10 categories. 3 ETFs each. 30 institutional expressions.
Every ETF in the universe was chosen to be liquid, pure-fit, and distinct from its two category peers. The three ETFs in each category express the same macro theme from different angles — so the model has three ways to be right and the portfolio avoids holding the same bet twice under different names.
Technology
Technology is the broad duration-growth sleeve. It captures institutional sponsorship of large-cap profitability, enterprise software demand, and cyber-security non-discretionary spend — without overlapping with the AI compute stack, which has its own category.
XLK represents mega-cap profitability and the institutional anchor. IGV represents the software layer where AI adoption shows up in enterprise buying. CIBR represents the one sub-sector of tech that behaves defensively regardless of macro — security spend is a cost center, not a discretionary line item.
Broad profitable mega-cap technology leadership
Tracks the S&P 500 Technology sector. Heavily concentrated in Apple, Microsoft, and NVIDIA, with exposure to semiconductors, software platforms, and hardware. One of the most liquid ETFs in existence.
XLK captures the institutional anchor trade — the ETFs that dominate passive flows and act as the de-facto technology benchmark. It is the most correlated with the broad market and the most sensitive to rate-regime changes because of its duration profile.
Monitor its relationship to SPY. When XLK leads SPY it usually confirms risk-on tape. When XLK lags, it is often a rate-regime warning sign even before the bond market moves.
Enterprise software and SaaS adoption layer
Tracks software and SaaS companies including Salesforce, Adobe, ServiceNow, Workday, and hundreds of smaller software businesses. Pure-play software — no hardware, no semiconductors.
IGV measures whether enterprise technology spending is accelerating or contracting. Unlike XLK (which can be held up by Apple hardware or NVIDIA compute), IGV reflects the willingness of corporations to sign multi-year software contracts. It is also more sensitive to Fed rate changes because software valuations are pure duration.
IGV outperforms XLK during disinflation and falling-rate environments. It underperforms during stagflation, rising real yields, and enterprise budget freezes. Watch the IGV/XLK ratio as a leading indicator of risk appetite within tech.
Non-discretionary security spend — the defensive sub-sector of tech
Tracks cybersecurity companies including CrowdStrike, Palo Alto Networks, Fortinet, and Zscaler. These companies sell mandatory infrastructure, not discretionary software upgrades.
CIBR has a lower beta to the broad market than XLK or IGV because cybersecurity budgets are contractually protected even during IT spending freezes. In a stagflation or late-cycle environment where enterprise software gets cut, security is the last budget line reduced. This makes CIBR uniquely positioned when the rest of tech is under pressure.
CIBR outperforms XLK most clearly in late-cycle and risk-off environments. It lags in pure risk-on liquidity expansions where the highest-beta software names capture all the flows.
AI
AI is the compute and automation sleeve. It separates the physical compute layer (semiconductors) from the software application layer (AI platforms/models) and the robotics/physical automation layer — because each can lead at a different phase of the AI buildout cycle.
SMH represents the bottleneck — the chips that every AI application depends on. AIQ represents the software platforms building on top of that compute. BOTZ represents the physical automation layer where AI becomes a robot, a machine, or an automated factory. Each responds to a different part of the AI investment cycle.
AI compute bottleneck — the picks and shovels of the AI buildout
Tracks the 25 largest semiconductor companies globally including NVIDIA, TSMC, ASML, Broadcom, and Applied Materials. Covers chip design, manufacturing equipment, and memory.
SMH is the purest proxy for AI infrastructure demand. When hyperscalers accelerate capex, SMH leads. When supply constraints ease or demand softens, SMH corrects fastest. It is the most volatile and highest-beta ETF in the AI category because the semiconductor cycle amplifies both upside and downside.
NVIDIA's weight in SMH makes it a quasi-single-name bet. Watch NVIDIA earnings and guidance as the forward indicator for the entire ETF. The SOXX/SMH spread also tells you whether the rally is concentrated (NVIDIA-led) or broad (full semi-cycle participation).
