{"id":234681,"date":"2025-12-01T11:20:49","date_gmt":"2025-12-01T16:20:49","guid":{"rendered":"https:\/\/ibkrcampus.com\/campus\/?p=234681"},"modified":"2025-12-02T11:50:15","modified_gmt":"2025-12-02T16:50:15","slug":"rhino-strategy-family-from-broken-wing-butterfly-to-genetic-optimization","status":"publish","type":"post","link":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/rhino-strategy-family-from-broken-wing-butterfly-to-genetic-optimization\/","title":{"rendered":"Rhino Strategy Family: From Broken-Wing Butterfly to Genetic Optimization"},"content":{"rendered":"\n<p><em>The article &#8220;Rhino Strategy Family: From Broken-Wing Butterfly to Genetic Optimization&#8221; was originally posted on <a href=\"https:\/\/blog.deltaray.io\/rhino-options-strategy\/\">Deltaray<\/a> blog<\/em><\/p>\n\n\n\n<p>The&nbsp;<strong>Rhino Options Strategy<\/strong>&nbsp;is a conservative, broken\u2011wing butterfly income trade with an upside hedge. Rhino is not just a simple trade; it\u2019s a whole family of related strategies that have evolved over nearly a decade in response to changing market conditions.<\/p>\n\n\n\n<p><em>Monthly<\/em>,&nbsp;<em>Giant<\/em>, and&nbsp;<em>Baby Rhino<\/em>&nbsp;variants coexist alongside variants from other developers like the&nbsp;<em>White Rhino<\/em>&nbsp;by Randy Schwartzenburg. Several modern income trades share similar DNA: Amy Meissner\u2019s&nbsp;<em>A14<\/em>, the&nbsp;<em>BWB\u2011Cal<\/em>&nbsp;trades from Ron Bertino, and more recent public trades such as&nbsp;<em><a href=\"https:\/\/www.youtube.com\/watch?v=nzx4yWbzs-I\" target=\"_blank\" rel=\"noreferrer noopener\">Time Flies Spread<\/a><\/em>&nbsp;and&nbsp;<em><a href=\"https:\/\/www.youtube.com\/watch?v=y_7vCLAcc9c\" target=\"_blank\" rel=\"noreferrer noopener\">Flyagonal<\/a><\/em>.<\/p>\n\n\n\n<p>They all blend a put\u2011side income structure with a calendar or diagonal hedge. Whether they were directly inspired by the Rhino or evolved in parallel, they live in the same design space.<\/p>\n\n\n\n<p>In this article we will show how Rhino has evolved, share our personal experience with related strategies, and we use a Genetic Algorithm to provide a variant that works well in recent market conditions.<\/p>\n\n\n\n<p>This will be a long one, settle in like you accidentally picked the director\u2019s cut.<\/p>\n\n\n\n<p><strong>TL;DR: Performance at a glance<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/blog.deltaray.io\/rhino-options-strategy\/#backtest-summary\"><strong>Original conservative SPX Rhino<\/strong><\/a>&nbsp;(2018\u20132025): Sharpe 1.12, CAGR 3.15%, MaxDD \u22122.81%<\/li>\n\n\n\n<li><a href=\"https:\/\/blog.deltaray.io\/rhino-options-strategy\/#optimization-results\"><strong>GeneticRhino-25Q4 (IS 2022\u20132025 \/ OOS 2018\u20132022)<\/strong><\/a>:\n<ul class=\"wp-block-list\">\n<li>IS Sharpe 2.31, CAGR 13.1%, MaxDD \u22124.2%, Deflated Sharpe: 1.15<\/li>\n\n\n\n<li>OOS Sharpe 2.2, CAGR 9.21%, MaxDD \u22126.74%<\/li>\n\n\n\n<li>Same design space (BWB + call hedge), simplified rules, GA + DSR to control overfitting.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"overview\">Overview<\/h2>\n\n\n\n<p>The&nbsp;<strong>Rhino Options Strategy<\/strong>&nbsp;was developed by Brian Larson and&nbsp;<a href=\"https:\/\/www.youtube.com\/watch?v=NBp8zzdrnXo\" target=\"_blank\" rel=\"noreferrer noopener\">published at Capital Discussions<\/a>&nbsp;(now Aeromir) in 2015. After the initial publication,&nbsp;<a href=\"https:\/\/www.youtube.com\/@brunovoisin\" target=\"_blank\" rel=\"noreferrer noopener\">Bruno Voisin<\/a>&nbsp;played a major role in the strategy development and has been steadily refining the trade ever since.<\/p>\n\n\n\n<p>At its core, the trade combines:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>An out\u2011of\u2011the\u2011money&nbsp;<strong>put broken\u2011wing butterfly<\/strong>&nbsp;(BWB)<\/li>\n\n\n\n<li>An&nbsp;<strong>upside hedge<\/strong>&nbsp;\u2014 typically call calendars<\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1100\" height=\"609\" data-src=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/risk-graph-deltaray-1100x609.png\" alt=\"Rhino Strategy Family\" class=\"wp-image-234682 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/risk-graph-deltaray-1100x609.png 1100w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/risk-graph-deltaray-700x387.png 700w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/risk-graph-deltaray-300x166.png 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/risk-graph-deltaray-768x425.png 768w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/risk-graph-deltaray-1536x850.png 1536w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/risk-graph-deltaray.png 1614w\" data-sizes=\"(max-width: 1100px) 100vw, 1100px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1100px; aspect-ratio: 1100\/609;\" \/><\/figure>\n\n\n\n<p class=\"has-vivid-green-cyan-color has-text-color has-link-color wp-elements-e2bd69b00a38bc62b4a52be8db583b70\"><strong>Rhino Shape<\/strong><\/p>\n\n\n\n<p class=\"has-vivid-green-cyan-color has-text-color has-link-color wp-elements-c543be5b7e88400bfea2a77b0da93ed3\">The risk graph resembles a Rhino\u2019s head: the BWB and the upside hedge form two horns, with a broad, relatively flat T+0 between them.<\/p>\n\n\n\n<p><strong>Trade characteristics:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Flat or slightly negative delta over a wide range<\/li>\n\n\n\n<li>Low gamma<\/li>\n\n\n\n<li>Positive theta that doesn\u2019t require hyper\u2011active management<\/li>\n<\/ul>\n\n\n\n<p>The Rhino family directly shaped MesoSim&#8217;s approach to leg selection and adjustments, therefore it is it is&nbsp;<strong>well-suited<\/strong> to showcase MesoSim&#8217;s capabilities.<\/p>\n\n\n<div class=\"accordion accordion-large\"> \n\t<div class=\"accordion-item\">\n\t\t<button id=\"accordionCampus-69d238d46b4a4\" class=\" collapsed w-100\" type=\"button\" data-bs-toggle=\"collapse\" data-bs-target=\"#collapseAccordion-69d238d46b4a4\" aria-expanded=\"false\" aria-controls=\"collapseAccordion-69d238d46b4a4\">\n\t\t\t<h3>Foreword<\/h3>\n\t\t\t\t\t<\/button>\n\t\t<div class=\"accordion-collapse collapse\" id=\"collapseAccordion-69d238d46b4a4\" aria-labelledby=\"accordionCampus-69d238d46b4a4\" data-bs-parent=\"\">\n\t\t\t<div class=\"accordion-body\">\n\t\t\t\t<div class=\"acf-innerblocks-container\">\n\n<p>Most Rhino variants are discretionary to some degree. In such setups, the delta limits, scaling decisions, and hedge choices are guidelines, rather than a strict algorithm.<\/p>\n\n\n\n<p>These are often choices of the developer. To quote Bruno:<\/p>\n\n\n\n<p>&#8220;I would never use specific mechanical rules, simple or sophisticated, and instead chose meta parameters in the form of risk management ratios combining margin and Greeks.&#8221;<\/p>\n\n\n\n<p>While we respect Bruno&#8217;s opinion, we believe that clear rules are essential for trading, at least when it comes to strategies we trade. This disparity is common in the trading world: traders are frequently opinionated and there is no single &#8220;correct&#8221; way to trade.<\/p>\n\n\n\n<p>When recreating these trades in MesoSim, we aimed to:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Respect the&nbsp;<strong>spirit<\/strong>&nbsp;of each author\u2019s intent<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Acknowledge that any exact rule set we encode will inevitably reflect some of&nbsp;<strong>our<\/strong>&nbsp;choices.<\/li>\n<\/ul>\n\n\n\n<p>To keep things honest, we share backtests based on the rules available at the time of development.<\/p>\n\n\n\n<p>The Rhino\u2019s evolution is a case study in that principle.<\/p>\n\n<\/div>\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n<\/div>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"history\">History<\/h2>\n\n\n\n<p>If you are interested in the detailed evolution of the Rhino strategy, please click the&nbsp;<em><strong>Rhino Development History<\/strong><\/em>&nbsp;below. It contains a summary from all the presentations from Brian and Bruno, highlighting the key changes over time. We included the presentation links for reference.