vendor: 28,347 bytes, lines 1-9
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this.fetch({...a,meta:{fetchMore:{direction:"backward"}}})}createResult(a,n){const{state:r}=a,o=super.createResult(a,n),{isFetching:c,isRefetching:d,isError:h,isRefetchError:m}=o,p=r.fetchMeta?.fetchMore?.direction,g=h&&p==="forward",v=c&&p==="forward",x=h&&p==="backward",w=c&&p==="backward";return{...o,fetchNextPage:this.fetchNextPage,fetchPreviousPage:this.fetchPreviousPage,hasNextPage:rj(n,r.data),hasPreviousPage:ij(n,r.data),isFetchNextPageError:g,isFetchingNextPage:v,isFetchPreviousPageError:x,isFetchingPreviousPage:w,isRefetchError:m&&!g&&!x,isRefetching:d&&!v&&!w}}},oj=class extends Ov{#t;#e;#a;#s;constructor(a){super(),this.#t=a.client,this.mutationId=a.mutationId,this.#a=a.mutationCache,this.#e=[],this.state=a.state||Pv(),this.setOptions(a.options),this.scheduleGc()}setOptions(a){this.options=a,this.updateGcTime(this.options.gcTime)}get meta(){return this.options.meta}addObserver(a){this.#e.includes(a)||(this.#e.push(a),this.clearGcTimeout(),this.#a.notify({type:"observerAdded",mutation:this,observer:a}))}removeObserver(a){this.#e=this.#e.filter(n=>n!==a),this.scheduleGc(),this.#a.notify({type:"observerRemoved",mutation:this,observer:a})}optionalRemove(){this.#e.length||(this.state.status==="pending"?this.scheduleGc():this.#a.remove(this))}continue(){return this.#s?.continue()??this.execute(this.state.variables)}async execute(a){const n=()=>{this.#n({type:"continue"})},r={client:this.#t,meta:this.options.meta,mutationKey:this.options.mutationKey};this.#s=_v({fn:()=>this.options.mutationFn?this.options.mutationFn(a,r):Promise.reject(new Error("No mutationFn found")),onFail:(d,h)=>{this.#n({type:"failed",failureCount:d,error:h})},onPause:()=>{this.#n({type:"pause"})},onContinue:n,retry:this.options.retry??0,retryDelay:this.options.retryDelay,networkMode:this.options.networkMode,canRun:()=>this.#a.canRun(this)});const 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vendor: 5,989 bytes, line 48
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vendor: 7,784 bytes, line 49
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Essential reading for family offices and professional allocators."}),l.jsxs("div",{"data-loc":"client/src/pages/Research.tsx:214",className:"flex flex-wrap gap-2 mb-4",children:[l.jsx(Lt,{"data-loc":"client/src/pages/Research.tsx:215",variant:"outline",className:"bg-background/50",children:"Regime Adaptation"}),l.jsx(Lt,{"data-loc":"client/src/pages/Research.tsx:216",variant:"outline",className:"bg-background/50",children:"Limits to Arbitrage"}),l.jsx(Lt,{"data-loc":"client/src/pages/Research.tsx:217",variant:"outline",className:"bg-background/50",children:"Risk Parity"})]})]}),l.jsx("a",{"data-loc":"client/src/pages/Research.tsx:220",href:"/AnInstitutionalFrameworkforTacticalAssetAllocation.pdf",target:"_blank",rel:"noopener noreferrer",className:"shrink-0",children:l.jsxs(Re,{"data-loc":"client/src/pages/Research.tsx:226",variant:"outline",className:"border-secondary/50 text-secondary hover:bg-secondary/10 font-bold gap-2",children:[l.jsx(Vs,{"data-loc":"client/src/pages/Research.tsx:227",className:"w-4 h-4"})," View Paper"]})})]})})]}),l.jsxs("div",{"data-loc":"client/src/pages/Research.tsx:235",className:"grid grid-cols-1 md:grid-cols-2 gap-6",children:[l.jsx(Ne,{"data-loc":"client/src/pages/Research.tsx:237",className:"border-border shadow-sm hover:shadow-md transition-shadow",children:l.jsxs(Ce,{"data-loc":"client/src/pages/Research.tsx:238",className:"p-6 flex flex-col h-full",children:[l.jsx("h3",{"data-loc":"client/src/pages/Research.tsx:239",className:"text-lg font-bold mb-2 text-foreground",children:"Predictive Superiority of the Second Derivative"}),l.jsx("p",{"data-loc":"client/src/pages/Research.tsx:240",className:"text-sm text-muted-foreground mb-4 flex-grow",children:'Original research on "growth of growth" in FCF and its predictive power for stock selection.'}),l.jsxs("a",{"data-loc":"client/src/pages/Research.tsx:243",href:"/Predictive_Superiority_Second_Derivative.pdf",target:"_blank",rel:"noopener noreferrer",className:"mt-auto inline-flex items-center text-sm font-medium text-secondary hover:underline",children:[l.jsx(ka,{"data-loc":"client/src/pages/Research.tsx:249",className:"w-4 h-4 mr-2"})," View PDF"]})]})}),l.jsx(Ne,{"data-loc":"client/src/pages/Research.tsx:254",className:"border-border shadow-sm hover:shadow-md transition-shadow",children:l.jsxs(Ce,{"data-loc":"client/src/pages/Research.tsx:255",className:"p-6 flex flex-col h-full",children:[l.jsx("h3",{"data-loc":"client/src/pages/Research.tsx:256",className:"text-lg font-bold mb-2 text-foreground",children:"Twenty Years of Quantitative Innovation"}),l.jsx("p",{"data-loc":"client/src/pages/Research.tsx:257",className:"text-sm text-muted-foreground mb-4 flex-grow",children:"A historical overview of the strategy's evolution from 2004 to present day."