AI software and application platforms
Tracks companies developing or using AI across software, cloud platforms, data analytics, and AI-adjacent services. Includes Alphabet, Meta, Microsoft, and dedicated AI software companies.
AIQ is the application layer. When AI spending shifts from infrastructure (chips) to software adoption (licenses, APIs, productivity tools), AIQ outperforms SMH. It has lower hardware-cycle exposure and is more correlated to enterprise adoption rates and software multiple expansion than to wafer demand.
The AIQ/SMH ratio is a cycle indicator within AI. Early in an AI wave, SMH leads. As the buildout matures and software monetization becomes the theme, AIQ leadership catches up. A sustained AIQ outperformance often signals the compute capex phase is digesting.
Physical AI — robotics, automation, and industrial AI systems
Tracks robotics companies, autonomous systems, industrial automation, and AI-integrated machinery. Includes Intuitive Surgical, ABB, Keyence, Fanuc, and autonomous vehicle supply chains.
BOTZ has a meaningful industrial cyclical component that AIQ and SMH do not. It performs best when manufacturing capex is rising, industrial automation is accelerating (deglobalization/reshoring), and robotic supply chains are being rebuilt. It lags in pure software rallies but can outperform when the AI story expands from digital to physical.
Monitor global manufacturing PMIs and reshoring capex announcements. BOTZ is sensitive to trade policy and industrial capex in ways that SMH and AIQ are not.
Defense & Aerospace
Defense and aerospace is the fiscal-geopolitical sleeve. It captures national security spending, which is one of the few categories where government budgets expand during economic weakness, geopolitical stress, and late-cycle environments simultaneously.
ITA represents the established prime contractors with multi-decade backlog visibility. XAR adds equal-weight aerospace and defense, which shifts exposure toward mid-cap suppliers rather than the largest primes. ROKT adds the space and aerospace optionality that is driven by different demand signals than traditional defense.
Defense prime contractors with multi-year backlog visibility
Tracks U.S. aerospace and defense companies including Raytheon, Lockheed Martin, Northrop Grumman, L3Harris, and Boeing. Concentrated in companies with multi-year government contracts.
ITA is the most contractually protected ETF in the category. Revenue is locked into long-term defense contracts that survive budget cycles, recessions, and credit stress. It is the defensive-of-defensives inside this sleeve.
ITA responds most to U.S. defense budget announcements, NATO spending commitments, and geopolitical escalations that trigger multi-year procurement cycles. Boeing's weight introduces some execution risk that is not purely geopolitical.
Equal-weight aerospace and defense — mid-cap suppliers over mega-cap primes
Tracks the S&P Aerospace & Defense Select Industry Index on an equal-weight basis, so mid-cap suppliers, component manufacturers, and smaller defense technology firms carry the same weight as the largest primes.
XAR's equal weighting is the entire point. ITA is dominated by a handful of mega-cap primes, so it moves with Lockheed, RTX, and Boeing. XAR spreads exposure across the supplier base, which means it captures broad sector participation and benefits more when defense spending flows down the supply chain rather than concentrating in a few prime contracts.
XAR outperforming ITA signals broad sector participation rather than a few large contract awards. Because it is equal weight, it is also more sensitive to small and mid-cap risk appetite than ITA.
Space economy, commercial aerospace, and autonomy optionality
Tracks companies involved in space technology, satellite communications, rocket manufacturing, autonomous vehicles, and ocean technologies. Includes SpaceX contractors, satellite operators, and aerospace innovators.
ROKT is the high-beta growth bet within the defense/aerospace category. Unlike ITA and PPA (which have stable contractual revenue), ROKT's companies are growing into commercial markets that are not yet fully priced. It performs best when risk appetite is high, government contracts expand into commercial space, and investor imagination runs ahead of current revenue.
ROKT is the most sensitive to risk-off episodes within the defense sleeve. If defense is in the portfolio for safety reasons, ROKT is the first to underperform. It is best suited for periods when defense meets risk-on.
Agriculture & Livestock
Agriculture is the food-security, input-cost, and commodity-reflation sleeve. It uses equity exposure to agricultural businesses rather than futures-heavy commodity products, capturing the economics of food production rather than the technical dynamics of commodity futures rolls.