<\/p>\n\n\n<div class=\"accordion accordion-large\"> \n\t<div class=\"accordion-item\">\n\t\t<button id=\"accordionCampus-69d238d46c579\" class=\" collapsed w-100\" type=\"button\" data-bs-toggle=\"collapse\" data-bs-target=\"#collapseAccordion-69d238d46c579\" aria-expanded=\"false\" aria-controls=\"collapseAccordion-69d238d46c579\">\n\t\t\t<h3>Rhino Development History<\/h3>\n\t\t\t\t\t<\/button>\n\t\t<div class=\"accordion-collapse collapse\" id=\"collapseAccordion-69d238d46c579\" aria-labelledby=\"accordionCampus-69d238d46c579\" data-bs-parent=\"\">\n\t\t\t<div class=\"accordion-body\">\n\t\t\t\t<div class=\"acf-innerblocks-container\">\n\n<p><strong>2014-2017: Early Rhino<\/strong><\/p>\n\n\n\n<p>The early Rhino, as documented in the&nbsp;<a href=\"https:\/\/www.youtube.com\/watch?v=NBp8zzdrnXo\" target=\"_blank\" rel=\"noreferrer noopener\">Original Video<\/a>&nbsp;and Bruno&#8217;s&nbsp;<a href=\"https:\/\/blog.deltaray.io\/assets\/files\/2016-09-RhinoTrade-af105facd244184bed70e7acfda6d162.pptx\" target=\"_blank\" rel=\"noreferrer noopener\">2016<\/a>&nbsp;and&nbsp;<a href=\"https:\/\/blog.deltaray.io\/assets\/files\/2017-04-TheRhinoTrade-983e96405a77a3fac63ce5c0cd79bd4a.pptx\" target=\"_blank\" rel=\"noreferrer noopener\">2017 deck<\/a>, is a&nbsp;<strong>fixed\u2011distance RUT BWB with clear delta triggers and a profit target ladder.<\/strong><\/p>\n\n\n\n<p>Core features:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>RUT focus<\/strong>&nbsp;\u2013 Five 50\/40 put BWBs with upper longs 10\u201315 points ITM (later 0.5\u20131% ITM).<\/li>\n\n\n\n<li><strong>SPX variant<\/strong>&nbsp;\u2013 Three 80\/60 put BWBs (later 100\/75 and 75\/50 wings) with similar upper\u2011long bias.<\/li>\n\n\n\n<li><strong>Entry<\/strong>&nbsp;\u2013 Around 77 DTE on a down day if possible, to launch with a flat T+0 line and conservative downside coverage of roughly 5\u20137%. $25k planned capital per cycle.<\/li>\n\n\n\n<li><strong>Adjustment logic<\/strong>&nbsp;\u2013\n<ul class=\"wp-block-list\">\n<li>Negative delta beyond \u221225 (half) \/ \u221250 (full) \u2192 add call calendars, put verticals or condors, occasionally roll back BWBs.<\/li>\n\n\n\n<li>Positive delta beyond +25 \u2192 remove or roll hedges\/BWBs to flatten.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Exit<\/strong>&nbsp;\u2013 :\n<ul class=\"wp-block-list\">\n<li>The profit ladder (10\/8\/6\/4%)<\/li>\n\n\n\n<li>Exiting before gamma \u201cgets hard to handle\u201d (generally before ~21 DTE)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<p>The trade assumes a fairly \u201cnormal\u201d volatility regime. Fixed strikes and ATM entries mean:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>In very low vol, the tent is narrow and profits harder to reach.<\/li>\n\n\n\n<li>In very high vol, more capital sits near the money, and large moves require heavier hedging.<\/li>\n<\/ul>\n\n\n\n<p><strong>2017\u20132019: from trade to trade&nbsp;<em>family<\/em><\/strong><\/p>\n\n\n\n<p>By 2017\u20132018, Bruno emphasized that the real Rhino is less a single trade and more a&nbsp;<strong>family of BWBs run as a capital\u2011allocation process<\/strong>.<\/p>\n\n\n\n<p>Two ideas arrive here:<\/p>\n\n\n\n<p>1. <strong>Trade phases<\/strong><\/p>\n\n\n\n<p>From the 2018 decks (<a href=\"https:\/\/blog.deltaray.io\/assets\/files\/2018-07-TheRhinoTrade-4faebc423d568d7074d387dbc9017f9a.pptx\" target=\"_blank\" rel=\"noreferrer noopener\">deck 1<\/a>,&nbsp;<a href=\"https:\/\/blog.deltaray.io\/assets\/files\/2018-08-01-TheRhinoTrade-00addf90b82b3bf1613d6e4c7aa617aa.pptx\" target=\"_blank\" rel=\"noreferrer noopener\">deck 2<\/a>,&nbsp;<a href=\"https:\/\/blog.deltaray.io\/assets\/files\/2018-08-08-TheRhinoTrade-Part2-91efb7e5af9003fa0dbe2f49ad437320.pptx\" target=\"_blank\" rel=\"noreferrer noopener\">deck 3<\/a>&nbsp;and&nbsp;<a href=\"https:\/\/blog.deltaray.io\/assets\/files\/2018-08-09-TheRhinoTrade-Part2.1-c46484b7ad63b2e753bcfdda4688a808.pptx\" target=\"_blank\" rel=\"noreferrer noopener\">deck 4<\/a>):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Take\u2011off (Growth)<\/strong>&nbsp;\u2013 From entry (~77 DTE) down to roughly&nbsp;<strong>49\u201356 DTE<\/strong>. Build up to full size, preferably on down days.<\/li>\n\n\n\n<li><strong>Cruise (Maturity)<\/strong>&nbsp;\u2013 From there down to around&nbsp;<strong>28\u201335 DTE<\/strong>. Hold capital constant, focus on Greeks.<\/li>\n\n\n\n<li><strong>Descent (Getting Old)<\/strong>&nbsp;\u2013 Roughly&nbsp;<strong>35\u201321 DTE<\/strong>, later tightening to&nbsp;<strong>28\u201314 DTE<\/strong>. Protect profits, peel off, avoid loading gamma.<\/li>\n<\/ul>\n\n\n\n<p>Each capital reallocation step (scale\u2011in, peel\u2011off, roll) is a chance to rebalance delta and gamma, with delta triggers becoming a \u201cmeasure of last resort\u201d rather than the primary decision driver.<\/p>\n\n\n\n<p>2. <strong>Horizontal layering &amp; the Rhino family<\/strong><\/p>\n\n\n\n<p>The&nbsp;<a href=\"https:\/\/blog.deltaray.io\/assets\/files\/2019-TheRhinoStrategy-b35a99ddaf281ec7a611294a2429d7e7.pptx\" target=\"_blank\" rel=\"noreferrer noopener\">2019 Rhino Strategy<\/a>&nbsp;formalises three related trades:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Monthly Rhino<\/strong>&nbsp;\u2013 The original 77\u219214 DTE cycle.<\/li>\n\n\n\n<li><strong>Giant Rhino<\/strong>&nbsp;\u2013 Longer\u2011dated version (~100\u2013120 DTE into ~35 DTE).<\/li>\n\n\n\n<li><strong>Baby Rhino<\/strong>&nbsp;\u2013 Weekly 14\u21927 DTE short\u2011duration BWB, essentially a theta game on a short fly.<\/li>\n<\/ul>\n\n\n\n<p>Overlapping these cycles at different expirations introduces&nbsp;<strong>horizontal layering<\/strong>&nbsp;\u2014 smoothing P&amp;L and turning the Rhino into a small BWB portfolio rather than a single isolated position.<\/p>\n\n\n\n<p>Delta triggers also get sharpened:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Downside: trigger if&nbsp;<strong>delta &lt; \u22125 per BWB inside the tent<\/strong>.<\/li>\n\n\n\n<li>Upside: trigger when&nbsp;<strong>delta &gt; 5 per BWB<\/strong>&nbsp;(roughly 25 per BWB at full size), and when the lowest shorts are being passed.<\/li>\n<\/ul>\n\n\n\n<p><strong>2020-2022: Volatility-adaptive structures<\/strong><\/p>\n\n\n\n<p>The&nbsp;<a href=\"https:\/\/blog.deltaray.io\/assets\/files\/2021-04-EvolvingRhino-fc69474ae58ee309b8d63d289a215aa8.pptx\" target=\"_blank\" rel=\"noreferrer noopener\">Evolving Rhino<\/a>&nbsp;presentation emphesizes that the ruling principle of the trade:<\/p>\n\n\n\n<p>\u201cA flattish Delta over the largest possible range.\u201d<\/p>\n\n\n\n<p>Everything else \u2014 entry, wings, hedges, capital \u2014 is adjusted to serve that principle in a volatile, post\u20112018 market.<\/p>\n\n\n\n<p>Key changes from that presentation and the&nbsp;<a href=\"https:\/\/blog.deltaray.io\/assets\/files\/2022-01-RhinoUpdate-f3e0de543a7939a35e7674501ce6191a.pptx\" target=\"_blank\" rel=\"noreferrer noopener\">2022 high\u2011vol update<\/a>:<\/p>\n\n\n\n<p>1. <strong>OTM entries &amp; larger wings in high vol<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>ATM entries in high vol tend to start with&nbsp;<strong>positive delta<\/strong>&nbsp;and a very pressurised T+0.<\/li>\n\n\n\n<li>Solution: move the BWB&nbsp;<strong>further OTM<\/strong>&nbsp;and increase wing sizes when VIX is high.<\/li>\n<\/ul>\n\n\n\n<p>\u201cMajor Changes (1)\u201d section introduces simple rules of thumb for SPX:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Low vol<\/strong>&nbsp;(VIX \u2272 12.5): wings \u2248 75\/50<\/li>\n\n\n\n<li><strong>Normal vol<\/strong>&nbsp;(\u224812.5\u201319.5): wings \u2248 100\/75<\/li>\n\n\n\n<li><strong>High vol<\/strong>&nbsp;(VIX \u2273 19.5): wings \u2248 125\/100<\/li>\n<\/ul>\n\n\n\n<p>The PDS (debit) wing is weaker on an OTM Rhino, but the trade gains robustness in volatile markets and is less sensitive to \u201cvol pops.\u201d<\/p>\n\n\n\n<p>2. <strong>Phase\u2011based capital management<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Take\u2011off: build to planned capital by about&nbsp;<strong>49 DTE<\/strong>.<\/li>\n\n\n\n<li>Cruise: keep capital stable&nbsp;<strong>49\u219228 DTE<\/strong>.<\/li>\n\n\n\n<li>Descent: gradually cut exposure&nbsp;<strong>28\u219210\u201314 DTE<\/strong>&nbsp;and either exit or leave at most&nbsp;<strong>\u00bc of planned capital<\/strong>&nbsp;in the old cycle.<\/li>\n<\/ul>\n\n\n\n<p>3. <strong>Risk metrics: MtE &amp; VaR<\/strong><\/p>\n\n\n\n<p>Rather than managing only by per\u2011trade delta, Bruno introduces:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Margin\u2011to\u2011expiration (MtE)<\/strong>&nbsp;bands (or similar VaR\u2011style limits) across all open cycles:\n<ul class=\"wp-block-list\">\n<li>Conservative: 35% with occasional peaks to 45%<\/li>\n\n\n\n<li>Balanced: 50% with peaks to 60%<\/li>\n\n\n\n<li>Aggressive: 65% with peaks to 70%<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<p>Delta triggers remain, but capital and margin become the primary risk knobs.