buys.
2. Confirm With Cross Asset Volatility Tracker
Validate that IV is genuinely rich or cheap vs HV using the Cross Asset Volatility Tracker. Avoid trades where IV and HV percentiles are tightly aligned (e.g., both near 50%).
3. Apply Structure Based on Volatility Environment
High IV + High VRP: Credit spreads or condors
Low IV + Low VRP: Debit spreads, straddles, or diagonals
4. Select Strikes Using Additional Models
Use Expected Move bands, Q-Levels, or technical inflections to refine strike selection.
Only size up when both VRP and HV/IV models align with supporting directional scores like Momentum or Options Activity.
Why This Combo Works
Individually, each model tells you part of the story:
VRP shows if options are rich or cheap on a statistical basis.
HV vs IV adds nuance is implied vol truly out of line with realized behavior?
Together, they act as a confirmation engine:
Avoid false positives: Don’t sell premium just because IV is high, HV might be climbing too.
Avoid overpaying: Don’t buy premium if both IV and HV are low, movement may stay muted.
This combo keeps you one step ahead of traders using only one lens.
Conclusion
If you’re serious about options trading, you need to know when to buy or sell premium — not just directionally, but also structurally. The VRP and HV vs IV percentile models give you that edge.
By using both together:
You spot when the market is overpaying for protection (sell opportunity)
You detect when the market is ignoring realized risk (buy opportunity)
This dual-model framework keeps your trading focused, your structures aligned, and your capital positioned in front of asymmetric payoffs.
Join us today
Access daily Market Research and our interactive Dashboard. Make better trading decisions.