MOO captures the agribusiness infrastructure — the large-cap farmers, fertilizer producers, and food equipment companies that benefit from input-cost pricing power. VEGI captures global agriculture broadly — more geographic exposure including emerging-market food producers. FTAG adds the food chain and supply-chain layer beyond just the production side.
Agribusiness — fertilizers, farm equipment, and large-cap food producers
Tracks global agribusiness companies including Deere & Co, Archer-Daniels-Midland, Bunge, Nutrien (fertilizer), and Corteva Agriscience. Covers crop inputs, equipment, and processing.
MOO captures the pricing-power side of agriculture — the companies that sell inputs to farmers at elevated margins during supply shocks. When fertilizer prices spike, when crop yields decline, when farm equipment demand is high — MOO's companies benefit from the economics of scarcity rather than just commodity price direction.
Natural gas prices (key fertilizer input), crop price expectations, and global food-trade disruption. MOO outperforms most clearly during stagflation when food inflation drives earnings upgrades for agribusiness.
Global agriculture producers with emerging-market exposure
Tracks a global index of agriculture producers including large Brazilian, Southeast Asian, and European agribusiness companies alongside U.S. names. Broader geographic coverage than MOO with less concentration in equipment and more in production.
VEGI adds global geographic breadth that MOO misses. When the agriculture thesis is driven by emerging-market food demand, Brazilian soybean cycles, or Southeast Asian commodity export growth, VEGI captures it better. Its EM exposure also means it benefits from dollar weakness more than MOO.
Brazilian real, global food trade flows, and emerging-market crop export data. VEGI often leads during reflation cycles when EM commodity exporters receive the first earnings benefits.
Broad agricultural commodities — direct exposure diverging from equity-heavy peers
Holds futures across a diversified basket of agricultural commodities — corn, soybeans, wheat, sugar, coffee, cocoa, and livestock — rather than a single grain. Tracks commodity prices directly, with no equity company exposure. Structured to report on a 1099 instead of a Schedule K-1.
PDBA provides what MOO and VEGI cannot: direct commodity price exposure. During agricultural supply shocks — drought, fertilizer disruption, export restrictions — commodity prices can move sharply while the equity producers lag, because companies do not capture spot price moves instantly. Spreading across grains, softs, and livestock makes it steadier than a single-crop fund: a wheat-only shock moves it less, but it is far less exposed to one crop's idiosyncratic weather. It replaced WEAT in the universe on 2026-08-07 because WEAT's K-1 partnership structure is not purchasable in many brokerage and retirement accounts.
USDA crop reports and WASDE releases, global grain export corridors, fertilizer and energy input costs, and La Niña/El Niño forecasts affecting yields across multiple growing regions.
Precious Metals
Precious metals are the monetary hedge, real-yield, and fiscal-dominance sleeve. Gold is the monetary anchor. Silver adds industrial demand and higher beta. Miners add operating leverage to metal prices but introduce equity and production risk.
GLD is the clean monetary hedge — no equity risk, no production risk, just the metal. SLV adds industrial demand that gold lacks and provides higher beta in risk-on precious metal rallies. GDX adds mining equity leverage when the market believes metal prices will stay elevated long enough to reward production expansion.
Physical gold — the pure monetary and real-yield hedge
Holds physical gold bullion. No equity risk. Tracks spot gold price minus a small management fee. The most liquid precious metals vehicle in existence.
GLD is the only ETF in the category with zero equity or production risk. In a crisis or credit event, GLD can appreciate while GDX falls because miner equities sell off with everything else. GLD's primary drivers are real yields, dollar pressure, central bank buying, and geopolitical stress — not mining margins.
10-year TIPS yield (real yield), DXY dollar index, and central bank gold reserve reports. GLD is the cleanest trade expression for falling real yields and dollar weakness.