<\/p>\n\n\n\n<p>4. <strong>Hedging style<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Upside<\/strong>&nbsp;\u2013 Narrow&nbsp;<strong>30\u2011delta call calendars<\/strong>&nbsp;placed above strong resistance levels act as \u201cspeedbumps\u201d in bullish high\u2011vol regimes. <\/li>\n\n\n\n<li><strong>Downside<\/strong>&nbsp;\u2013 Layered convexity:\n<ul class=\"wp-block-list\">\n<li>Inner&nbsp;<strong>put debit spreads<\/strong>, outer&nbsp;<strong>put credit spreads<\/strong>&nbsp;(PDS\/PCS).<\/li>\n\n\n\n<li>Occasional&nbsp;<strong>put calendar below the lowest shorts<\/strong>, particularly as part of a \u201croll in one go\u201d crash response.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<p>5. <strong>Profit expectations<\/strong><\/p>\n\n\n\n<p>In this high\u2011vol, conservative variant Bruno explicitly sets:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Profit target:&nbsp;<strong>around 2% of planned capital<\/strong>&nbsp;per cycle<\/li>\n\n\n\n<li>Exit at ~14 DTE or reduce exposure to \u2264\u00bc planned capital<\/li>\n<\/ul>\n\n\n\n<p>The modern conservative Rhino is therefore:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Still recognisably the same trade<\/li>\n\n\n\n<li>Less about rigid delta numbers, more about&nbsp;<strong>MtE bands, overlapping cycles, and a flattish delta shape across regimes<\/strong><\/li>\n<\/ul>\n\n\n\n<p><strong>2023: Flexibility to adapt to lower vol &amp; 0DTE effects<\/strong><\/p>\n\n\n\n<p>The&nbsp;<a href=\"https:\/\/blog.deltaray.io\/assets\/files\/2023-Rhino-OverdueUpdate-03e346047401a51f271dce3dd72f45a9.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">2023&nbsp;<em>\u201cAn Overdue Rhino Update\u201d<\/em><\/a>&nbsp;revisits the strategy in the context of today\u2019s market: lower headline volatility but heavy 0-DTE activity, Interest Rate changes and fast\u2011flipping regimes.<\/p>\n\n\n\n<p>Key messages:<\/p>\n\n\n\n<p>1. <strong>Environment: lower vol is not automatically safer<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Volatility regimes are changing rapidly; SPX and VIX still mean\u2011revert against each other, but their correlation can be unstable.<\/li>\n\n\n\n<li>Interest rates have moved but remain moderate; for options traders, the more important changes are in equity risk appetite and FX correlations.<\/li>\n\n\n\n<li>A huge share of CBOE volume is now 0DTE. On some days these flows approach 50% of volume, concentrating dealer gamma and creating strong intraday \u201cattractors.\u201d<\/li>\n<\/ul>\n\n\n\n<p>The takeaway:&nbsp;<strong>\u201cLower volatility = higher risk\u201d<\/strong>&nbsp;for a slow income trade that sells options across weeks, because short\u2011dated order flow can whip prices through your tent.<\/p>\n\n\n\n<p>2. <strong>Market reading: a \u201cdelta\u2011neutral\u201d trade is not market\u2011neutral<\/strong><\/p>\n\n\n\n<p>Bruno doubles down on basic market reading:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Use simple chart levels: support\/resistance, fibs, basic patterns.<\/li>\n\n\n\n<li>Track key drivers like the big tech stocks and correlated indices (NDX, DJI).<\/li>\n\n\n\n<li>Watch dealer gamma and vanna (GEX &amp; VEX) to understand where dealers are likely to push or defend prices.<\/li>\n<\/ul>\n\n\n\n<p>3. <strong>What has changed: more flexibility<\/strong><\/p>\n\n\n\n<p>The \u201cWhat has changed\u201d slide highlights&nbsp;<strong>flexibility and tool choice<\/strong>&nbsp;in lower\u2011vol conditions:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>The \u201ctypical\u201d BWB (on 25\u2011point strikes in his book) can sometimes be replaced with a&nbsp;<strong>split\u2011strike BWB<\/strong>&nbsp;to better fit local skew.<\/li>\n\n\n\n<li>Call calendars can be&nbsp;<strong>substituted with call diagonals<\/strong>&nbsp;where the goal is to \u201cgo with the flow\u201d \u2014 participating in bullish moves while keeping vega exposure smaller than with horizontal spreads.<\/li>\n\n\n\n<li>When the trader admits to being \u201ctotally lost\u201d about short\u2011term direction, Bruno suggests falling back on a reasonable&nbsp;<strong>delta\/vega ratio<\/strong>, roughly similar to the balanced profile used in the cruise phase.<\/li>\n<\/ul>\n\n\n\n<p>In other words, the modern Rhino toolkit is broader: calendars, diagonals, split\u2011strike BWBs, balanced flies all live under the same philosophy.<\/p>\n\n<\/div>\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n<\/div>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-rhino-in-mesosim\">Rhino in MesoSim<\/h2>\n\n\n\n<p>Many variants &#8211; public and proprietary &#8211; of the Rhino trade exist as MesoSim Strategy Definitions, and we can\u2019t cover them all here. We will try to capture the final version presented by Bruno in 2023, with some adjustments to match our personal beliefs and preferences.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-our-preferences\">Our preferences<\/h3>\n\n\n\n<p>There are, however, some aspects we have adjusted to match our personal beliefs and preferences:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>The market reading part (support \/ resistance, fibs, chart patterns) is excluded as we accept the thesis provided by David Aronson in his&nbsp;<a href=\"https:\/\/www.amazon.com\/Evidence-Based-Technical-Analysis-Scientific-Statistical\/dp\/0470008741\" target=\"_blank\" rel=\"noreferrer noopener\">Evidence Based Technical Analysis<\/a>&nbsp;book.<\/li>\n\n\n\n<li>The upside hedge (Call Calendar) side is added from the beginning of the trade.<\/li>\n\n\n\n<li>The structure is delta-neutral at initiation<\/li>\n<\/ul>\n\n\n\n<p>We used ChatGPT for Strategy Development:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><em>GPT-5 Pro<\/em>&nbsp;model with Extended Thinking time was used to obtain the trade rules. We provided the model with all the public presentations (available in the&nbsp;<a href=\"https:\/\/blog.deltaray.io\/rhino-options-strategy\/#history\">History<\/a>&nbsp;section above), and asked it to summarise the latest rules of the trade.<\/li>\n\n\n\n<li>The&nbsp;<a href=\"https:\/\/chatgpt.com\/g\/g-690516c500b8819191e154543a9a85a7-mesosim-ai-assistant\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>MesoSim AI Agent<\/strong><\/a>&nbsp;was used to convert the rules into MesoSim Strategy Definition. The agent is a GPT-5 based assistant trained on MesoSim&#8217;s&nbsp;<a href=\"https:\/\/docs.mesosim.io\/\" target=\"_blank\" rel=\"noreferrer noopener\">documentation<\/a>,&nbsp;<a href=\"https:\/\/blog.deltaray.io\/tags\/strategies\">strategies<\/a>&nbsp;and blog posts.<\/li>\n\n\n\n<li>We reviewed the generated Strategy Definition and confirmed it is aligned with the public presentations. We needed to adjust the adjustment trigger delta and the Concurrency.MaxPositionsInFlight to match the trade plan.<\/li>\n<\/ul>\n\n\n\n<p>The resulting Strategy Definition can be summarized as follows:<\/p>\n\n\n\n<p><strong>Underlying<\/strong>: SPX<\/p>\n\n\n\n<p><strong>Tenors<\/strong>: front month around ~77 DTE (window 56\u201384), back month ~107 DTE.<\/p>\n\n\n\n<p><strong>Core structure<\/strong>&nbsp;at entry (5 legs):<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th>Parameter<\/th><th>VIX &lt; 12.5<\/th><th>12.5 &lt; VIX &lt; 19.5<\/th><th>VIX &gt; 19.5<\/th><\/tr><\/thead><tbody><tr><td>BWB Upper Long OTM offset from ATM<\/td><td>15 pts<\/td><td>25 pts<\/td><td>35 pts<\/td><\/tr><tr><td>BWB Upper Long &#8211; Shorts width<\/td><td>75 pts<\/td><td>100 pts<\/td><td>125 pts<\/td><\/tr><tr><td>BWB Shorts &#8211; Lower Long width<\/td><td>50 pts<\/td><td>75 pts<\/td><td>100 pts<\/td><\/tr><tr><td>Calendar Shorts Delta<\/td><td>30 \u0394<\/td><td>30 \u0394<\/td><td>30 \u0394<\/td><\/tr><tr><td>Calendar Longs Delta<\/td><td>30 \u0394<\/td><td>30 \u0394<\/td><td>30 \u0394<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p><strong>Entry<\/strong>: Daily, 30 min before close, only on \u201cvery down day\u201d:&nbsp;<code>price &lt; open &lt; prior close<\/code>. Concurrency allows up to 9 positions with 7-day entry spacing.<\/p>\n\n\n\n<p><strong>Adjustments<\/strong>: Daily, 30 min before close<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Phase 2 BWB: If the original\u2019s DTE in [49,56] and only the 5 initial legs are open, add a second BWB (same VIX-mapped logic).