AIMAI Infra Monitor
AI Infra MonitorAtlas 01 · AI infrastructure fund map
Six listed routes into the physical AI buildout

AI Infrastructure ETF Atlas

AIPO, GRID, LYTE, DRAM, NCLD and DTCR do not own the same trade. This atlas separates the broad buildout from its scarce inputs—power delivery, optical bandwidth, memory, GPU capacity and data-center real estate—then compares what the tape has rewarded.

01 / Performance

One starting line. Six paths.

By default every series starts at 0% on the first close all six funds share, so the returns compare like for like. Full 2026 rebases each fund at its first 2026 close: AIPO, GRID and DTCR from January, DRAM, LYTE and NCLD from their launches. Click a ticker to isolate a path.

2026 market-price change

Market-price change · loading…

Solid lines: single-bottleneck funds · dashed: broad baskets

Price return, not total return.
Latest 2026 performance by fund
TickerSince first shared closeFull 2026 periodFull 2026 return
02 / Read-through

Three decisions hiding inside one theme.

The tickers can complement one another, but indiscriminately owning all six quietly builds repeated exposure to the same capital-spending cycle.

Few shared holdings.

Portfolio weight each pair of funds holds in the same securities, in percent

Prices that move together.

Correlation of daily price returns for each pair of funds
01 / Core vs satellite

Broad sleeves are not neutral.

AIPO spans power, construction, cooling and silicon; GRID leans industrial; DTCR leans real estate and towers. Each can anchor a basket, but each imports a different factor exposure.

02 / Chokepoint beta

Does purity raise torque?

DRAM, LYTE and NCLD target narrower scarcity claims. That can make the thesis legible, while increasing cycle, geography, financing and single-industry risk.

03 / Track-record trap

Do not compare unequal histories.

LYTE and NCLD have only closes in this dataset; DRAM began in April. The chart therefore opens on the window all six share; in the full-2026 view their lines are launch-to-date snapshots, not full-year evidence.

03 / Exposure map

From electrons to rent.

The cleanest comparison is by economic sleeve. The sequence is not a literal supply-chain order; it shows what scarce resource or asset class each fund monetizes.

    04 / Fund sleeves

    Each fund can break from the AI story.

    Each card pairs the mandate with fees, structure, launch date, leading exposures and the risk most likely to make the ticker behave differently from the AI narrative.

    05 / Holdings

    See the names behind each sleeve.

    Switch funds to inspect up to the top 20 issuer-reported security positions, ranked by portfolio weight. When a concentrated fund owns fewer than 20 distinct securities, the table shows its entire reported security portfolio.

    Holdings

    Positions shown—
    Top 5 weight—
    Shown weight—
    RankSecurityPortfolio weight
    06 / Compare

    The selection matrix.

    Purity is a qualitative measure of how directly the portfolio maps to the named AI infrastructure bottleneck—not a quality score or return forecast.

    FundPrimary sleeveStructureFeeInception2026 tapeTheme purityPortfolio role
    07 / Method

    Method & sources.

    Market data and fund descriptions are deliberately separated: Nasdaq supplies the closing-price series; issuers supply objectives, fees, inception dates and holdings.

    Performance methodology

    • Daily unadjusted closing market prices, through the latest date shared by all six funds.
    • The default chart view rebases all six to 0% at the first close they share. The full-2026 view rebases each series at its first available 2026 close, so 2026 launches show since-inception price change.
    • Distributions, taxes, bid/ask spreads and trading costs are excluded. Issuer-reported total returns will differ.
    • Holdings change. Every exposure list carries its own as-of date and should be refreshed before making a trade.
    • Cash, currencies and money-market funds are excluded. Roundhill rows sharing the same security identifier are consolidated; the displayed weights are summed.

    Primary sources

      AI Infra Monitor · built by Eric Wyluda · source
      Also by the author: MacroGauge (data center cost indexes) · GPU Price Index (compute rental prices)
      Research and analysis only, not investment advice. Market prices: FMP (equities) and Nasdaq (ETF history), shown with their quote dates.