Silver — monetary beta with industrial demand hybrid
Holds physical silver. Silver is both a monetary metal (driven by real yields and dollar pressure like gold) and an industrial metal (driven by solar panel manufacturing, EV charging, electronics, and industrial demand). This dual nature makes SLV more volatile and more cyclically sensitive than GLD.
SLV provides what GLD cannot: industrial demand exposure. In a reflation cycle where manufacturing PMIs are rising and renewable energy build-out is accelerating, silver benefits from physical industrial demand on top of monetary tailwinds. SLV typically has a higher beta to precious metal bull markets than GLD but also falls harder in risk-off episodes.
Solar installation rates, global manufacturing PMIs, and the gold-silver ratio. When silver is outperforming gold (falling gold/silver ratio), it usually signals genuine industrial demand momentum, not just monetary-hedge buying.
Gold mining equities — operating leverage to gold prices
Tracks large gold mining companies including Newmont, Barrick, Agnico Eagle, Wheaton Precious Metals, and others. Mining equity exposure means GDX has balance-sheet, production, and management risk that physical gold ETFs do not.
GDX provides leverage to gold prices through the operating cost structure of miners. When gold rises above miners' all-in sustaining costs, margins expand rapidly — giving GDX 2-3x the move of GLD in strong gold bull markets. However, in risk-off episodes or gold corrections, GDX underperforms GLD because equity beta drags it down even when gold is stable.
All-in sustaining costs for major miners, gold price relative to those costs, and equity market risk appetite. GDX works best when both gold is rising AND equity risk appetite is supportive. A GLD rally during maximum fear often leaves GDX behind.
Industrial Metals
Industrial metals are the real-economy and electrification sleeve. Copper, rare earths, and diversified mining each represent a distinct physical demand story: copper is the economic cycle barometer, rare earths are the strategic materials bottleneck, and diversified miners represent commodity breadth.
COPX isolates the copper story — the most economically sensitive single metal. REMX isolates the rare earth and strategic materials story — driven by EV, defense, and supply-chain deglobalization, not just the commodity cycle. PICK provides diversified mining breadth that catches commodity cycles that copper and rare earths might miss.
Copper miners — the barometer of global industrial demand
Tracks global copper mining companies. Copper is used in virtually every electrical system, construction project, and industrial process. COPX is the equity expression of copper supply-demand dynamics.
COPX is the most economically sensitive ETF in the Industrial Metals category. It rises when global manufacturing accelerates, infrastructure spending expands, and electrification investment increases. Unlike PICK (which diversifies across metals), COPX is a pure-play copper bet — which means it is more volatile and more directly responsive to copper price moves.
Global PMI composite (especially China), copper futures term structure, and mine supply disruptions. The copper-to-gold ratio is one of the oldest economic cycle indicators — watch it as a leading indicator for whether COPX is in an improving or deteriorating macro environment.
Rare earths and strategic materials — deglobalization and EV supply chains
Tracks companies mining and processing rare earth elements, lithium, cobalt, and other strategic materials critical for EVs, defense systems, and advanced electronics. Includes Chinese and non-Chinese rare earth producers.
REMX is driven by supply-chain deglobalization, EV adoption, and defense technology demand — not just the commodity cycle. China controls over 80% of rare earth processing, making REMX uniquely sensitive to geopolitical supply-chain risk. It can outperform other industrial metals ETFs when trade policy, EV adoption, or defense procurement accelerates, regardless of the broad commodity cycle.
China export restrictions on rare earths, Western mine permitting timelines, and EV production forecasts. REMX is more geopolitically sensitive than COPX or PICK.
Diversified global mining — commodity breadth across the metals complex
Tracks a global index of metals and mining companies spanning iron ore, coal, copper, aluminum, zinc, nickel, and platinum group metals. Includes BHP, Rio Tinto, Vale, and Glencore.
PICK provides what COPX and REMX cannot: commodity breadth. When the metals complex is rising broadly — not just copper or rare earths — PICK captures the whole move. It also has lower volatility than COPX or REMX because diversification across metals reduces single-commodity risk. It is the more conservative way to own industrial metals exposure.