<\/li>\n\n\n\n<li>Delta guards with calendars:\n<ul class=\"wp-block-list\">\n<li>If pos_delta &lt; \u22125 and no second calendar yet, add a second call calendar (front short ~30\u0394, back long \u0394 \u2248 |pos_delta|)<\/li>\n\n\n\n<li>If pos_delta &gt; 5, remove all calendar legs.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>Downside repair: If spot &lt; BWB short strike, add a put debit spread (\u22121 at short_strike\u221210pts \/ +1 at short_strike\u221230pts ).<\/li>\n\n\n\n<li>De-risk late: If the extra BWB exists and the first BWB\u2019s DTE \u2264 28, remove the second BWB set.<\/li>\n<\/ul>\n\n\n\n<p><strong>Exit<\/strong>: Daily, 30 min before close; profit target = $500, stop loss = $2,500 (both constants scaled from $25k base); OR exit if front BWB DTE \u2264 14<\/p>\n\n\n\n<p><strong>Fills, fees, margin<\/strong>: At mid (no slippage), $1.50\/contract, PM-like margin<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-risk-graphs\">Risk Graphs<\/h3>\n\n\n\n<p>Here are the Risk Graphs at various stages:<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1100\" height=\"814\" data-src=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-risk-graph-entry-1100x814.png\" alt=\"Rhino Strategy Family\" class=\"wp-image-234685 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-risk-graph-entry-1100x814.png 1100w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-risk-graph-entry-700x518.png 700w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-risk-graph-entry-300x222.png 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-risk-graph-entry-768x569.png 768w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-risk-graph-entry-1536x1137.png 1536w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-risk-graph-entry.png 1880w\" data-sizes=\"(max-width: 1100px) 100vw, 1100px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1100px; aspect-ratio: 1100\/814;\" \/><\/figure>\n\n\n\n<p>Source: MesoSim<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1100\" height=\"812\" data-src=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-risk-graph-double-bwb-cal-1100x812.png\" alt=\"Rhino Strategy Family\" class=\"wp-image-234686 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-risk-graph-double-bwb-cal-1100x812.png 1100w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-risk-graph-double-bwb-cal-700x517.png 700w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-risk-graph-double-bwb-cal-300x221.png 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-risk-graph-double-bwb-cal-768x567.png 768w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-risk-graph-double-bwb-cal-1536x1134.png 1536w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-risk-graph-double-bwb-cal.png 1864w\" data-sizes=\"(max-width: 1100px) 100vw, 1100px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1100px; aspect-ratio: 1100\/812;\" \/><\/figure>\n\n\n\n<p>Source: MesoSim<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1100\" height=\"823\" data-src=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-risk-graph-bwb-with-pds-1100x823.png\" alt=\"Rhino Strategy Family\" class=\"wp-image-234688 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-risk-graph-bwb-with-pds-1100x823.png 1100w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-risk-graph-bwb-with-pds-700x523.png 700w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-risk-graph-bwb-with-pds-300x224.png 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-risk-graph-bwb-with-pds-768x574.png 768w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-risk-graph-bwb-with-pds-1536x1149.png 1536w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-risk-graph-bwb-with-pds.png 1856w\" data-sizes=\"(max-width: 1100px) 100vw, 1100px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1100px; aspect-ratio: 1100\/823;\" \/><\/figure>\n\n\n\n<p>Source: MesoSim<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"backtest-summary\">Backtest Summary<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong><a href=\"https:\/\/mesosim.io\/backtests\/6dffc016-e6bb-4e97-9b1c-16c66f662ed0\" target=\"_blank\" rel=\"noreferrer noopener\">MesoSim run: Rhino-SPX<\/a><\/strong><\/li>\n\n\n\n<li><strong>Backtest period<\/strong>: 2018-01-01 to 2025-11-11<\/li>\n\n\n\n<li><strong>Sharpe Ratio<\/strong>: 1.12<\/li>\n\n\n\n<li><strong>CAGR<\/strong>&nbsp;\/&nbsp;<strong>Max Drawdown<\/strong>: 3.15% \/ -2.81%<\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1100\" height=\"612\" data-src=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-backtest-results-1100x612.png\" alt=\"Rhino Strategy Family\" class=\"wp-image-234690 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-backtest-results-1100x612.png 1100w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-backtest-results-700x389.png 700w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-backtest-results-300x167.png 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-backtest-results-768x427.png 768w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-backtest-results-1536x854.png 1536w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-backtest-results-2048x1139.png 2048w\" data-sizes=\"(max-width: 1100px) 100vw, 1100px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1100px; aspect-ratio: 1100\/612;\" \/><\/figure>\n\n\n\n<p>Source: MesoSim<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1100\" height=\"821\" data-src=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-tearsheet-1-1100x821.png\" alt=\"Rhino Strategy Family\" class=\"wp-image-234691 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-tearsheet-1-1100x821.png 1100w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-tearsheet-1-700x522.png 700w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-tearsheet-1-300x224.png 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-tearsheet-1-768x573.png 768w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-tearsheet-1-1536x1146.png 1536w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-tearsheet-1.png 1842w\" data-sizes=\"(max-width: 1100px) 100vw, 1100px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1100px; aspect-ratio: 1100\/821;\" \/><\/figure>\n\n\n\n<p>Source: MesoSim<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1100\" height=\"751\" data-src=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-tearsheet-2-1100x751.png\" alt=\"Rhino Strategy Family\" class=\"wp-image-234692 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-tearsheet-2-1100x751.png 1100w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-tearsheet-2-700x478.png 700w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-tearsheet-2-300x205.png 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-tearsheet-2-768x525.png 768w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-tearsheet-2-1536x1049.png 1536w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-tearsheet-2.png 1836w\" data-sizes=\"(max-width: 1100px) 100vw, 1100px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1100px; aspect-ratio: 1100\/751;\" \/><\/figure>\n\n\n\n<p>Source: MesoSim<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1100\" height=\"811\" data-src=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-tearsheet-3-1100x811.png\" alt=\"Rhino Strategy Family\" class=\"wp-image-234693 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-tearsheet-3-1100x811.png 1100w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-tearsheet-3-700x516.png 700w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-tearsheet-3-300x221.png 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-tearsheet-3-768x567.png 768w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-tearsheet-3-1536x1133.png 1536w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/rhino-tearsheet-3.png 1822w\" data-sizes=\"(max-width: 1100px) 100vw, 1100px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1100px; aspect-ratio: 1100\/811;\" \/><\/figure>\n\n\n\n<p>Source: MesoSim<\/p>\n\n\n\n<p><strong>Tip<\/strong><\/p>\n\n\n\n<p>The above implementation is a fairly complex Strategy Definition, with multiple adjustments (structures added dynamically), scaling rules, and risk checks. If you need help understanding the Strategy Definition elements you can paste the Strategy Definition to the MesoSim AI agent and ask for explanations. You can start here:&nbsp;<a href=\"https:\/\/chatgpt.com\/share\/6917508b-1bcc-800d-ba72-ac0c38421ff5\" target=\"_blank\" rel=\"noreferrer noopener\">Explain the Rhino Strategy Definition<\/a><\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"other-variants\">Other variants<\/h2>\n\n\n\n<p>A little detour to mention related trades we have first-hand experience with: A14 and BWB-Cal.