}),l.jsxs("a",{"data-loc":"client/src/pages/Research.tsx:260",href:"/Twenty_Years_Quantitative_Innovation.pdf",target:"_blank",rel:"noopener noreferrer",className:"mt-auto inline-flex items-center text-sm font-medium text-secondary hover:underline",children:[l.jsx(ka,{"data-loc":"client/src/pages/Research.tsx:266",className:"w-4 h-4 mr-2"})," View PDF"]})]})})]}),l.jsx(Ne,{"data-loc":"client/src/pages/Research.tsx:273",className:"border-border shadow-sm",children:l.jsxs(Ce,{"data-loc":"client/src/pages/Research.tsx:274",className:"p-8 md:p-12 max-w-none",children:[l.jsx("h1",{"data-loc":"client/src/pages/Research.tsx:275",className:"text-3xl md:text-4xl font-bold text-foreground mb-6 leading-tight",children:"From Second Derivative Growth to All-Asset Momentum + Risk Parity: A Strategy for Superior Drawdown Management"}),l.jsxs("div",{"data-loc":"client/src/pages/Research.tsx:279",className:"flex flex-col sm:flex-row sm:items-center gap-2 sm:gap-8 text-sm text-muted-foreground mb-10 border-b border-border pb-6",children:[l.jsxs("div",{"data-loc":"client/src/pages/Research.tsx:280",children:[l.jsx("span",{"data-loc":"client/src/pages/Research.tsx:280",className:"font-semibold text-foreground",children:"Author:"})," Peter Lusk, Jr."]}),l.jsxs("div",{"data-loc":"client/src/pages/Research.tsx:281",children:[l.jsx("span",{"data-loc":"client/src/pages/Research.tsx:281",className:"font-semibold text-foreground",children:"Date:"})," December 4, 2025"]})]}),l.jsxs("div",{"data-loc":"client/src/pages/Research.tsx:284",className:"space-y-6 mb-12",children:[l.jsx("h3",{"data-loc":"client/src/pages/Research.tsx:285",className:"text-2xl font-bold text-foreground",children:"Abstract"}),l.jsx("p",{"data-loc":"client/src/pages/Research.tsx:286",className:"text-base leading-relaxed text-muted-foreground",children:`The Acanto Adaptive All Asset 8 (8A) strategy represents an innovative evolution beyond traditional "static" risk parity and age-related stock and bond allocations that can fail in rising interest rate environments or long-term equity downturns. While fixed allocation models (such as Ray Dalio's All Weather) suffered significant losses in 2022 due to the simultaneous decline of stocks and bonds, the 8A strategy's dynamic momentum filter successfully pivoted capital away from falling fixed income and into cash and commodities, preserving capital when it mattered most. This adaptability continues to drive outperformance in 2025, where a timely rotation into precious metals (Gold and Silver) has allowed the strategy to beat the NASDAQ year to date (2025) despite the tech-heavy index's gains for the year.`}),l.jsx("p",{"data-loc":"client/src/pages/Research.tsx:289",className:"text-base leading-relaxed text-muted-foreground",children:'This paper traces the full evolution of this philosophy, from early Free Cash Flow (FCF) stock selection models to the AI-driven multi-asset strategies developed with Prof. Hans von Mettenheim, and finally to the current 8A framework. By synthesizing momentum and risk parity across a universe of over 20 ETFs representing 8 distinct asset classes, we demonstrate how this approach solves the "Beta problem" inherent in equity-only strategies, delivering superior risk-adjusted returns and drawdown protection compared to traditional benchmarks [3] [4].'})]}),l.jsxs("div",{"data-loc":"client/src/pages/Research.tsx:294",className:"space-y-6 mb-12",children:[l.jsxs("h3",{"data-loc":"client/src/pages/Research.tsx:295",className:"text-2xl font-bold text-foreground",children:[l.jsx("span",{"data-loc":"client/src/pages/Research.tsx:295",className:"mr-2",children:"1."})," Introduction"]}),l.jsxs("p",{"data-loc":"client/src/pages/Research.tsx:296",className:"text-base leading-relaxed text-muted-foreground",children:['The central challenge in modern portfolio construction is the inherent trade-off between generating growth and managing risk. While numerous quantitative models have been developed to optimize stock selection, many fall short in protecting capital during systemic market downtur
336ns. Even sophisticated models, such as those based on the growth of free cash flow (FCF), can leave investors fully exposed to market beta. Static or fixed allocations can leave older clients heavily weighed in fixed income and subject to inflation and interest rate risk, while all investors tend to panic and sell at market bottoms and hesitate too long to "get back in". This systematic strategy tries to solve these problems by shifting the primary objective from ',l.jsx("em",{"data-loc":"client/src/pages/Research.tsx:297",className:"italic text-foreground",children:"beating an index"})," to ",l.jsx("em",{"data-loc":"client/src/pages/Research.tsx:297",className:"italic text-foreground",children:"capturing trends across liquid asset classes and avoiding significant drawdown"}),". As we often tell clients: ",l.jsx("em",{"data-loc":"client/src/pages/Research.tsx:297",className:"italic text-foreground",children:`"We will always be a month or two late getting out and a month or two late getting back in, but I don't want to have to tell a retiree or panicked investor to 'just ride it out' in a 50% bear market like 2000, 2008, or even 2022, where bond holders got punished more than anytime in the last 40 years."`})]}),l.jsxs("p",{"data-loc":"client/src/pages/Research.tsx:299",className:"text-base leading-relaxed text-muted-foreground",children:['We trace the evolution of this thinking, starting with the "Eco-Vest" FCF strategy (2004-2006), moving through the AI-driven "All Market +" and "Absolute DL" strategies developed with Prof. Hans von Mettenheim (2017-2021), and culminating in the current Adaptive All Asset 8 (8A) strategy. This latest iteration combines ',l.jsx("strong",{"data-loc":"client/src/pages/Research.tsx:300",className:"font-semibold text-foreground",children:"All Asset Momentum + Risk Parity"}),' to provide a robust, transparent solution for risk-averse investors. The full Acanto 8A Strategy Paper, as well as the historical "Predictive Superiority of the Second Derivative" and "Twenty Years of Quantitative Innovation" research papers, are listed above for viewing to provide complete context on this evolutionary journey.']