The Bloomberg Commodity Index (broad) vs. the LME metals sub-index. When commodity breadth is wide, PICK outperforms relative to COPX. When the cycle is concentrated in copper specifically, COPX leads.
Traditional Energy
Traditional Energy is the hydrocarbon scarcity, inflation-pass-through, and energy-cash-flow sleeve. It combines oil and gas into one category because both respond to the same supply discipline, geopolitical pressure, and inflation dynamics — but the three ETFs separate the risk/reward profiles meaningfully.
XLE captures the integrated majors with the strongest balance sheets and dividend protection. XOP captures E&P beta — companies that benefit most from rising oil prices but are exposed to the downside. FCG captures natural gas and LNG demand, which is driven by power generation, AI data center energy demand, and export markets — a distinct and currently underowned story.
Integrated energy majors — cash flow, dividends, and inflation defense
Tracks the S&P 500 Energy sector. Heavily weighted to Exxon Mobil, Chevron, and other integrated majors. These companies produce, refine, and distribute energy with large balance sheets and significant dividend programs.
XLE is the defensive expression of the energy trade. Integrated majors have diversified operations, strong balance sheets, and dividend support that buffers the downside of oil price corrections. XLE works best when the energy thesis is about inflation protection and cash flow — not pure oil price leverage.
Dividends sustainability (payout ratio vs. free cash flow), oil price break-even for Exxon and Chevron, and refining margins. XLE's relative outperformance vs XOP tells you whether the market trusts the energy trade or is treating it speculatively.
E&P pure-play — maximum oil price leverage
Tracks upstream exploration and production companies. Unlike XLE (which has downstream refining and a few mega-caps dominating), XOP is equally weighted across smaller, more leveraged E&P companies.
XOP provides the highest oil price beta in the energy category. When oil spikes, XOP outperforms XLE by a significant margin. However, it has much more downside in oil corrections because smaller E&P companies have thinner balance sheets and higher operating leverage. XOP is the trade when you believe oil will stay high — not when you want inflation protection.
WTI futures curve shape (contango vs. backwardation), U.S. rig counts, and E&P hedging ratios. XOP leads in the first phase of an energy rally but often gives back gains faster than XLE in corrections.
Natural gas and LNG — power demand, AI data centers, and export markets
Tracks companies involved in natural gas exploration, production, distribution, and LNG export. Includes EQT, Antero Resources, and midstream companies connected to LNG export facilities.
FCG captures a distinct demand story: AI data centers require massive amounts of electricity, and natural gas is the primary baseload power source in the U.S. LNG export growth also ties natural gas prices to European and Asian demand, decoupling it partially from U.S. seasonal patterns. This gives FCG independent drivers that XLE and XOP lack.
Henry Hub natural gas prices, LNG export utilization rates, U.S. power generation demand (especially AI data center electricity consumption), and European energy import needs.
Nuclear Energy
Nuclear Energy is the uranium fuel-security and baseload-power sleeve. It captures both the physical scarcity of uranium fuel and the policy-driven expansion of nuclear power as the only scalable zero-carbon baseload source — particularly relevant as AI data centers require reliable 24/7 power.
URNM captures the established uranium mining story — the companies most correlated to spot uranium prices. URA adds diversified uranium exposure including physical uranium and international miners with a broader basket than URNM. NLR adds the regulated nuclear utility side — companies that operate reactors and have long-term power purchase agreements, making it far more defensive than the miners.
Senior uranium miners — direct spot uranium price leverage
Tracks established uranium mining companies including Cameco, Kazatomprom, and uranium royalty companies. Also holds physical uranium through the Sprott Physical Uranium Trust.
URNM is the most direct equity expression of uranium spot price movements. When utilities sign new fuel contracts or spot uranium demand spikes, URNM leads. It is the primary expression for uranium conviction trades.
Spot uranium price (UxC weekly spot), utility long-term contracting activity, and Kazatomprom (Kazakhstan) production guidance. The long-term contract cycle for uranium typically takes 2-3 years to fully play out.
Diversified uranium miners + physical uranium — broad uranium beta
Tracks a diversified basket of uranium mining companies and physical uranium holdings across multiple countries. Includes both large producers and mid-tier miners, providing broader exposure than URNM's senior-miner focus.