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-note\">note<\/h3>\n\n\n\n<p>Because the A14 and BWB\u2011CD are proprietary trades, we won\u2019t publish their MesoSim strategy definitions. We can provide them on request where the requester\u2019s eligibility (e.g. active membership in the relevant service) can be verified.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"a14-by-amy-meissner\">A14 by Amy Meissner<\/h3>\n\n\n\n<p>The A14 Trade was developed by Amy Meissner and can be obtained (for a fee) from Aeromir. We got to know A14 before the Rhino and it influenced how MesoSim adjustments were designed.<\/p>\n\n\n\n<p>Our live trading experience showed that the volatility of the strategy is beyond our comfort zone and we stopped trading it after a few cycles.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1100\" height=\"615\" data-src=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-backtest-results-1100x615.png\" alt=\"Rhino Strategy Family\" class=\"wp-image-235260 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-backtest-results-1100x615.png 1100w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-backtest-results-700x391.png 700w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-backtest-results-300x168.png 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-backtest-results-768x429.png 768w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-backtest-results-1536x858.png 1536w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-backtest-results-2048x1144.png 2048w\" data-sizes=\"(max-width: 1100px) 100vw, 1100px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1100px; aspect-ratio: 1100\/615;\" \/><\/figure>\n\n\n\n<p>Source: MesoSim<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1100\" height=\"851\" data-src=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-tearsheet-1-1100x851.png\" alt=\"Rhino Strategy Family\" class=\"wp-image-235262 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-tearsheet-1-1100x851.png 1100w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-tearsheet-1-700x541.png 700w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-tearsheet-1-300x232.png 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-tearsheet-1-768x594.png 768w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-tearsheet-1-1536x1188.png 1536w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-tearsheet-1.png 1968w\" data-sizes=\"(max-width: 1100px) 100vw, 1100px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1100px; aspect-ratio: 1100\/851;\" \/><\/figure>\n\n\n\n<p>Source: MesoSim<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1100\" height=\"729\" data-src=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-tearsheet-2-1-1100x729.png\" alt=\"Rhino Strategy Family\" class=\"wp-image-235264 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-tearsheet-2-1-1100x729.png 1100w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-tearsheet-2-1-700x464.png 700w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-tearsheet-2-1-300x199.png 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-tearsheet-2-1-768x509.png 768w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-tearsheet-2-1-1536x1018.png 1536w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-tearsheet-2-1.png 1976w\" data-sizes=\"(max-width: 1100px) 100vw, 1100px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1100px; aspect-ratio: 1100\/729;\" \/><\/figure>\n\n\n\n<p>Source: MesoSim<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1100\" height=\"831\" data-src=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-tearsheet-3-1100x831.png\" alt=\"Rhino Strategy Family\" class=\"wp-image-235265 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-tearsheet-3-1100x831.png 1100w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-tearsheet-3-700x529.png 700w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-tearsheet-3-300x227.png 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-tearsheet-3-768x580.png 768w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-tearsheet-3-1536x1160.png 1536w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/a14-tearsheet-3.png 1978w\" data-sizes=\"(max-width: 1100px) 100vw, 1100px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1100px; aspect-ratio: 1100\/831;\" \/><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<p>Source: MesoSim<\/p>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"backtest-summary-1\">Backtest Summary<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Backtest period<\/strong>: 2018-01-01 to 2025-11-11<\/li>\n\n\n\n<li><strong>Sharpe Ratio<\/strong>: 0.81<\/li>\n\n\n\n<li><strong>CAGR<\/strong>&nbsp;\/&nbsp;<strong>Max Drawdown<\/strong>: 9.3% \/ -22.05%<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"bwb-cal-by-ron-bertino\">BWB-Cal by Ron Bertino<\/h3>\n\n\n\n<p>The BWB-Cal trade was developed by Ron Bertino from Trading Dominion and the trade plan is available in the MasterMind service. This strategy uses longer-dated tenors and does not contain any adjustments. The strategy we traded had additional hedges (2LPs in a third expiration cycle), which were added to mitigate the drawdowns observed during COVID.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"backtest-summary-2\">Backtest Summary<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Backtest period<\/strong>: 2018-01-01 to 2025-11-11<\/li>\n\n\n\n<li><strong>Sharpe Ratio<\/strong>: 1.65<\/li>\n\n\n\n<li><strong>CAGR<\/strong>&nbsp;\/&nbsp;<strong>Max Drawdown<\/strong>: 10.51% \/ -6.67%<\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1100\" height=\"610\" data-src=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-backtest-results-1100x610.png\" alt=\"Rhino Strategy Family\" class=\"wp-image-234707 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-backtest-results-1100x610.png 1100w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-backtest-results-700x388.png 700w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-backtest-results-300x166.png 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-backtest-results-768x426.png 768w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-backtest-results-1536x852.png 1536w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-backtest-results-2048x1136.png 2048w\" data-sizes=\"(max-width: 1100px) 100vw, 1100px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1100px; aspect-ratio: 1100\/610;\" \/><\/figure>\n\n\n\n<p>Source: MesoSim<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1100\" height=\"802\" data-src=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-tearsheet-1-1100x802.png\" alt=\"Rhino Strategy Family\" class=\"wp-image-234708 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-tearsheet-1-1100x802.png 1100w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-tearsheet-1-700x510.png 700w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-tearsheet-1-300x219.png 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-tearsheet-1-768x560.png 768w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-tearsheet-1-1536x1120.png 1536w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-tearsheet-1.png 2024w\" data-sizes=\"(max-width: 1100px) 100vw, 1100px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1100px; aspect-ratio: 1100\/802;\" \/><\/figure>\n\n\n\n<p>Source: MesoSim<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1100\" height=\"743\" data-src=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-tearsheet-2-1100x743.png\" alt=\"Rhino Strategy Family\" class=\"wp-image-234709 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-tearsheet-2-1100x743.png 1100w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-tearsheet-2-700x473.png 700w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-tearsheet-2-300x203.png 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-tearsheet-2-768x519.png 768w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-tearsheet-2-1536x1037.png 1536w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-tearsheet-2-2048x1383.png 2048w\" data-sizes=\"(max-width: 1100px) 100vw, 1100px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1100px; aspect-ratio: 1100\/743;\" \/><\/figure>\n\n\n\n<p>Source: MesoSim<\/p>\n\n\n\n<p><\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1100\" height=\"813\" data-src=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-tearsheet-3-1100x813.png\" alt=\"Rhino