})]}),l.jsxs("div",{"data-loc":"client/src/pages/Research.tsx:304",className:"space-y-6 mb-12",children:[l.jsxs("h3",{"data-loc":"client/src/pages/Research.tsx:305",className:"text-2xl font-bold text-foreground",children:[l.jsx("span",{"data-loc":"client/src/pages/Research.tsx:305",className:"mr-2",children:"2."})," The Evolution of the Strategy"]}),l.jsxs("div",{"data-loc":"client/src/pages/Research.tsx:307",className:"pl-4 border-l-2 border-border space-y-4 mt-6",children:[l.jsxs("h4",{"data-loc":"client/src/pages/Research.tsx:308",className:"text-xl font-bold text-foreground",children:[l.jsx("span",{"data-loc":"client/src/pages/Research.tsx:308",className:"mr-2",children:"2.1."})," Phase 1: The Predictive Power of FCF (2004-2006)"]}),l.jsxs("p",{"data-loc":"client/src/pages/Research.tsx:309",className:"text-base leading-relaxed text-muted-foreground",children:['Our journey began with the "Eco-Vest" strategy, which focused on the ',l.jsx("em",{"data-loc":"client/src/pages/Research.tsx:310",className:"italic text-foreground",children:"acceleration"})," of free cash flow growthâthe second derivative. Grounded in Aswath Damodaran's valuation principles [2], this approach successfully identified high-quality companies on a trajectory of outperformance. While effective at generating Alp
336ha, it remained an equity-only strategy, leaving it vulnerable to broad market declines (Beta risk)."]})]}),l.jsxs("div",{"data-loc":"client/src/pages/Research.tsx:314",className:"pl-4 border-l-2 border-border space-y-4 mt-6",children:[l.jsxs("h4",{"data-loc":"client/src/pages/Research.tsx:315",className:"text-xl font-bold text-foreground",children:[l.jsx("span",{"data-loc":"client/src/pages/Research.tsx:315",className:"mr-2",children:"2.2."})," Phase 2: AI and Multi-Asset Allocation (2017-2021)"]}),l.jsx("p",{"data-loc":"client/src/pages/Research.tsx:316",className:"text-base leading-relaxed text-muted-foreground",children:'Recognizing the need for drawdown protection, we co-founded Acanto with Prof. Hans von Mettenheim. Together, we developed the "All Market +" and "Absolute DL" strategies. These models utilized AI and machine learning to analyze market sentiment and volatility across four key asset classes: Equities, Bonds, Gold, and Cash.'}),l.jsx("p",{"data-loc":"client/src/pages/Research.tsx:319",className:"text-base leading-relaxed text-muted-foreground",children:'The "All Market +" strategy sought to outperform US equities with less volatility by dynamically allocating between these assets without leverage. The "Absolute DL" strategy employed Dynamic Leverage (up to 2x) to maximize returns while capping drawdowns. These strategies successfully navigated the volatile markets of 2017-2021, validating the power of dynamic asset allocation over static stock picking.'})]}),l.jsxs("div",{"data-loc":"client/src/pages/Research.tsx:324",className:"pl-4 border-l-2 border-border space-y-4 mt-6",children:[l.jsxs("h4",{"data-loc":"client/src/pages/Research.tsx:325",className:"text-xl font-bold text-foreground",children:[l.jsx("span",{"data-loc":"client/src/pages/Research.tsx:325",className:"mr-2",children:"2.3."})," Phase 3: The Adaptive All Asset 8 (8A) Strategy (2021-Present)"]}),l.jsx("p",{"data-loc":"client/src/pages/Research.tsx:326",className:"text-base leading-relaxed text-muted-foreground",children:'In 2021, we sought to create a more robust and transparent framework, moving away from "black box" AI algorithms. The result was the 8A strategy. It expands the universe to over 20 ETFs representing 8 distinct asset classes and replaces complex AI signals with academically validated principles of Momentum and Risk Parity. This shift has not only simplified the investment process but has also surpassed expectations in terms of performance and market timing, particularly during the challenging environment of 2022.'})]})]}),l.jsxs("div",{"data-loc":"client/src/pages/Research.tsx:332",className:"space-y-6 mb-12",children:[l.jsxs("h3",{"data-loc":"client/src/pages/Research.tsx:333",className:"text-2xl font-bold text-foreground",children:[l.jsx("span",{"data-loc":"client/src/pages/Research.tsx:333",className:"mr-2",children:"3."})," Methodology: The Acanto Adaptive All Asset 8 (8A) Strategy"]}),l.jsxs("p",{"data-loc":"client/src/pages/Research.tsx:334",className:"text-base leading-relaxed text-muted-foreground",children:['The 8A strategy is designed to solve the "Beta problem" inherent in equity-only models. It employs an asymmetric downside mechanism, seeking to ',l.jsx("em",{"data-loc":"client/src/pages/Research.tsx:335",className:"italic text-foreground",children:"avoid drawdown"})," by rotating out of falling assets entirely."]}),l.jsxs("div",{"data-loc":"client/src/pages/Research.tsx:338",className:"pl-4 border-l-2 border-border space-y-4 mt-6",children:[l.jsxs("h4",{"data-loc":"client/src/pages/Research.tsx:339",className:"text-xl font-bold text-foreground",children:[l.jsx("span",{"data-loc":"client/src/pages/Research.tsx:339",className:"mr-2",children:"3.1."