What Is the QTUM ETF? The Defiance Quantum ETF, Explained

Educational content only. This article is not investment advice and is not a recommendation to buy, sell, or hold QTUM or any other security.

QTUM is the ticker symbol for the Defiance Quantum ETF, an exchange-traded fund built around companies tied to quantum computing and machine-learning technology. It's one of several funds in the market with "quantum" in the name or theme, which makes it an easy fund to confuse with similarly branded products. This article looks specifically at the Defiance Quantum ETF — what it is, what index it follows, what it actually holds, what it costs, and the risks that come with a thematic, emerging-technology fund. It does not evaluate whether QTUM is a good or bad investment for anyone, because that isn't a question a general-education article — or Zydhra as a platform — is positioned to answer.

What the Defiance Quantum ETF is

QTUM is issued by Defiance ETFs LLC and trades on the Nasdaq under the ticker QTUM (Defiance ETFs — QTUM fund page). The fund launched on September 4, 2018, making it one of the longer-running thematic technology ETFs in the current market (StockAnalysis.com — QTUM overview). It is structured as a passively managed, index-tracking ETF — meaning it isn't run by a manager picking stocks at their own discretion; instead, it aims to replicate the composition and performance of a specific published index, rebalancing its holdings periodically to stay aligned with that index (Defiance ETFs — QTUM fund page). Like other US-listed ETFs, QTUM is registered under the Investment Company Act of 1940 and its holdings and financial statements are disclosed in periodic filings with the SEC (SEC EDGAR — ETF Series Solutions N-CSR filing referencing QTUM).

The index and methodology it tracks

QTUM seeks to track the total return performance of the BlueStar Quantum Computing and Machine Learning Index, a benchmark maintained by BlueStar Global Investors, LLC, with index calculation now provided under the MarketVector Indexes platform (formerly known as MVIS) (Defiance ETFs — QTUM fund page; MarketVector — BlueStar Machine Learning and Quantum Computing Index (BQTUM)). Index branding and ownership in this corner of the market has shifted over time, and readers comparing sources should confirm they're looking at the specific benchmark QTUM currently tracks rather than a similarly named sibling index — MarketVector, for example, also publishes separate indexes such as the MarketVector Quantum Computing Ecosystem Index and the MarketVector Global Quantum Leaders Index, which are not the index QTUM tracks (MarketVector — Quantum Computing Ecosystem Index; MarketVector — Global Quantum Leaders Index).

According to the fund's own fact sheet, eligible companies must derive at least 50% of their annual revenue or operating activity from the development of quantum computing and machine-learning technology, including things like the design of quantum computers or computing chips, superconducting materials, applications built on quantum computers, embedded AI chips, and software focused on collecting, processing, or managing large datasets (Defiance QTUM Fact Sheet, PDF). Constituents are screened from a global universe of publicly listed companies, including emerging markets, on a semi-annual basis, based on regulatory filings, analyst reports, and industry trade publications (Defiance QTUM Fact Sheet, PDF).

One methodology detail is worth flagging rather than glossing over: the fund's fact sheet describes the index as a "modified equal-weighted portfolio," with individual position weights capped near 2% at rebalance (Defiance QTUM Fact Sheet, PDF), while the index provider's own public index page describes the broader BlueStar Machine Learning and Quantum Computing Index family as "modified market cap-weighted" (MarketVector — BlueStar Machine Learning and Quantum Computing Index (BQTUM)). These sources don't fully agree, and this piece isn't in a position to resolve the discrepancy — it's noted here so readers checking multiple sources aren't surprised by the inconsistency. Anyone who needs a precise, current answer should read the index's own published methodology guide, which is linked from the fund's documents page (MarketVector — BQTUM Index Guide, PDF), rather than relying on any single secondary summary, including this one.

What it holds

QTUM's portfolio spans companies connected to quantum computing and machine learning in different ways — not just pure-play quantum computing startups. Based on the fund's public holdings data, the mix includes semiconductor and chip-equipment companies (names like Applied Materials, MKS Inc., Onto Innovation, Teradyne, and Lam Research have appeared among the fund's larger positions), cloud- and data-infrastructure companies (such as Cloudflare), specialized semiconductor and connectivity firms (such as Astera Labs), and smaller, more speculative quantum-computing-focused companies (such as Arqit Quantum, Quantinuum, and Horizon Quantum Holdings) (StockAnalysis.com — QTUM holdings). As of the most recent data available from that source, the fund held roughly 86 individual positions (StockAnalysis.com — QTUM holdings).

Two things worth understanding about that mix. First, because the index's eligibility test is about a company's business activity rather than its sector classification, QTUM ends up spanning several conventional sectors — semiconductors, software, industrials, and communications equipment can all appear in the fund at once, unified by the "quantum/machine-learning" business-activity theme rather than a single industry code. Second, individual position sizes and the specific list of holdings change at each semi-annual reconstitution and can shift meaningfully between rebalances as constituent share prices move, so any specific holdings list — including the one above — is a snapshot, not a fixed roster. Readers who want the current list should check the fund's own holdings page directly rather than relying on a cited snapshot (Defiance ETFs — QTUM full holdings).

