The Defiance Quantum ETF (NYSEARCA:QTUM) offers exposure to global companies involved in areas like machine learning, artificial intelligence (AI), quantum computing, and other computing technologies.
QTUM is benefiting from the market momentum surrounding these themes in tech with advancements in AI seen as driving a new wave of growth for companies at the forefront of innovation. The fund has returned 28% over the past year.
On the other hand, QTUM's performance doesn't stand out as exceptional compared to tech benchmarks like the NASDAQ-100 (QQQ) or the Technology Select Sector SPDR ETF (XLK). We'll go through some of the fund's strong points and weaknesses, but overall find that its ambitious index misses the mark by not having a cohesive focus.
What is the QTUM ETF?
QTUM is intended to track the "BlueStar Quantum Computing and Machine Learning Index". This thematic index begins its securities selection process by screening companies primarily involved in "Quantum Computing" and, or "Machine Learning". This covers not only related products and services but also semiconductors, manufacturing equipment, materials, and specialty applications.
Beyond meeting criteria such as a minimum market capitalization of $150 million, and a free float of at least 10%, companies must also generate at least 50% of their revenue from related activities. The index and the QTUM ETF feature a modified equal-weighting methodology with a semi-annual rebalancing and reconstitution.
Missing a Distinct Strategy
From the current portfolio with 68 holdings, we find a variety of tech stocks covering well-recognized semiconductor industry leaders, mega-cap software names, as well as some emerging players.
Here we can point to our main criticism of the fund, which is that the overall exposure may be a bit too diverse across tech, making it lose its potential as a differentiated or unique thematic strategy.
Top 10 QTUM positions include Nvidia Corp (NVDA), Taiwan Semiconductor Manufacturing Co (TSM), Micron Technology Inc (MU), Qualcomm Inc (QCOM), and Applied Materials Inc (AMAT) are leading chip stocks, but not necessarily names we would consider as having quantum computing as a core business.
Similarly, the fund's largest position is in MicroStrategy Inc (MSTR), a company whose current operating model is based on accumulating Bitcoin (BTC-USD). While the stock has been a big winner this year amid the market rally, thereby increasing its role within the QTUM ETF, it's not a name we would consider a flagbearer for quantum computing or machine learning.
The problem with QTUM as we see it is that in 2024, "every" tech stock is involved with artificial intelligence which crosses over into machine learning. There's a case to be made that any company manufacturing computer hardware stands to benefit from the developments
Quantum computing can be seen as a distinct technology, but the limited number of companies we would consider as a pure-play into that field like Rigetti Computing Inc (RGTI), IonQ Inc (IONQ), or Arquit Quantum Inc (ARQQ) end up lost amid the greater number of tech sector bellwethers like Microsoft Corp (MSFT), Advanced Micro Devices Inc (AMD), Texas Instruments Inc (TXN), or Alphabet Inc (GOOGL).
In our opinion, QTUM doesn't do a great job as a "semiconductor" industry ETF and isn't differentiated enough from a general tech sector strategy.
Since the fund's inception date in September 2018, QTUM has returned a cumulative 171%, slightly trailing the 172% return from QQQ, but well below the 227% gain in XLK or 438% return by the VanEck Semiconductor ETF (SMH) over the period.
What Does QTUM Do Well?
Keep an open mind and balanced approach, we can't dismiss QTUM entirely as it's still possible the strategy could outperform going forward.
The inclusion of several foreign stocks in the portfolio that are not typically widely held like Hitachi Ltd (OTCPK:HTHIY), NEC Corp (OTCPK:NIPNF), or Renesas Electronics Corp (OTCPK:RNECY) is a strong point for the fund in that it can work as a portfolio diversifier for investors.
The quasi-equal-weighting methodology works to add importance to smaller holdings that are often underrepresented in larger indexes.
By this measure, QTUM has delivered an edge compared to alternative ETFs like the Direxion NASDAQ-100 Equal Weight ETF (QQQE) or the Invesco NASDAQ Next Gen 100 ETF (QQQJ) focusing on smaller companies. QTUM has outperformed both over the past year, recognizing it's not an apples-to-apples comparison.
What's Next for QTUM?
The good news is that we expect QTUM to continue benefiting from the broad market rally. A scenario where economic conditions remain resilient, with a potential for interest rates to stabilize lower could mark the start of a new tech growth driver carried by positive sentiment toward risk assets.
It's clear to us that the AI theme covering machine learning and related computing technologies remains in the early stages. Quantum computing stands to benefit from this dynamic through its alternative architecture representing a specialized approach for solving real-world optimization problems.
The companies within the QTUM portfolio are well-positioned to capture the next wave of innovation. That being said, the big question is whether the fund represents a better option for investors compared to a more vanilla-indexed tech alternative like XLK or QQQ. We remain skeptical on this point.
The main risk to consider is the possibility that economic conditions deteriorate at the macro level, forcing a reassessment of global demand tailwinds. A pullback in business investments toward AI or consumer spending could open the door for a wider market selloff and volatility in this side of tech stocks.
Final Thoughts
The QTUM ETF is an interesting option in the plethora of exchange-traded funds investors can choose from. Despite the strong gains from the fund, it's important to understand what's behind the curtain.
In this case, QTUM may not be the quantum computing and machine learning thematic fund investors are looking for. The 0.40% expense ratio appears pricey for what's on offer in our opinion.
Dan Victor, CFA
Dan Victor is passionate about financial markets and loves exploring what moves asset prices.
Analyst’s Disclosure: I/we have no stock, option or similar derivative position in any of the companies mentioned, and no plans to initiate any such positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.
The information contained herein represents the personal opinions and views of Dan Victor only and is intended for informational and/or educational purposes. It should not be construed as a specific recommendation or solicitation to buy or sell any security or follow any particular investment strategy. Please consult with your financial advisor before making any investment decisions.
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