})," Momentum and Risk Parity vs. Static Allocation"]}),l.jsxs("p",{"data-loc":"client/src/pages/Research.tsx:340",className:"text-base leading-relaxed text-muted-foreground",children:["The strategy relies on two pillars: ",l.jsx("strong",{"data-loc":"client/src/pages/Research.tsx:341",className:"font-semibold text-foreground",children:"Momentum"})," for asset selection and ",l.jsx("strong",{"data-loc":"client/src/pages/Research.tsx:341",className:"font-semibold text-foreground",children:"Risk Parity"})," for position sizing."]}),l.jsx("p",{"data-loc":"client/src/pages/Research.tsx:343",className:"text-base leading-relaxed text-muted-foreground",children:`Unlike "static" Risk Parity strategies (e.g., Ray Dalio's All Weather), which maintain fixed exposures to bonds and equities based on historical correlations, the 8A strategy is dynamic. Static models suffered significant losses in 2022 when rising interest rates caused both stocks and bonds to fall simultaneously. In contrast, the 8A strategy's momentum filter allowed it to exit falling bonds and pivot to commodities and cash, preserving capital [3]. This adaptability is the key to its superior performance.`})]}),l.jsxs("div",{"data-loc":"client/src/pages/Research.tsx:348",className:"pl-4 border-l-2 border-border space-y-4 mt
336-6",children:[l.jsxs("h4",{"data-loc":"client/src/pages/Research.tsx:349",className:"text-xl font-bold text-foreground",children:[l.jsx("span",{"data-loc":"client/src/pages/Research.tsx:349",className:"mr-2",children:"3.2."})," Strategy Construction"]}),l.jsxs("p",{"data-loc":"client/src/pages/Research.tsx:350",className:"text-base leading-relaxed text-muted-foreground",children:["The strategy operates on a universe of ",l.jsx("strong",{"data-loc":"client/src/pages/Research.tsx:351",className:"font-semibold text-foreground",children:"over 20 liquid ETFs"})," representing 8 major asset classes: Equities, Fixed Income, Real Estate (REITs), Commodities, Metals, Cash, Volatility, and Digital Assets (Bitcoin)."]}),l.jsx("p",{"data-loc":"client/src/pages/Research.tsx:353",className:"text-base leading-relaxed text-muted-foreground",children:"Each month, assets are ranked by relative strength using multiple performance windows. The top eight are selected, and a risk-parity framework sizes positions based on their recent volatility. This ensures that no single asset dominates the portfolio's risk profile, creating a truly diversified and resilient allocation."})]})]}),l.jsxs("div",{"data-loc":"client/src/pages/Research.tsx:359",className:"space-y-6 mb-12",children:[l.jsxs("h3",{"data-loc":"client/src/pages/Research.tsx:360",className:"text-2xl font-bold text-foreground",children:[l.jsx("span",{"data-loc":"client/src/pages/Research.tsx:360",className:"mr-2",children:"4."}),' Robustness and the "Breakthrough Insight"']}),l.jsxs("p",{"data-loc":"client/src/pages/Research.tsx:361",className:"text-base leading-relaxed text-muted-foreground",children:["A critical question in the strategy's development was: ",l.jsx("em",{"data-loc":"client/src/pages/Research.tsx:362",className:"italic text-foreground",children:'"What performs better: Growth, Value, or Bonds?"'})," The breakthrough insight came from reframing the question: ",l.jsx("em",{"data-loc":"client/src/pages/Research.tsx:362",className:"italic text-foreground",children:'"What about 2 out of 3? Or 3 out of 5? Or 5 out of 10?"'})]}),l.jsxs("p",{"data-loc":"client/src/pages/Research.tsx:364",className:"text-base leading-relaxed text-muted-foreground",children:["Extensive sensitivity analysis (spanning 1993-2022) revealed a remarkably consistent pattern: selecting the top ",l.jsx("em",{"data-loc":"client/src/pages/Research.tsx:365",className:"italic text-foreground",children:"N"})," performing assets from a universe of ",l.jsx("em",{"data-loc":"client/src/pages/Research.tsx:365",className:"italic text-foreground",children:"M"})," assets, based on mid-term momentum trends, consistently outperformed both equal-weighted portfolios of all assets and traditional balanced benchmarks."]}),l.jsx("p",{"data-loc":"client/src/pages/Research.tsx:367",className:"text-base leading-relaxed text-muted-foreground",children:"This robustness held true across various permutations of asset counts and trend lookback periods (e.g., 3, 6, 9, or 12 months). As detailed in our internal sensitivity studies (pages 13-19), whether the portfolio selected the top 3 of 5 assets or the top 5 of 8, the combination of momentum selection and risk parity weighting delivered superior risk-adjusted returns. This finding confirmed what we believe is the strategy's edge is not a result of curve-fitting a specific set of parameters, but rather a fundamental property of momentum in multi-asset universes."})]}),l.jsxs("div",{"data-loc":"client/src/pages/Research.tsx:372",className:"space-y-6 mb-12",children:[l.jsxs("h3",{"data-loc":"client/src/pages/Research.tsx:373",className:"text-2xl font-bold text-foreground",children:[l.jsx("span",{"data-loc":"client/src/pages/Research.tsx:373",className:"mr-2",children:"5."})," Data and Performance Analysis"]}),l.jsxs("div",{"data-loc":"client/src/pages/Research.tsx:375",className:"pl-4 border-l-2 border-border space-y-4 mt-6",children:[l.jsxs("h4",{"data-loc":"client/src/pages/Research.tsx:376",className:"text-xl font-bold text-foreground",children:[l.jsx("span",{"data-loc":"client/src/pages/Research.tsx:376",className:"mr-2",children:"5.
