Hedge Funds Dump AI Stocks and Cut Tech Exposure

Hedge funds have rapidly reversed their buying of AI stocks, selling in five consecutive sessions from 8 to 14 October and wiping out all their net purchases since the start of 2025. Goldman Sachs data show that over two weeks they cut about $20 billion in technology stocks, mainly by selling existing positions: they sold existing AI holdings 3.5 times faster than they opened new short positions. The retreat followed a broader reduction in risk exposure. Goldman said technology shares led equity outflows, while funds shifted towards healthcare and consumer staples. A Goldman-tracked basket of hedge-fund favourites fell 4.2% on 22 October, its biggest one-day drop since 2011. Separately, Morgan Stanley data cited by Steno Research showed hedge funds reduced overall equity exposure by about 7.8%, the largest decline in that series since 2016. Despite the sales, AI stocks still accounted for 26.1% of global single-stock net exposure, a high level by historical standards. Gross leverage remained near a five-year high even as net leverage fell sharply, and Goldman warned that further deleveraging could follow, particularly amid foreign outflows from Asian markets. For crypto traders, the hedge-fund retreat from AI stocks is a sign of weaker appetite for risk assets and could add to volatility across markets, including crypto, though the reports cite no direct cryptocurrency positions or price moves.
Bearish
The reports do not identify a specific cryptocurrency or provide direct crypto-market data, so any effect on crypto prices is indirect. Still, hedge funds’ broad retreat from AI and technology stocks, alongside a sharp cut in overall equity exposure, signals weaker risk appetite. In the short term, this kind of risk-off positioning can prompt traders to reduce exposure to volatile assets, potentially increasing selling pressure and price swings in crypto. Over the longer term, persistent deleveraging and outflows from risk assets could weigh on crypto sentiment, although the scale of any effect would depend on crypto-specific demand, liquidity and market conditions. The bearish classification reflects this potential spillover, not a confirmed move in any particular cryptocurrency.