URA provides broader uranium exposure than URNM with less concentration in the very largest producers. It includes physical uranium exposure and international miners not captured by URNM, making it a diversified complement in the uranium bull thesis.
Spot uranium price, utility contracting cycles, and international uranium policy (Canada, Australia, Kazakhstan). URA tends to lag URNM slightly in bull moves but captures more of the sector breadth.
Nuclear utilities and reactor operators — baseload power income
Tracks companies that generate power from nuclear reactors, including Constellation Energy, Duke Energy, Exelon, and international utility operators. Also includes some uranium mining exposure.
NLR is the defensive expression of nuclear energy. Reactor operators have long-term power purchase agreements that provide stable, predictable revenue regardless of spot uranium price volatility. NLR works when the investment thesis is about nuclear power as regulated baseload infrastructure — especially relevant for AI data center power demand — rather than uranium price speculation.
U.S. nuclear license renewals, new nuclear capacity announcements (SMRs), power purchase agreements with AI hyperscalers, and electricity grid capacity markets.
Emerging Markets
Emerging Markets is the global liquidity and non-U.S. growth sleeve. It captures the rerating opportunity when the dollar weakens, global liquidity improves, and commodity-exporting nations benefit from terms-of-trade improvements. The three ETFs separate broad EM beta, domestic India growth, and commodity-driven Latin America.
IEMG provides the broadest, most liquid EM exposure — the default EM trade. INDA isolates India's domestic growth story, which is driven by internal demand, policy reform, and demographics rather than global commodity prices. ILF captures Latin America's commodity and value exposure, which behaves very differently from Indian growth or Asian tech EM.
Broad emerging markets — the institutional EM anchor trade
Tracks a broad index of emerging market equities across China, India, Taiwan, South Korea, Brazil, and other EM nations. One of the most liquid and widely held EM ETFs. Technology-heavy due to large TSMC and Samsung weights.
IEMG is the go-to for broad EM beta. It captures dollar weakness, global liquidity expansion, and the institutional rotation into non-U.S. assets. When the consensus shifts from U.S. exceptionalism to global diversification, IEMG is typically the first to receive inflows.
DXY dollar index (EM most sensitive to dollar direction), China economic policy announcements, and global risk appetite. IEMG leads EM rallies but also sells off faster than INDA or ILF in risk-off episodes.
India domestic growth — demographics, reform, and internal demand
Tracks Indian equities across financials, IT services, consumer staples, and infrastructure. Unlike IEMG (which is sensitive to China), INDA's performance is driven by Indian domestic demand, interest rate policy from the RBI, and corporate earnings growth.
INDA is the most independent EM ETF in the category — it has the lowest correlation to China, the lowest commodity price sensitivity, and the strongest domestic demand driver. India's growth story (digitization, infrastructure, middle class expansion, demographics) is internal enough that INDA can outperform IEMG even when China is weak.
Indian GDP growth, RBI rate decisions, India fiscal stimulus, and the premium/discount of INDA vs. India's domestic equity market. INDA sometimes lags IEMG in risk-on EM rallies but holds up better in China-driven selloffs.
Latin America — commodity-export value with currency beta
Tracks 40 of the largest Latin American companies primarily from Brazil, Mexico, and Chile. Heavy exposure to Petrobras, Vale, Brazilian banks, and Mexican conglomerates. Highly sensitive to oil, iron ore, and other commodity prices.
ILF is the most commodity-sensitive and value-oriented EM ETF in the category. Brazil is effectively an expression of iron ore, oil, and agricultural commodity prices wrapped in equity form. When reflation and commodity cycles are strong, ILF can significantly outperform IEMG. However, it also has the highest political and currency risk of the three.
Brazilian real (BRL/USD), Chinese steel demand (drives iron ore prices, which drives Vale), and Petrobras oil production guidance. ILF can be the strongest EM performer in commodity supercycles but the weakest in global risk-off or Chinese demand slowdowns.