3361."})," Performance Results"]}),l.jsxs("p",{"data-loc":"client/src/pages/Research.tsx:377",className:"text-base leading-relaxed text-muted-foreground",children:["The Acanto 8A strategy demonstrates compelling performance, achieving a Compound Annual Growth Rate (CAGR) of ",l.jsx("strong",{"data-loc":"client/src/pages/Research.tsx:378",className:"font-semibold text-foreground",children:"12.08%"}),". This outpaces the S&P 500 ETF (10.97%) with significantly lower volatility (10.57% vs. 15.78%), resulting in a superior Sharpe Ratio (1.01) and Sortino Ratio (1.87)."]}),l.jsxs("figure",{"data-loc":"client/src/pages/Research.tsx:381",className:"my-10",children:[l.jsx("img",{"data-loc":"client/src/pages/Research.tsx:382",src:"/images/figure1_performance.png",alt:"Performance Summary and Portfolio Growth",className:"w-full rounded-lg border border-border shadow-sm"}),l.jsx("figcaption",{"data-loc":"client/src/pages/Research.tsx:387",className:"mt-3 text-sm text-center text-muted-foreground italic",children:"Figure 1: Performance Summary and Portfolio Growth (2008-2025)."})]})]}),l.jsxs("div",{"data-loc":"client/src/pages/Research.tsx:393",className:"pl-4 border-l-2 border-border space-y-4 mt-6",children:[l.jsxs("h4",{"data-loc":"client/src/pages/Research.tsx:394",className:"text-xl font-bold text-foreground",children:[l.jsx("span",{"data-loc":"client/src/pages/Research.tsx:394",className:"mr-2",children:"5.2."})," Drawdown Analysis"]}),l.jsxs("p",{"data-loc":"client/src/pages/Research.tsx:395",className:"text-base leading-relaxed text-muted-foreground",children:["The strategy's maximum drawdown was a mere ",l.jsx("strong",{"data-loc":"client/src/pages/Research.tsx:396",className:"font-semibold text-foreground",children:"-9.59%"}),", compared to -48.23% for the S&P 500. This confirms the efficacy of the dynamic momentum + risk parity approach in mitigating downside risk."]}),l.jsxs("figure",{"data-loc":"client/src/pages/Research.tsx:399",className:"my-10",children:[l.jsx("img",{"data-loc":"client/src/pages/Research.tsx:400",src:"/images/figure2_drawdown.png",alt:"Drawdown Comparison Chart",className:"w-full rounded-lg border border-border shadow-sm"}),l.jsx("figcaption",{"data-loc":"client/src/pages/Research.tsx:405",className:"mt-3 text-sm text-center text-muted-foreground italic",children:"Figure 2: Drawdown Comparison (2008-2025)."})]})]}),l.jsxs("div",{"data-loc":"client/src/pages/Research.tsx:411",className:"pl-4 border-l-2 border-border space-y-4 mt-6",children:[l.jsxs("h4",{"data-loc":"client/src/pages/Research.tsx:412",className:"text-xl font-bold text-foreground",children:[l.jsx("span",{"data-loc":"client/src/pages/Research.tsx:412",className:"mr-2",children:"5.3."})," Asset Allocation Timeline"]}),l.jsx("p",{"data-loc":"client/src/pages/Research.tsx:413",className:"text-base leading-relaxed text-muted-foreground",children:"The timeline below illustrates the strategy's adaptive nature. For instance, recent outperformance against the NASDAQ has been driven by timely exposures to metals (Gold/Silver) and other non-equity assets, highlighting the benefits of a broad, multi-asset universe."}),l.jsxs("figure",{"data-loc":"client/src/pages/Research.tsx:417",className:"my-10",children:[l.jsx("img",{"data-loc":"client/src/pages/Research.tsx:418",src:"/images/figure3_allocation.png",alt:"Asset Allocation Timeline",className:"w-full rounded-lg border border-border shadow-sm"}),l.jsx("figcaption",{"data-loc":"client/src/pages/Research.tsx:423",className:"mt-3 text-sm text-center text-muted-foreground italic",children:"Figure 3: Dynamic Asset Allocation (2008-2025)."})]})]})]}),l.jsxs("div",{"data-loc":"client/src/pages/Research.tsx:430",className:"space-y-6 mb-12",children:[l.jsxs("h3",{"data-loc":"client/src/pages/Research.tsx:431",className:"text-2xl font-bold text-foreground",children:[l.jsx("span",{"data-loc":"client/src/pages/Research.tsx:431",className:"mr-2",children:"6."})," Conclusion"]}),l.jsx("p",{"data-loc":"client/src/pages/Research.tsx:432",className:"text-base leading-relaxed text-muted-foreground",children:"The Acanto Adaptive All Asset 8 strategy represents the culmination of two decades of research and innovation. By evolving from single-asset stock selection to a robust, multi-asset framework, we have created a strategy that effectively solves the drawdown problem. The synthesis of momentum and risk parity allows for superior risk-adjusted returns and capital preservation, offering a compelling alternative to traditional equity and static balanced portfolios."})]}),l.jsxs("div",{"data-loc":"client/src/pages/Research.tsx:437",className:"space-y-6 pt-8 border-t border-border",children:[l.jsx("h3",{"data-loc":"client/src/pages/Research.tsx:438",className:"text-xl font-bold text-foreground",children:"References"}),l.jsxs("ol",{"data-loc":"client/src/pages/Research.tsx:439",className:"list-decimal pl-5 space-y-3 text-sm text-muted-foreground",children:[l.jsxs("li",{"data-loc":"client/src/pages/Research.tsx:440",children:["Moskowitz, T. J., & Daniel, K. D. (1999). Momentum in Asset Returns. ",l.jsx("em",{"data-loc":"client/src/pages/Research.tsx:440",className:"italic",children:"The Journal of Finance"}),"."]