Home Finance The Anti-AI ETF Is Here, and Its Biggest Holdings Are Engines, Trucks and Air Conditioners
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The Anti-AI ETF Is Here, and Its Biggest Holdings Are Engines, Trucks and Air Conditioners

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  • Cummins (CMI) posted record Q2 Power Systems sales of $2.3 billion, up 19%, by selling backup diesel generators directly to AI data centers.

  • AutoZone (AZO) and Lennox (LII) anchor LOHA’s physical-moat thesis, though Lennox’s residential revenues fell 30% as high mortgage rates squeezed demand.

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Roundhill’s Roundhill Heavy Assets and Low Obsolescence ETF (NYSEARCA:LOHA) launched in May 2026 as a counterweight to the software and AI concentration dominating most passive equity portfolios. The idea belongs to Josh Brown of Ritholtz Wealth Management, who coined the acronym HALO for heavy assets and low obsolescence to describe companies whose value sits in physical infrastructure, entrenched distribution, and long-lived capital rather than in code that a competitor can rewrite. LOHA translates that idea into an index of 100 US companies, equally weighted and rebalanced quarterly, with a 0.35% expense ratio and a unitary fee structure under which Roundhill absorbs most operating expenses.

Close-up of a person wearing grey work overalls and white gloves, holding a manifold gauge set with red and blue pressure gauges connected to a car engine. The engine bay is open, revealing dark engine components, hoses, and an orange dipstick handle. The background is blurred, showing a workshop setting.
AleksandarGeorgiev / iStock via Getty Images

The top holdings make the pitch clear. Cummins (NYSE:CMI) builds diesel and natural gas engines, AutoZone (NYSE:AZO) runs the largest aftermarket auto parts network in the country, TFI International (NYSE:TFII) hauls freight, Lennox International makes furnaces and rooftop HVAC units, and Newmont digs gold out of the ground. If AI-heavy indices own the software layer, LOHA owns what sits under, around, and behind it.

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The Thesis Behind Heavy Assets

The argument runs like this: a company whose competitive position depends on physical scale (mines, factories, distribution centers, truck fleets, refrigerated warehouses, a national franchise footprint) cannot be disintermediated by a well-funded startup with GPUs. Replicating AutoZone’s roughly 20% operating margin requires actually building thousands of stores stocked with the right SKUs within a short drive of a mechanic who needs a part today. Replicating Cummins’ multi-year hyperscaler agreement, which secures several gigawatts of future backup power genset demand, requires foundries, engineering depth, and permits that a model checkpoint cannot provide.



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