On Tuesday, June 2, Tuttle Capital premiered the Tuttle Capital Concentrated Memory Stack ETF (HBMX) on Cboe. Operating with an expense ratio of 95 basis points, HBMX offers exposure to pure-play memory stack companies in the rapidly growing memory semiconductor ecosystem.
The Roundhill Memory ETF (DRAM) has a similar focus to HBMX. As the most dominant ETF debut of 2026, DRAM recently crossed $14 billion in AUM after launching just two months ago. A comparison with HBMX reveals distinct strategic variations, however. DRAM utilizes a highly-concentrated model, with less than a dozen holdings as of early June. The strategy mandates that portfolio companies generate at least 50% of their revenue from memory semiconductor manufacturing or development. Additionally, DRAM requires a minimum market capitalization of $10 billion and an average daily trading volume of $5 million for its constituents. The lion’s share of its portfolio is in non-U.S. exposures.
See more: Powerhouse AI ETF DRAM Hits $6.5 Billion at Record Pace
In contrast, HBMX employs a more flexible investment framework, permitting inclusion regardless of market capitalization or trading volume. While it shares a focus on the memory semiconductor sector, HBMX operates with a lower memory-related revenue threshold of 25%. The fund also maintains a slightly broader portfolio of approximately 20 to 35 holdings.
Capturing AI Alpha Through Memory
HBMX is designed to capture “AI Alpha” by targeting the surge in AI-driven demand through a strategic focus on memory, a critical pillar of the AI revolution. This actively managed fund provides specialized exposure across the entire semiconductor memory ecosystem. Tuttle Capital classifies “memory stack companies” as entities involved in the development, manufacturing, packaging, testing, and commercialization of memory technologies.
“There are two things that in my mind necessitate the need for more specific exposure,” said Matthew Tuttle, CEO and chief investment officer of Tuttle Capital Management. “The first is AI and what it is going to destroy. Software is a great example. In the “old” days, you just buy something like IGV [iShares Expanded Tech-Software Sector ETF] and you have software covered. Today, there is a big difference between a software stock that AI is going to put out of business and a software stock that will be immune from, or benefit from AI.”
“The second is the bottleneck. For AI to reach its full potential it is going to encounter bottlenecks along the way, one such bottleneck is memory. Memory companies’ stock prices have been rewarded handsomely for helping to solve this bottleneck,” Tuttle added.
To maximize the potential for generating alpha, the fund invests mainly in equity holdings in memory stack companies or related financial instruments. Seeking to optimize the risk-reward profile, HBNX maintains a highly concentrated and narrow portfolio. This is to ensure a high-conviction approach to capturing growth within the sector.
With the massive memory requirements for AI development well-established, producers are set to gain from ongoing government and corporate capital spending. As data generation accelerates, HBMX provides a strategic way to enter the AI market while avoiding the volatility found in other industry segments.
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