}),l.jsxs("li",{"data-loc":"client/src/pages/Research.tsx:441",children:["Damodaran, A. (2012). ",l.jsx("em",{"data-loc":"client/src/pages/Research.tsx:441",className:"italic",children:"Investment Valuation: Tools and Techniques for Determining the Value of Any Asset"}),". Wiley Finance."]}),l.jsxs("li",{"data-loc":"client/src/pages/Research.tsx:442",children:["Clare, A., Seaton, J., Smith, P. N., & Thomas, S. (2016). The Trend is Our Friend: Risk Parity, Momentum and Trend Following in Global Asset Allocation. ",l.jsx("em",{"data-loc":"client/src/pages/Research.tsx:442",className:"italic",children:"Journal of Behavioral and Experimental Finance"}),"."]}),l.jsxs("li",{"data-loc":"client/src/pages/Research.tsx:443",children:["Lusk, P. (2025). ",l.jsx("em",{"data-loc":"client/src/pages/Research.tsx:443",className:"italic",children:"Twenty Years of Quantitative Innovation: The Evolution of Lusk Investment Strategies"}),". Acanto LLC Internal Research."]})]})]})]})})]}),r&&l.jsx(O5,{"data-loc":"client/src/pages/Research.tsx:452",open:a,onOpenChange:n,paperTitle:r.title,paperUrl:r.url,source:r.source})]})}function M5(){const{isAccepted:a}=Qc(),[n,r]=b.useState(!1),[o,c]=b.useState(null);return l.jsx(ja,{"data-loc":"client/src/pages/Strategy.tsx:17",children:l.jsx("div",{"data-loc":"client/src/pages/Strategy.tsx:18",className:"max-w-5xl mx-auto
336space-y-8",children:a?l.jsxs(l.Fragment,{children:[l.jsxs("div",{"data-loc":"client/src/pages/Strategy.tsx:25",className:"text-center space-y-2",children:[l.jsx("h1",{"data-loc":"client/src/pages/Strategy.tsx:26",className:"text-4xl font-heading font-bold text-foreground",children:"The Acanto 8A Strategy"}),l.jsx("p",{"data-loc":"client/src/pages/Strategy.tsx:29",className:"text-xl text-muted-foreground max-w-3xl mx-auto text-center",children:"A tactical asset allocation framework designed to solve for reduced drawdown while capturing growth through multi-asset momentum and risk parity."})]}),l.jsxs("section",{"data-loc":"client/src/pages/Strategy.tsx:35",className:"space-y-4",children:[l.jsxs("div",{"data-loc":"client/src/pages/Strategy.tsx:36",className:"flex items-start gap-4 pt-0",children:[l.jsx("div",{"data-loc":"client/src/pages/Strategy.tsx:37",className:"h-24 w-1 bg-secondary rounded-full shrink-0 mt-1"}),l.jsxs("h2",{"data-loc":"client/src/pages/Strategy.tsx:38",className:"text-3xl font-heading font-bold leading-tight",children:["Acantoâs All Asset Adaptive 8:Â Â Momentum + Risk Parity",l.jsx("span",{"data-loc":"client/src/pages/Strategy.tsx:40",className:"text-xl text-foreground/80 mt-2 block font-normal",children:"A Strategy for Superior Drawdown Management"})]})]}),l.jsx("div",{"data-loc":"client/src/pages/Strategy.tsx:44",className:"prose prose-lg dark:prose-invert max-w-none text-muted-foreground",children:l.jsxs("p",{"data-loc":"client/src/pages/Strategy.tsx:45",children:["The central challenge in modern portfolio construction is balancing growth and risk management. Traditional approachesâthe 60/40 portfolio, target date funds, and risk parity strategiesârely on stable correlations between asset classes. The 2022 market environment exposed their fundamental flaw: ",l.jsx("strong",{"data-loc":"client/src/pages/Strategy.tsx:46",children:"when correlations break down and multiple asset classes decline simultaneously, static allocation strategies may offer less than desired drawdown protection."})]})}),l.jsxs("div",{"data-loc":"client/src/pages/Strategy.tsx:51",className:"space-y-2",children:[l.jsxs("div",{"data-loc":"client/src/pages/Strategy.tsx:52",className:"rounded-xl overflow-hidden border border-border shadow-lg bg-white cursor-zoom-in group relative",onClick:()=>c("https://files.manuscdn.com/user_upload_by_module/session_file/310419663030585508/JjkMeXbRapTPwTFD.png"),children:[l.jsx("div",{"data-loc":"client/src/pages/Strategy.tsx:56",className:"absolute inset-0 bg-black/0 group-hover:bg-black/10 transition-colors flex items-center justify-center",children:l.jsx(tv,{"data-loc":"client/src/pages/Strategy.tsx:57",className:"w-12 h-12 text-white opacity-0 group-hover:opacity-100 transition-opacity drop-shadow-lg"})}),l.jsx("img",{"data-loc":"client/src/pages/Strategy.tsx:59",src:"https://files.manuscdn.com/user_upload_by_module/session_file/310419663030585508/JjkMeXbRapTPwTFD.png",alt:"17 Years of Dynamic Rotation Across 8 Asset Classes",className:"w-full h-auto"})]}),l.jsx("p",{"data-loc":"client/src/pages/Strategy.tsx:65",className:"text-[10px] text-muted-foreground/60 text-center italic",children:"Performance shown is hypothetical, gross of fees, and for educational purposes only. Past performance is not indicative of future results."})]}),l.jsxs("div",{"data-loc":"client/src/pages/Strategy.tsx:71",className:"space-y-2",children:[l.jsxs("div",{"data-loc":"client/src/pages/Strategy.tsx:72",className:"rounded-xl overflow-hidden border border-border shadow-sm cursor-zoom-in group relative",onClick:()=>c("https://files.manuscdn.com/user_upload_by_module/session_file/310419663030585508/RbzDTlVzfBzQqjtx.png"),children:[l.jsx("div",{"data-loc":"client/src/pages/Strategy.tsx:76",className:"absolute inset-0 bg-black/0 group-hover:bg-black/10 transition-colors flex items-center justify-center",children:l.jsx(tv,{"data-loc":"client/src/pages/Strategy.tsx:77",className:"w-12 h-12 text-white opacity-0 group-hover:opacity-100 transition-opacity drop-shadow-lg"})}),l.jsx("img",{"data-loc":"client/src/pages/Strategy.tsx:79",src:"https://files.manuscdn.com/user_upload_by_module/session_file/310419663030585508/RbzDTlVzfBzQqjtx.png",alt:"Portfolio Growth Chart: Acanto All Asset Allocation 8 Adaptive vs Benchmarks",className:"w-full h-auto"})]}),l.jsx("p",{"data-loc":"client/src/pages/Strategy.tsx:85",className:"text-[10px] text-muted-foreground
