AI Hardware Bet Splits Funds as Top Hedge Funds Gain 39%

A concentrated rally in artificial intelligence hardware stocks created a stark divergence in fund performance in April, with stock-picking hedge funds collectively logging their best month since 1999 while most active mutual funds fell behind their benchmarks.

"AI is our most computationally intensive thing, ever... We are in a golden age for hardware," Alex Sacerdote, whose Whale Rock Capital Management saw its public portfolio gain about 39 percent in April, said at the Sohn Investment Conference.

The chasm in returns was stark: tech-focused hedge funds rose 10.3 percent in April, according to PivotalPath data. In contrast, the proportion of active mutual funds outperforming the S&P 500 plummeted to just 28 percent, down from over 60 percent at the end of February, according to data from Barclays.

The performance gap highlights a critical juncture for asset managers, where exposure to a handful of semiconductor and AI supply chain stocks is now the primary determinant of relative success, forcing a crowded trade into a narrow market leadership despite growing macro-economic headwinds.

A Golden Age for Hardware Bulls

The April rally produced remarkable returns for managers with heavy exposure to the AI hardware theme. Steve Cohen’s Point72 Asset Management saw its flagship fund gain approximately 4.5 percent, marking one of its best months in over five years. A specialized AI fund within Point72, managed by Eric Sanchez, surged 15 percent.

Whale Rock’s 39 percent gain was reportedly driven by significant positions in memory and storage companies, including SanDisk, SK Hynix, and Kioxia. Similarly, the Seligman Tech Spectrum fund, managed by Paul Wick, jumped nearly 20 percent for its best monthly performance since its 2001 inception. The fund’s top holdings as of March included semiconductor giants Broadcom and Applied Materials.

This trend is reflected in broader positioning data. According to Morgan Stanley, hedge funds have increased their exposure to semiconductor stocks to the highest level in a decade. These stocks now constitute 20 percent of hedge fund net holdings, a dramatic increase from 5.5 percent just one year ago.

A Narrow Path to Outperformance

While concentrated bets paid off for some, the narrowness of the rally left most active managers struggling. The S&P 500 gained about four percent in April, but with less than half of its constituent stocks advancing, the gains were highly concentrated.

This is illustrated by the performance of the equal-weight S&P 500 index, which at the end of February was outperforming its market-cap-weighted counterpart by six percentage points. By the end of April, it was lagging by three percentage points, a nine-point swing that shows the influence of a few mega-cap tech stocks.

Many active mutual funds are falling behind, in part due to structural under-allocation to the largest technology names, as concentration rules prevent them from mirroring the index's heavy weighting. This has put them at a significant disadvantage in a market where a small number of AI-related stocks are responsible for the majority of gains.

Industrial-Scale Demand Underpins Rally

The core driver of this performance divide is the immense and accelerating demand for computing power. Tech giants like Microsoft, Alphabet, Meta Platforms, and Amazon have outlined a combined $670 billion in capital expenditures for the year, with the majority earmarked for data centers equipped with advanced chips.

This spending is fueling a boom across the entire supply chain, from chip designers like Nvidia to memory producers and equipment makers. It's also benefiting companies that provide the tools to manage this new infrastructure. AI-powered observability firm Datadog, for instance, has seen its stock soar 51 percent in 2026, more than doubling Nvidia's gains, after reporting its first $1 billion quarter.

However, the rally's sustainability depends on the industry's ability to meet this demand at scale. The core challenge is now industrial; a question of supply chain depth and production capacity. The situation mirrors challenges in other advanced technology sectors, where the ability to manufacture critical components at scale, not just design them, determines success. The market has accepted that the AI build-out is real; the next phase is about which companies can execute an industrial-scale ramp-up to meet the historic demand.

This article is for informational purposes only and does not constitute investment advice.