Brad Gerstner’s Altimeter is making dramatic changes in its portfolio, dumping tens of millions of dollars in Alphabet (GOOGL) in a span of three months.
The News
Altimeter’s latest 13F filing from the U.S. Securities and Exchange Commission shows that the fund fully exited its stake in Alphabet in Q1 of this year.
The tech-focused firm unloaded all 519,290 GOOGL shares previously valued at $162.537 million.
Altimeter used the freed-up cash to accumulate picks-and-shovels plays in AI, starting with a new position in the AI chip architecture and licensing company ARM Holdings (ARM). The fund gobbled up 1,715,440 ARM shares valued at $259.511 million in Q1.
Also in the quarter ending March 31st, Altimeter opened a new stake in Axon Enterprise (AXON), an AI-powered firm focused on public safety. The firm bought 148,986 AXON shares worth $63.272 million.
On top of the newly opened positions, the firm loaded up on CoreWeave, adding 1,285,845 CRWV shares to bring its total position to 4,499,075 CRWV shares worth $348.543 million. Altimeter also added to its Broadcom stake, accumulating 34,965 AVGO shares in Q1 and increasing its ownership to 67,094 AVGO shares valued at $20.766 million.
What It Means for Investors
Gerstner’s Q1 moves mirror the portfolio reallocation of billionaire Stanley Druckenmiller’s Duquesne Family Office. Institutional investors are now shifting their strategy as they rotate capital into the potential winners of the massive AI spending this year, which is projected to shatter $800 billion, according to the banking titan Morgan Stanley.
Altimeter fully unloaded its stake in the Gemini creator Google and used the money to invest in different areas of AI diffusion and deployment. ARM Holdings, which is the company’s biggest purchase in Q1, licenses its AI chip architecture to some of the largest chip manufacturers in the world, including Apple (AAPL), Nvidia (NVDA) and Qualcomm (QCOM).
Meanwhile, CoreWeave, Altimeter’s fourth-largest buy last quarter, focuses on GPU cloud infrastructure, and Broadcom’s custom silicon is used by Google and Meta for AI inference training workloads.
Gerstner appears to be following where the AI spending money is headed, and that’s the signal for investors. Last month, the World Economic Forum projected that $7 trillion in data center investment is expected through 2030, and much of the spending will benefit hardware, cooling and power generation companies. The data indicates that the AI picks-and-shovels play still has a long way to go, and chip and infrastructure names are primed to capture the staggering amount of AI investment in the next four years.
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