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Universe Selection"})]}),l.jsx(Ce,{"data-loc":"client/src/pages/Strategy.tsx:222",children:l.jsxs("p",{"data-loc":"client/src/pages/Strategy.tsx:223",className:"text-sm text-muted-foreground",children:["The strategy monitors a diverse universe of ",l.jsx("strong",{"data-loc":"client/src/pages/Strategy.tsx:224",children:"more than 20 ETFs representing 8 classes"})," including Global and Domestic Equities, Fixed Income, REITs, Commodities, Metals, and Digital Assets (Bitcoin), represented by liquid ETFs."]})})]}),l.jsxs(Ne,{"data-loc":"client/src/pages/Strategy.tsx:229",className:"border-border shadow-sm",children:[l.jsxs(Ve,{"data-loc":"client/src/pages/Strategy.tsx:230",children:[l.jsx(wc,{"data-loc":"client/src/pages/Strategy.tsx:231",className:"w-10 h-10 text-primary mb-2"}),l.jsx(Qe,{"data-loc":"client/src/pages/Strategy.tsx:232",className:"text-lg font-bold",children:"2. Momentum Ranking"})]}),l.jsx(Ce,{"data-loc":"client/src/pages/Strategy.tsx:234",children:l.jsxs("p",{"data-loc":"client/src/pages/Strategy.tsx:235",className:"text-sm text-muted-foreground",children:["Each month, assets are ranked based on a blend of 3-6 month trend metrics. The system identifies the ",l.jsx("strong",{"data-loc":"client/src/pages/Strategy.tsx:236",children:"top 8 performing assets"})," that are showing the strongest relative strength."]})})]}),l.jsxs(Ne,{"data-loc":"client/src/pages/Strategy.tsx:241",className:"border-border shadow-sm",children:[l.jsxs(Ve,{"data-loc":"client/src/pages/Strategy.tsx:242",children:[l.jsx(bc,{"data-loc":"client/src/pages/Strategy.tsx:243",className:"w-10 h-10 text-primary mb-2"}),l.jsx(Qe,{"data-loc":"client/src/pages/Strategy.tsx:244",className:"text-lg font-bold",children:"3. Risk Parity Sizing"})]}),l.jsx(Ce,{"data-loc":"client/src/pages/Strategy.tsx:246",children:l.jsxs("p",{"data-loc":"client/src/pages/Strategy.tsx:247",className:"text-sm text-muted-foreground",children:["Selected assets are not equal-weighted. Instead, positions are sized based on ",l.jsx("strong",{"data-loc":"client/src/pages/Strategy.tsx:248",children:"inverse volatility (Risk Parity)"}),". Less volatile assets get larger allocations, while highly volatile assets get smaller ones, balancing risk across the portfolio."]})})]})]})]}),l.jsxs("section",{"data-loc":"client/src/pages/Strategy.tsx:258",className:"space-y-6",children:[l.jsxs("div",{"data-loc":"client/src/pages/Strategy.tsx:259",className:"flex items-center gap-3",children:[l.jsx("div",{"data-loc":"client/src/pages/Strategy.tsx:260",className:"h-8 w-1 bg-secondary rounded-full"}),l.jsx("h2",{"data-loc":"client/src/pages/Strategy.tsx:261",className:"text-3xl font-heading font-bold",children:"Why It Works"})]}),l.jsxs("div",{"data-loc":"client/src/pages/Strategy.tsx:264",className:"grid md:grid-cols-2 gap-8",children:[l.jsxs("div",{"data-loc":"client/src/pages/Strategy.tsx:265",className:"space-y-4",children:[l.jsx("h3",{"data-loc":"client/src/pages/Strategy.tsx:266",className:"text-xl font-bold text-foreground",children:"Adaptive Nature"}),l.jsxs("p",{"data-loc":"client/src/pages/Strategy.tsx:267",className:"text-muted-foreground leading-relaxed",children:["Traditional portfolios (like 60/40) are static. They hold stocks even when stocks are crashing. The Acanto 8A strategy is ",l.jsx("strong",{"data-loc":"client/src/pages/Strategy.tsx:268",children:"adaptive"}),'. It has no mandate to hold any specific asset class. If equities are falling, it rotates into Bonds, Cash, or Commodities. This ability to "go where the strength is" allows it to avoid large drawdowns.']})]}),l.jsxs("div",{"data-loc":"client/src/pages/Strategy.tsx:272",className:"space-y-4",children:[l.jsx("h3",{"data-loc":"client/src/pages/Strategy.tsx:273",className:"text-xl font-bold text-foreground",children:"True Diversification"}),l.jsxs("p",{"data-loc":"client/src/pages/Strategy.tsx:274",className:"text-muted-foreground leading-relaxed",children:['Most "diversified" portfolios are still highly correlated to the stock market. By including non-correlated assets like ',l.jsx("strong",{"data-loc":"client/src/pages/Strategy.tsx:275",children:"Commodities, Precious Metals, REITs, US Equities, Non-US Equities, Digital Assets, Corporate & Gov Bonds, and Cash"}),", the 8A strategy achieves a correlation of just ",l.jsx("strong",{"data-loc":"client/src/pages/Strategy.tsx:275",children:"0.52"})," to the S&P 500. This means it can generate returns even when the stock market is flat or down."]