Utilities & Infrastructure
Utilities and Infrastructure is the defensive-income, grid-build, and AI power-demand sleeve. It separates classic regulated utilities (rate-sensitive income) from domestic infrastructure (capex-driven growth) and global infrastructure (diversified income) to capture different phases of the rate and capex cycle.
XLU is the rate-sensitive defensive anchor — the bond proxy in equity form. PAVE is the domestic infrastructure growth play — driven by fiscal spending, not interest rates. IGF is the global infrastructure income fund — diversified across airports, toll roads, and utilities globally, with lower correlation to U.S. rate moves.
Regulated U.S. utilities — the bond proxy and defensive anchor
Tracks U.S. regulated utilities including NextEra Energy, Southern Company, Duke Energy, Dominion Energy. These companies have regulated returns, predictable dividends, and highly leveraged balance sheets.
XLU is the most interest-rate-sensitive ETF in the category. When rates fall, XLU benefits from both multiple expansion and reduced financing costs. When rates rise, XLU underperforms because its dividend yield becomes less competitive and its debt cost rises. XLU is a defensive play in economic slowdowns but is not AI data center growth play.
10-year Treasury yield (primary driver), utility earnings growth vs. rate cost, and dividend sustainability. XLU/SPY ratio is a classic risk-off/risk-on indicator.
Domestic infrastructure build — construction, materials, and fiscal spending
Tracks U.S. companies involved in infrastructure construction, raw materials for infrastructure (steel, aggregates), engineering, and heavy equipment. Includes Vulcan Materials, Martin Marietta, Caterpillar, Fluor, and Jacobs Engineering.
PAVE is the most cyclical ETF in the utilities/infrastructure category. It is driven by government infrastructure spending, construction activity, and industrial demand — not interest rates. The Inflation Reduction Act and Infrastructure Investment and Jobs Act created multi-year tailwinds. PAVE can perform in risk-on environments where XLU underperforms.
U.S. federal infrastructure spending authorization and appropriation, construction spending data, and industrial raw material pricing. PAVE outperforms XLU when rates are rising but fiscal spending is expanding.
Global infrastructure income — airports, toll roads, utilities diversified globally
Tracks global infrastructure companies including toll road operators, airport managers, gas pipeline operators, and water utilities across Europe, Australia, North America, and Asia. Diversified by infrastructure type and geography.
IGF offers what XLU and PAVE lack: geographic diversification and infrastructure asset type diversification. Airports, toll roads, and pipelines have different demand drivers than regulated utilities. IGF also has lower correlation to U.S. interest rates than XLU because of its international footprint and non-utility infrastructure mix.
Global economic activity (airports and toll roads depend on traffic volumes), currency movements (IGF has significant non-USD revenue), and infrastructure project pipeline in Australia and Europe.
Three overlay states that replace 50% of the category allocation.
When a regime trigger fires, the portfolio is split 50% overlay / 50% categories. The category sleeve uses the same tier ranking but with half the weights (10%/10%/5%×6/0%/0%).
BTC reclaims the 50W SMA on two consecutive closes (TrendBTC) or completes a 200W buy zone accumulation and range escape (ValueBTC).
50% FBTC — the most liquid Bitcoin ETF available. The other 50% goes to the category winners under overlay weights.
BTC is already in trend or value state, OTHERS/BTC ratio shows altcoin leadership, Fear & Greed is 50–90, ISM PMI above 50, dollar pressure is contained, and credit stress is low. All conditions must pass simultaneously.
50% FSOL — Solana as the altcoin-cycle expression. The category sleeve runs at overlay weights.
Crisis macro risk score exceeds threshold OR 3 of 5 bear-defense conditions fire (SPY/QQQ trend damage, HYG credit breakdown, dollar spike, risk appetite broken). Only activates when crypto is NoCrypto — confirmed BTC cycle has priority.
50% cause-matched: SGOV (liquidity crisis), GLD (monetary/disinflation), XLE (inflation/scarcity), GLD+XLE split (stagflation), or SGOV+GLD+XLU (transition). The cause selector determines which.