Costs and basic facts

Expense ratio: 0.40% per year, consistently reported across the fund's own materials and third-party data providers as of mid-2026 (Yahoo Finance — QTUM quote; Charles Schwab — QTUM ETF report). This is the fund's annual operating cost, expressed as a percentage of assets, and it's deducted from fund assets over time rather than billed separately — it does not include brokerage commissions or bid-ask spreads an investor may incur buying or selling shares.
Assets under management: The fund reported surpassing $5 billion in assets in a late-May 2026 press release published by the fund's own issuer (GlobeNewswire — Defiance Quantum Computing ETF (QTUM) Surpasses $5 Billion in Assets, May 26, 2026). Because it is issuer-published, and because AUM moves with both fund flows and the market value of the underlying holdings, treat it as a dated, promotional-context figure — check a neutral live source for a current number.
Distributions: QTUM has paid income distributions on a quarterly schedule (Dividend.com — QTUM dividend history). Reported trailing yield figures vary somewhat by source and calculation date — different data providers have shown slightly different trailing 12-month distribution totals and yield percentages for the same period, which is common for ETFs and usually reflects timing differences rather than a factual disagreement. As with AUM, treat any specific yield figure as a snapshot rather than a fixed rate, and note that a fund's distribution yield is not the same thing as its total return.

Risks and limitations of a thematic, emerging-technology ETF

The following is drawn from the fund's own disclosures and general characteristics of thematic-fund structures, cross-checked against issuer and third-party sources cited throughout this article. It is not a complete list of risks, is not a judgment on the fund, and is not a substitute for reading QTUM's official prospectus, which contains the fund's full, legally required risk disclosures. Readers should review that document and consider speaking with a licensed financial professional before drawing any conclusions.

A few structural features are worth understanding specifically because QTUM is a thematic, narrow-focus fund rather than a broad-market index fund:

Concentration in an emerging, unproven technology theme. Quantum computing, as an industry, is still in an early and rapidly evolving stage — commercial applications, competitive winners, and realistic timelines for widespread adoption remain unsettled. A fund built around this theme is more exposed to the fortunes (and setbacks) of a single technology narrative than a fund spread across the broader market.
Small-cap and early-stage-company exposure. Some of the fund's constituents are smaller, less established companies whose business is more directly tied to quantum computing specifically, as opposed to larger, diversified technology companies that happen to meet the index's eligibility criteria. Smaller companies can be more volatile and less liquid than large, established firms.
Sector and factor concentration despite a diversified-sounding holdings count. Even with dozens of holdings, a thematic fund's return can still be driven disproportionately by a handful of large positions or by sentiment toward the technology theme as a whole, rather than by the kind of broad economic diversification a total-market index fund is designed to provide.
Methodology and classification judgment. Because eligibility for the underlying index depends on a judgment call about how much of a company's business is "quantum computing or machine learning" related, reasonable people (and different index providers) can classify the same company differently, and a company's eligibility can change as its business evolves.
Volatility. Thematic technology funds, as a category, have historically shown higher price volatility than broad-market index funds over various periods. This is a description of a risk characteristic, not a prediction about what QTUM will do next — past performance does not guarantee or indicate future results, for QTUM or any fund discussed in this article.
Tracking and rebalancing effects. Because the fund aims to track an index rather than optimize returns directly, its holdings and weights shift at each semi-annual reconstitution regardless of an individual investor's own view of any single company in the fund.

How QTUM differs from a broad-market index fund

It can be useful to understand this contrast in general, educational terms — not as a comparison meant to favor one over the other. A broad-market index fund (one tracking, for example, the total US stock market or a large diversified index like the S&P 500) aims to reflect the performance of hundreds or thousands of companies across many industries, with position sizes generally driven by company size. A thematic fund like QTUM instead starts from a specific business-activity theme, screens a global universe of companies for exposure to that theme, and builds a portfolio — in QTUM's case, roughly 80-plus holdings — around that narrower criterion. The practical difference is exposure: a broad-market fund's return reflects the economy-wide average across many industries and company sizes, while a thematic fund's return reflects the fortunes of a specific slice of the market, concentrated around a single technological narrative. Neither structure is inherently better or worse — they answer different questions about what an investor wants their holdings to represent, and that's a decision that depends on an individual's own goals, time horizon, and risk tolerance.

Is the QTUM ETF right for you?

This article isn't going to answer that question, and it's worth being direct about why: whether any specific fund fits a specific person's portfolio depends on things only that person (or a licensed professional working with them) can properly weigh — their existing holdings and how concentrated they already are in technology, their time horizon, their tolerance for volatility, their tax situation, and their broader financial goals. Answering "should I buy this" for an individual reader would cross from general education into personalized investment advice, which is a regulated activity that Zydhra, as a portfolio-tracking tool, is not licensed to provide.

What can be said generally: thematic, single-technology funds like QTUM carry a different risk and concentration profile than broad-market index funds, for the reasons described above, and that difference is something worth understanding — independent of any specific decision — before researching further. If you're weighing whether a fund like this fits your own portfolio, consider reviewing the fund's official prospectus in full, examining how a position would fit alongside what you already hold, and, if appropriate, speaking with a licensed financial or tax professional who can look at your specific circumstances.

Disclaimer: This article is for general educational and informational purposes only. It is not investment advice, and nothing in it should be construed as a recommendation to buy, sell, or hold QTUM or any other security. Zydhra is a portfolio-tracking and analytics tool — it is not a broker-dealer and is not a registered investment adviser. Figures such as expense ratio, assets under management, holdings, and distribution yield change over time and were current as of the dates and sources cited above; they may no longer be accurate by the time you read this. Past performance does not guarantee or predict future results. Before making any investment decision, review the fund's official prospectus and consider consulting a licensed financial professional.