})]}),l.jsxs("div",{"data-loc":"client/src/pages/Strategy.tsx:279",className:"space-y-4",children:[l.jsx("h3",{"data-loc":"client/src/pages/Strategy.tsx:280",className:"text-xl font-bold text-foreground",children:"Drawdown Math"}),l.jsxs("p",{"data-loc":"client/src/pages/Strategy.tsx:281",className:"text-muted-foreground leading-relaxed",children:["Avoiding losses is more important than chasing gains. A 50% loss requires a 100% gain just to get back to even. By limiting maximum drawdown to ",l.jsx("strong",{"data-loc":"client/src/pages/Strategy.tsx:282",children:"-9.59%"})," (vs -48% for SPY), the strategy preserves the capital base, allowing the power of compounding to work more effectively over time."]})]}),l.jsxs("div",{"data-loc":"client/src/pages/Strategy.tsx:286",className:"space-y-4",children:[l.jsx("h3",{"data-loc":"client/src/pages/Strategy.tsx:287",className:"text-xl font-bold text-foreground",children:"Risk Parity Stability"}),l.jsxs("p",{"data-loc":"client/src/pages/Strategy.tsx:288",className:"text-muted-foreground leading-relaxed",children:["Equal-weighting assets ignores risk. A 10% allocation to Bitcoin is far riskier than a 10% allocation to Bonds. Risk Parity equal
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This worked for decades until 2022, when both fell together. Ray Dalio's All Weather portfolio, with its 55% fixed bond allocation, had no mechanism to exit during the historic bond bear market. It lost 26.5% with a maximum drawdown of 34.61%."})]}),l.jsxs("div",{"data-loc":"client/src/pages/Strategy.tsx:304",className:"bg-card border border-border p-6 rounded-lg",children:[l.jsx("h3",{"data-loc":"client/src/pages/Strategy.tsx:305",className:"text-xl font-bold text-foreground mb-3",children:"The Adaptive 8 Solution"}),l.jsx("p",{"data-loc":"client/src/pages/Strategy.tsx:306",className:"text-sm text-muted-foreground",children:"Adaptive 8 addresses these flaws through a paradigm shift. Rather than assuming stable correlations and maintaining fixed allocations, it identifies the top trending assets monthly from a liquid universe and allocates capital based on risk parity principles applied to those currently trending assets."})]})]})}),l.jsxs("section",{"data-loc":"client/src/pages/Strategy.tsx:314",className:"space-y-6",children:[l.jsxs("div",{"data-loc":"client/src/pages/Strategy.tsx:315",className:"flex items-center gap-3",children:[l.jsx("div",{"data-loc":"client/src/pages/Strategy.tsx:316",className:"h-8 w-1 bg-secondary rounded-full"}),l.jsx("h2",{"data-loc":"client/src/pages/Strategy.tsx:317",className:"text-3xl font-heading font-bold",children:"Correlation-Agnostic Design"})]}),l.jsxs("div",{"data-loc":"client/src/pages/Strategy.tsx:320",className:"prose prose-lg dark:prose-invert max-w-none text-muted-foreground space-y-4",children:[l.jsxs("p",{"data-loc":"client/src/pages/Strategy.tsx:321",children:["The Acanto Adaptive All Asset 8 (8A) strategy is ",l.jsx("strong",{"data-loc":"client/src/pages/Strategy.tsx:322",children:"correlation-agnostic"}),". It uses momentum signals to identify trending assets and short-term volatility measures to size positions, adapting monthly to current market conditions. The strategy does not depend on any particular historical relationship between asset classesâit simply follows what is working now, sized appropriately for current risk levels."]}),l.jsx("p",{"data-loc":"client/src/pages/Strategy.tsx:324",children:"This real-time adaptive approach means the strategy benefits from non-correlation when it exists, but is not dependent on it. The strategy only cares about recent data (last 3-6 months for momentum, last 60 days for volatility), not decades of historical correlations."})]})]}),l.jsxs("section",{"data-loc":"client/src/pages/Strategy.tsx:331",className:"space-y-6",children:[l.jsxs("div",{"data-loc":"client/src/pages/Strategy.tsx:332",className:"flex items-start gap-4 mb-6",children:[l.jsx("div",{"data-loc":"client/src/pages/Strategy.tsx:333",className:"h-16 w-1 bg-secondary rounded-full shrink-0 mt-1"}),l.jsx("h2",{"data-loc":"client/src/pages/Strategy.tsx:334",className:"text-3xl font-heading font-bold leading-tight",children:"The Smart Complement to IUL, Whole Life & Fixed Index Annuities"})]}),l.jsx("div",{"data-loc":"client/src/pages/Strategy.tsx:336",className:"bg-secondary/5 border border-secondary/20 rounded-xl p-8",children:l.jsxs("div",{"data-loc":"client/src/pages/Strategy.tsx:337",className:"grid md:grid-cols-2 gap-12 items-center",children:[l.jsxs("div",{"data-loc":"client/src/pages/Strategy.tsx:338",className:"space-y-6",children:[l.jsx("h3",{"data-loc":"client/src/pages/Strategy.tsx:339",className:"text-2xl font-bold text-foreground",children:"Uncapped Upside with Managed Drawdowns"}),l.jsxs("p",{"data-loc":"client/src/pages/Strategy.tsx:340",className:"text-muted-foreground leading-relaxed",children:["Indexed Universal Life (IUL), Whole Life, and Fixed Index Annuities (FIA) are powerful tools for principal protection and tax-free income. 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