Strategy Family\" class=\"wp-image-234710 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-tearsheet-3-1100x813.png 1100w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-tearsheet-3-700x517.png 700w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-tearsheet-3-300x222.png 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-tearsheet-3-768x567.png 768w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-tearsheet-3-1536x1135.png 1536w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/bwb-cal-tearsheet-3.png 1976w\" data-sizes=\"(max-width: 1100px) 100vw, 1100px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1100px; aspect-ratio: 1100\/813;\" \/><\/figure>\n\n\n\n<p>Source: MesoSim<\/p>\n\n\n\n<p>We traded this strategy live between 2022. June and 2023. March. The 2022 performance was convincing but the 2023 performance wiped the previous year&#8217;s profits. Other MasterMind members at the time achieved similar live-trading performance. To quote Brad: &#8220;IV up and Skew up. Double whammy&#8221;<\/p>\n\n\n\n<p>The two years of sideways performance confirm that it was the right choice to stop this trade. We attribute the lack of performance to changes in the market dynamics, similarly as we saw it with the&nbsp;<a href=\"https:\/\/blog.deltaray.io\/netzero-skew-this\">NetZero Trade<\/a>.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"geneticrhino-25q4\">GeneticRhino-25Q4<\/h2>\n\n\n\n<p>We believe that optimization and re-optimization is an essential part of every trade lifecycle and, as researchers, our goal is to come up with better performing variant. When it comes to optimization &#8211; manual or automated &#8211; overfitting is always a risk, but we believe that with proper precautions it can be mitigated. We will use a Genetic Algorithm to find a good-enough solution in a reasonable time-frame. As the name of this section implies: we suggest redoing this optimization at least quarterly.<\/p>\n\n\n\n<p>The original Rhino is a fairly dynamic trade: structures (BWB, PDS, Calendars) are added and removed. This dynamism comes with costs:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>it&#8217;s more difficult to reason about: one needs to understand multiple structure combinations with varying wing-lengths<\/li>\n\n\n\n<li>contains more parameters and thresholds to tune.<\/li>\n<\/ul>\n\n\n\n<p>Therefore, we apply the following simplifications of the trade before optimizing:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Initiation<\/strong>: The original trade has a fairly complex (VIX-based) leg selection. Our intuition (and later, experience) tells us that the leg selection can be simplified by delta-based rules as delta is derived from volatilities. This can replace the VIX-based wing-width calculation while keeping the same risk profile.<\/li>\n\n\n\n<li><strong>Adjustments<\/strong>: Layering and adding structures definitely shape the overall delta, but MesoSim supports this natively using the&nbsp;<a href=\"https:\/\/docs.mesosim.io\/faq\/multiple-pos-in-flight\" target=\"_blank\" rel=\"noreferrer noopener\">Campaign-style trading<\/a>. Moving single legs around to adjust delta is a well-known practice, and &#8211; we believe &#8211; that it can provide a more cost-effective mean to keep the position delta in check.<\/li>\n\n\n\n<li><strong>Exit<\/strong>: In cases of strongly trending markets it might happen that the underlying leaves the tent completely, rendering the trade&#8217;s outcome negative. Exiting and re-entering at that stage is a better option than trying to balance deltas using single leg moves.<\/li>\n<\/ul>\n\n\n\n<p>Taking the above into consideration we&#8217;re tasked with obtaining the optimal settings for the trade. Our decision space is defined as follows:<\/p>\n\n\n<div class=\"accordion accordion-large\"> \n\t<div class=\"accordion-item\">\n\t\t<button id=\"accordionCampus-69d238d46e0b1\" class=\" collapsed w-100\" type=\"button\" data-bs-toggle=\"collapse\" data-bs-target=\"#collapseAccordion-69d238d46e0b1\" aria-expanded=\"false\" aria-controls=\"collapseAccordion-69d238d46e0b1\">\n\t\t\t<h3>Decision Space<\/h3>\n\t\t\t\t\t<\/button>\n\t\t<div class=\"accordion-collapse collapse\" id=\"collapseAccordion-69d238d46e0b1\" aria-labelledby=\"accordionCampus-69d238d46e0b1\" data-bs-parent=\"\">\n\t\t\t<div class=\"accordion-body\">\n\t\t\t\t<div class=\"acf-innerblocks-container\">\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th>Numerical Parameter<\/th><th>Minimum<\/th><th>Maximum<\/th><th>Step<\/th><\/tr><\/thead><tbody><tr><td>expiration_front_dte<\/td><td>7<\/td><td>100<\/td><td>4<\/td><\/tr><tr><td>expiration_front_to_back_distance<\/td><td>7<\/td><td>30<\/td><td>1<\/td><\/tr><tr><td>max_days_in_trade<\/td><td>1<\/td><td>expiration_front_dte<\/td><td>2<\/td><\/tr><tr><td>lower_long_delta<\/td><td>3<\/td><td>10<\/td><td>1<\/td><\/tr><tr><td>short_put_delta<\/td><td>lower_long_delta<\/td><td>30<\/td><td>1<\/td><\/tr><tr><td>upper_long_delta<\/td><td>short_put_delta<\/td><td>50<\/td><td>1<\/td><\/tr><tr><td>short_cal_delta<\/td><td>15<\/td><td>50<\/td><td>1<\/td><\/tr><tr><td>delta_adj_threshold_lower (a1)<\/td><td>5<\/td><td>20<\/td><td>5<\/td><\/tr><tr><td>delta_adj_threshold_upper (a2)<\/td><td>-5<\/td><td>-20<\/td><td>-5<\/td><\/tr><tr><td>delta_cutoff<\/td><td><code>max(a1, a2) + 5<\/code><\/td><td><code>max(a1, a2) + 15<\/code><\/td><td>1<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th>Categorical Parameter<\/th><th>Values<\/th><\/tr><\/thead><tbody><tr><td>adjustment_leg_name_lower<\/td><td>short_put \/ lower_long_put \/ upper_long_put<\/td><\/tr><tr><td>adjustment_leg_name_upper<\/td><td>short_call \/ long_call<\/td><\/tr><tr><td>lower_cutoff_leg_name<\/td><td>short_put \/ lower_long_put \/ upper_long_put<\/td><\/tr><tr><td>upper_cutoff_leg_name<\/td><td>short_call \/ long_call<\/td><\/tr><\/tbody><\/table><\/figure>\n\n<\/div>\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n<\/div>\n\n\n\n<p>The dumbest (and most thorough) approach is to simply brute-force the expirations, deltas, adjustment thresholds and exit rules. Even with the simplified setup, the total number of combinations are enormous:<br><\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">648 \u00d7 24 \u00d7 6440 \u00d7 36 \u00d7 4 \u00d7 4 \u00d7 11 \u00d7 3 \u00d7 2 \u00d7 3 \u00d7 2 = 22,844,927,508,480 combinations.<\/pre>\n\n\n\n<p>We can&#8217;t tackle this using brute-force, but we can use Genetic Algorithms to find a good-enough solution in a reasonable time-frame.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"mesominer\">MesoMiner<\/h3>\n\n\n\n<p><strong>MesoMiner<\/strong>&nbsp;is our latest addition to the&nbsp;<a href=\"https:\/\/deltaray.io\/fundpro\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>FundPro offering<\/strong><\/a>&nbsp;which is built to tackle exactly this type of problem:<\/p>\n\n\n\n<p>MesoMiner was inspired by Google&#8217;s&nbsp;<a href=\"https:\/\/deepmind.google\/blog\/alphaevolve-a-gemini-powered-coding-agent-for-designing-advanced-algorithms\/\" target=\"_blank\" rel=\"noreferrer noopener\">AlphaEvolve<\/a>&nbsp;and blends AI models with evolutionary algorithms to efficiently explore large decision spaces.<\/p>\n\n\n\n<p>As with any optimization (and trade development) process, there is a risk of overfitting. We mitigate this risk by:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Using an In-Sample (IS) and Out-Of-Sample (OOS) period split (50\/50)<\/li>\n\n\n\n<li>Rely on Deflated Sharpe Ratio to account for the multiple testing bias<\/li>\n\n\n\n<li>Keeping the original trade structure (BWB + Cal) defined using Min \/ Max ranges during the leg selection process<\/li>\n<\/ul>\n\n\n\n<p>You can read more about the IS \/ OOS split and DSR below.<\/p>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:100%\">\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:100%\"><div id=\"accordion-sm-69d238d46e56c\" class=\"accordion accordion-small\"> \n\t<div class=\"accordion-item\">\n\t\t<button id=\"accordionCampus-69d238d46e56c\" class=\"collapsed w-100\" type=\"button\" data-bs-toggle=\"collapse\" data-bs-target=\"#collapseAccordion-69d238d46e56c\" aria-expanded=\"false\" aria-controls=\"collapseAccordion-69d238d46e56c\">\n\t\t\t<h6>IS \/ OOS Split<\/h6>\n\t\t\t\t\t<\/button>\n\t\t<div class=\"accordion-collapse collapse\" id=\"collapseAccordion-69d238d46e56c\" aria-labelledby=\"accordionCampus-69d238d46e56c\" data-bs-parent=\"#accordion-sm-69d238d46e56c\">\n\t\t\t<div class=\"accordion-body\">\n\t\t\t\t<div class=\"acf-innerblocks-container\">\n\n<p>While doing the IS \/ OOS split, we take the approach of optimizing in the most recent period (2022-2025) and validating in the older period (2018-2022). Both periods contain market turmoils (e.g. 2020 Covid crash, 2024 VolZilla), sideways and trending markets.