Key Takeaways
- • A tech selloff on October 22 led by Meta (down 7%) and Nvidia (down 4%) pushed Goldman Sachs-tracked hedge fund strategies down more than 1% on the day.
- • Goldman Sachs data showed tech-focused hedge funds down roughly 10% and Asia-focused funds down roughly 9% through October 22, weighed by technology and China-related holdings and crowded short positions.
- • Reuters attributed the slide to rising doubts about how much companies are spending to build AI, with Meta's plan to issue a new class of shares adding pressure through dilution concerns.
- • Traders described the move as deleveraging, as lenders and risk teams demanded more cash or lower exposure, causing correlated selling across portfolios with overlapping AI-linked positions.
- • TriVista Capital's Masaki Gotoh warned that the AI trade is uncomfortably concentrated and echoes the late-1990s dotcom era, citing a 'circular financing' loop between public equity markets and AI spending.
Summary
A broad technology selloff on October 22 spilled into hedge funds, leaving Goldman Sachs-tracked strategies down more than 1% on the day. The decline was led by Meta, which fell 7%, and Nvidia, which fell 4%. According to Reuters, the slide reflected rising doubts about how much companies are spending to build artificial intelligence infrastructure.
Meta, one of the largest cloud and data-center operators, intensified the selloff when it said it would issue a new class of shares to raise money for its projects. The move underscored how funding AI buildouts can dilute existing shareholders and pressure valuations.
The impact was uneven across hedge fund strategies. Goldman Sachs data showed tech-focused hedge funds were down roughly 10% and Asia-focused funds roughly 9% through October 22, reflecting losses in technology and China-related holdings as well as sharp moves in crowded short positions. Because many funds held similar AI-linked positions, losses in the same names hit numerous portfolios simultaneously. Traders told Reuters the drop triggered deleveraging, as lenders and risk teams requested additional cash or reduced exposure when prices fell.
TriVista Capital's Masaki Gotoh said the current AI trade looks uncomfortably concentrated, drawing a parallel to the late-1990s dotcom era. His concern centers on circular financing, in which public markets help fund larger AI spending through equity issuance, and that spending in turn supports the same AI-linked stocks many funds already own. When that loop is questioned, portfolios can move together as margin requirements rise and exposure is cut, turning separate stock stories into a single crowded trade and producing a correlated drawdown across hedge fund strategies.
Meta, one of the largest cloud and data-center operators, intensified the selloff when it said it would issue a new class of shares to raise money for its projects. The move underscored how funding AI buildouts can dilute existing shareholders and pressure valuations.
The impact was uneven across hedge fund strategies. Goldman Sachs data showed tech-focused hedge funds were down roughly 10% and Asia-focused funds roughly 9% through October 22, reflecting losses in technology and China-related holdings as well as sharp moves in crowded short positions. Because many funds held similar AI-linked positions, losses in the same names hit numerous portfolios simultaneously. Traders told Reuters the drop triggered deleveraging, as lenders and risk teams requested additional cash or reduced exposure when prices fell.
TriVista Capital's Masaki Gotoh said the current AI trade looks uncomfortably concentrated, drawing a parallel to the late-1990s dotcom era. His concern centers on circular financing, in which public markets help fund larger AI spending through equity issuance, and that spending in turn supports the same AI-linked stocks many funds already own. When that loop is questioned, portfolios can move together as margin requirements rise and exposure is cut, turning separate stock stories into a single crowded trade and producing a correlated drawdown across hedge fund strategies.
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