<\/p>\n\n\n\n<p>Researchers often set the OOS period is to the most recent period, but our experience is that the benefits of having a recently optimized strategy outweight the drawbacks. Using the older data in the OOS period results in a trade optimized (IS) for the most recent period. It&#8217;s easy to see that an optimized trade performance will&nbsp;<em>likely<\/em>&nbsp;be better tomorrow, than 1 or 10 years from now. Since there is no overlap between the two periods, the validation is valid either way.<\/p>\n\n<\/div>\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:100%\">\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:100%\"><div id=\"accordion-sm-69d238d46e9fd\" class=\"accordion accordion-small\"> \n\t<div class=\"accordion-item\">\n\t\t<button id=\"accordionCampus-69d238d46e9fd\" class=\"collapsed w-100\" type=\"button\" data-bs-toggle=\"collapse\" data-bs-target=\"#collapseAccordion-69d238d46e9fd\" aria-expanded=\"false\" aria-controls=\"collapseAccordion-69d238d46e9fd\">\n\t\t\t<h6>Deflated Sharpe Ratio (DSR)<\/h6>\n\t\t\t\t\t<\/button>\n\t\t<div class=\"accordion-collapse collapse\" id=\"collapseAccordion-69d238d46e9fd\" aria-labelledby=\"accordionCampus-69d238d46e9fd\" data-bs-parent=\"#accordion-sm-69d238d46e9fd\">\n\t\t\t<div class=\"accordion-body\">\n\t\t\t\t<div class=\"acf-innerblocks-container\">\n\n<p>Introduced by Marcos L\u00f3pez de Prado and David H. Bailey in&nbsp;<a href=\"https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=2460551\" target=\"_blank\" rel=\"noreferrer noopener\">The Deflated Sharpe Ratio: Correcting for Selection Bias, Backtest Overfitting and Non-Normality (2014)<\/a>, the Deflated Sharpe Ratio provides a principled way to account for optimization processes.<\/p>\n\n\n\n<p>It adjusts a strategy\u2019s Sharpe ratio for the two forces that typically inflate backtest results: selection bias from testing many configurations, and the non-normal shape of real-world returns.<\/p>\n\n\n\n<p>The key idea is that when a researcher runs a large number of trials, the best-performing Sharpe ratio is almost always upwardly biased. The DSR corrects this by replacing the usual zero-Sharpe benchmark with the expected maximum Sharpe produced purely by chance, a value derived from the distribution of Sharpe ratios across all trials<\/p>\n\n\n\n<p>The&nbsp;<em>Deflated Sharpe Ratio (DSR)<\/em>&nbsp;is a metric similar to Sharpe, whereas the&nbsp;<em>DSR Probability<\/em>&nbsp;is the final output of the DSR computation: the probability that the strategy\u2019s Sharpe ratio is truly positive after accounting for multiple trials and the skew and kurtosis of the actual return series.<\/p>\n\n<\/div>\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"optimization-results\">Optimization results<\/h3>\n\n\n\n<p>MesoMiner was run with a population size of 50 for 20 generations on the In-Sample period 2022-01-01 to 2025-11-11. The best results (in terms of Sharpe) is reported, whenever a population reaches new highs. We accept the fact that the Sharpe ratio will be optimistically biased \/ inflated. As the trials grow, the Deflated Sharpe Ratio decreases until a new &#8220;best result&#8221; is found.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1100\" height=\"674\" data-src=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/mesominer-ga-opt-1-1100x674.png\" alt=\"Rhino Strategy\" class=\"wp-image-234734 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/mesominer-ga-opt-1-1100x674.png 1100w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/mesominer-ga-opt-1-700x429.png 700w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/mesominer-ga-opt-1-300x184.png 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/mesominer-ga-opt-1-768x471.png 768w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/mesominer-ga-opt-1-1536x941.png 1536w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/mesominer-ga-opt-1.png 1772w\" data-sizes=\"(max-width: 1100px) 100vw, 1100px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1100px; aspect-ratio: 1100\/674;\" \/><\/figure>\n\n\n\n<p>Source: MesoSim<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th>Runs<\/th><th>Best Run In Population<\/th><th>CAGR<\/th><th>MaxDD<\/th><th>Sharpe<\/th><th>DSR<\/th><th>DSR Probability<\/th><\/tr><\/thead><tbody><tr><td>50<\/td><td><a href=\"https:\/\/mesosim.io\/backtests\/780b6ad8-a554-451f-9c03-3d2ee03990b0\" target=\"_blank\" rel=\"noreferrer noopener\">780b6ad8-&#8230;<\/a><\/td><td>12.2%<\/td><td>-4.2%<\/td><td>2.17<\/td><td>1.09<\/td><td>97.9%<\/td><\/tr><tr><td>400<\/td><td><a href=\"https:\/\/mesosim.io\/backtests\/da8721df-196b-4eed-b723-8ef7a09eae28\" target=\"_blank\" rel=\"noreferrer noopener\">da8721df-&#8230;<\/a><\/td><td>10.1%<\/td><td>-5.2%<\/td><td>2.24<\/td><td>1.12<\/td><td>96.4%<\/td><\/tr><tr><td><strong>450<\/strong><\/td><td><a href=\"https:\/\/mesosim.io\/backtests\/7fb14ac4-40a9-4081-bba4-9a48d59cc37a\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>7fb14ac4-&#8230;<\/strong><\/a><\/td><td><strong>13.1%<\/strong><\/td><td><strong>-4.2%<\/strong><\/td><td><strong>2.31<\/strong><\/td><td><strong>1.15<\/strong><\/td><td><strong>98.8%<\/strong><\/td><\/tr><tr><td>750<\/td><td><a href=\"https:\/\/mesosim.io\/backtests\/bbb95eb2-c536-487c-9fe8-4405e57ff46e\" target=\"_blank\" rel=\"noreferrer noopener\">bbb95eb2-&#8230;<\/a><\/td><td>12.5%<\/td><td>-4.4%<\/td><td>2.46<\/td><td>0.93<\/td><td>97.1%<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-best-in-sample-results-by-dsr\">Best In-Sample results by DSR<\/h2>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1100\" height=\"620\" data-src=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-backtest-results-1100x620.jpg\" alt=\"\" class=\"wp-image-234754 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-backtest-results-1100x620.jpg 1100w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-backtest-results-700x394.jpg 700w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-backtest-results-300x169.jpg 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-backtest-results-768x433.jpg 768w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-backtest-results-1536x865.jpg 1536w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-backtest-results-2048x1154.jpg 2048w\" data-sizes=\"(max-width: 1100px) 100vw, 1100px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1100px; aspect-ratio: 1100\/620;\" \/><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<p>Source: MesoSim<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1100\" height=\"869\" data-src=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-tearsheet-1-1100x869.jpg\" alt=\"\" class=\"wp-image-234760 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-tearsheet-1-1100x869.jpg 1100w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-tearsheet-1-700x553.jpg 700w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-tearsheet-1-300x237.jpg 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-tearsheet-1-768x607.jpg 768w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-tearsheet-1-1536x1214.jpg 1536w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-tearsheet-1.jpg 1774w\" data-sizes=\"(max-width: 1100px) 100vw, 1100px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1100px; aspect-ratio: 1100\/869;\" \/><\/figure>\n\n\n\n<p>Source: MesoSim<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1100\" height=\"753\" data-src=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-tearsheet-2-1-1100x753.jpg\" alt=\"\" class=\"wp-image-234764 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-tearsheet-2-1-1100x753.jpg 1100w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-tearsheet-2-1-700x479.jpg 700w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-tearsheet-2-1-300x205.jpg 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-tearsheet-2-1-768x526.jpg 768w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-tearsheet-2-1-1536x1052.jpg 1536w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-tearsheet-2-1.jpg 1808w\" data-sizes=\"(max-width: 1100px) 100vw, 1100px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1100px; aspect-ratio: 1100\/753;\" \/><\/figure>\n\n\n\n<p>Source: MesoSim<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1100\" height=\"753\" data-src=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-tearsheet-2-1100x753.jpg\" alt=\"\" class=\"wp-image-234758 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-tearsheet-2-1100x753.jpg 1100w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-tearsheet-2-700x479.jpg 700w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-tearsheet-2-300x205.jpg 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-tearsheet-2-768x526.jpg 768w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-tearsheet-2-1536x1052.jpg 1536w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2025\/11\/genetic-rhino-25q4-is-tearsheet-2.jpg 1808w\" data-sizes=\"(max-width: 1100px) 100vw, 1100px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1100px; aspect-ratio: 1100\/753;\" \/><\/figure>\n\n\n\n<p>Source: MesoSim<\/p>\n\n\n\n<p>Besides monitoring the DSR we also track the DSR Probability and aims to pick runs where there is high confidence that the Sharpe is truly positive: cutoff at 95%. Considering the DSR and DSR Probability we pick the best run at the 450 runs mark and we validate this using the withheld, 2018 &#8211; 2022 period.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th>Period<\/th><th>Run<\/th><th>CAGR<\/th><th>MaxDD<\/th><th>Sharpe<\/th><\/tr><\/thead><tbody><tr><td>IS<\/td><td><a href=\"https:\/\/mesosim.io\/backtests\/7fb14ac4-40a9-4081-bba4-9a48d59cc37a\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>7fb14ac4-&#8230;<\/strong><\/a><\/td><td>13.1%<\/td><td>-4.2%<\/td><td><strong>2.31<\/strong><\/td><\/tr><tr><td>OOS<\/td><td><a href=\"https:\/\/mesosim.io\/backtests\/07763433-8bee-4154-9a00-f9b09961e964\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>07763433-&#8230;<\/strong><\/a><\/td><td>9.21%<\/td><td>-6.74%<\/td><td><strong>2.2<\/strong><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>The Out-of-Sample results confirm that the optimized trade performs well on unseen data, with a Sharpe ratio similar to the In-Sample period. Our expectation is that the trade will perform well in the near future, but re-optimization will be needed as market conditions change.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"optimized-trade-plan\">Optimized Trade Plan<\/h3>\n\n\n\n<p>You can study the Strategy Definition in the&nbsp;<a href=\"https:\/\/mesosim.io\/backtests\/ce675a51-d8ca-49a8-b9fd-e723505d2bb0\" target=\"_blank\" rel=\"noreferrer noopener\">MesoSim Portal<\/a>&nbsp;or you can use&nbsp;<a href=\"https:\/\/chatgpt.com\/share\/691a1d92-355c-800d-95ae-85e2f70a2982\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>MesoSim AI Agent<\/strong><\/a>.<br>Here is a brief summary of the optimized trade plan:<\/p>\n\n\n\n<p><strong>Underlying<\/strong>: SPX.<\/p>\n\n\n\n<p><strong>Expirations<\/strong>:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>exp1 (front): target \u2248 99 DTE for the entire BWB and the short call.<\/li>\n\n\n\n<li>exp2 (back): target \u2248 110 DTE (Min=110), used for the long call hedge.<\/li>\n<\/ul>\n\n\n\n<p><strong>Structure<\/strong>:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>BWB<\/strong>:\n<ul class=\"wp-block-list\">\n<li>short_put (exp1): Qty \u22122, \u0394\u224822.<\/li>\n\n\n\n<li>lower_long_put (exp1): Qty +1, \u0394\u22486. Max(\u0394) dynamically capped by per-contract delta of the short put.<\/li>\n\n\n\n<li>upper_long_put (exp1): Qty +1, \u0394\u224846, with a dynamic Min(\u0394) tied to the short put\u2019s per-contract delta; Max=50.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Call diagonal<\/strong>:\n<ul class=\"wp-block-list\">\n<li>short_call (exp1): Qty \u22121, \u0394\u224824, Max(\u0394)=50.<\/li>\n\n\n\n<li>long_call (exp2): Qty +1, \u0394 set to abs(pos_delta) at selection time to neutralize with a back-month long leg<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<p><strong>Entry<\/strong>: Daily, 30 min after open. Up to 12 simultaneous positions, with 6-day entry staggering \u2192 campaign deployment to smooth path risk. No gating conditions.<\/p>\n\n\n\n<p><strong>Adjustments<\/strong>: Daily, 60 min after close. Delta guardrails with surgical rolls:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>If&nbsp;<code>pos_delta &gt; 5<\/code>: move upper_long_put (front-month wing) to a new strike as such that the position delta becomes 0.<\/li>\n\n\n\n<li>If&nbsp;<code>pos_delta &lt; \u22125<\/code>: move short_call similarly, re-setting position delta to 0 by shifting the short call\u2019s strike.<\/li>\n<\/ul>\n\n\n\n<p><strong>Exit<\/strong>: Daily, 30 min before close. Max Days in Trade: 53. Hard exit conditions (any hit \u2192 close):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Downside breach: spot &lt; short-put strike<\/li>\n\n\n\n<li>Upside breach: spot &gt; back-month long-call strike<\/li>\n\n\n\n<li>Greeks:&nbsp;<code>abs(pos_delta) &gt; 16<\/code><\/li>\n\n\n\n<li>No explicit PT\/SL; exits are path-driven by barriers + delta.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"further-work\">Further work<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Calendarized structures can &#8220;sink&#8221; when volatility becomes unfavorable for the position. With MesoSim-v3.0 such cases can now be detected and acted upon by using the&nbsp;<a href=\"https:\/\/docs.mesosim.io\/about-the-simulator\/options-valuation\" target=\"_blank\" rel=\"noreferrer noopener\">Options Valuation Model<\/a>.<\/li>\n\n\n\n<li>Margin to Equity (MtE) and Equity to Vega ratios can be incorporated to the original Rhino plan to better match Bruno&#8217;s style of trading. The required tools are already provided by MesoSim.<\/li>\n\n\n\n<li>Slippage modeling can be enabled to better capture the real-life trading costs. Our experience is that the genetic variant can be filled using two orders, each slipping by 5 cents from mid-price (SPX).<\/li>\n<\/ul>\n\n\n\n<p>Do you have other ideas or suggestions?<br>Please leave a comment below!<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-conclusion\">Conclusion<\/h2>\n\n\n\n<p>Rhino is a family of related broken\u2011wing butterfly income trades that have evolved over nearly a decade. The latest rules of the original trade (from 2023) still hold up in today&#8217;s market, providing reasonable performance.<\/p>\n\n\n\n<p>We hope our&nbsp;<a href=\"https:\/\/blog.deltaray.io\/rhino-options-strategy\/#geneticrhino-25q4\">GeneticRhino-SPX-25Q4<\/a>&nbsp;implementation will hold up and provide good performance for the next few months. We are sure, however, that re-optimization is an integral part of trade development process and the trade can benefit from it as market conditions are changing.<\/p>\n\n\n\n<p>Both trade plans are readily available for live and paper trading in MesoLive and can be further customized in MesoSim.<\/p>\n\n\n\n<p>Some of the historical variants shown later in this article have not performed well in the recent markets. That\u2019s not a criticism of their original designers; it just illustrates what Bruno Voisin keeps repeating:<\/p>\n\n\n\n<p>Adapt or die.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-acknowledgements\">Acknowledgements<\/h2>\n\n\n\n<p>We would like to thank Bruno Voisin for his pioneering work on the Rhino trade and for making much of his material publicly available. His support throughout the development of this article has been invaluable.<\/p>\n\n\n\n<p>We also thank Claudio Valerio and Rafael Munhoz for their feedback on the drafts of this article<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The Rhino Options Strategy is a conservative, broken\u2011wing butterfly income trade with an upside hedge. <\/p>\n","protected":false},"author":186,"featured_media":169745,"comment_status":"open","ping_status":"closed","sticky":true,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[339,338,341,9563],"tags":[851,18362,20867,806,20866,5545],"contributors-categories":[20614],"class_list":{"0":"post-234681","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-data-science","8":"category-ibkr-quant-news","9":"category-quant-development","10":"category-options-quant","11":"tag-algo-trading","12":"tag-broken-wing-butterfly","13":"tag-cagr-max-drawdown","14":"tag-data-science","15":"tag-rhino-options-strategy","16":"tag-sharpe-ratio","17":"contributors-categories-deltaray"},"pp_statuses_selecting_workflow":false,"pp_workflow_action":"current","pp_status_selection":"publish","acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.9 (Yoast SEO v27.3) - 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