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Hedge Funds Dumped Tech Stocks at a Record Pace in Late June, Goldman Sachs Data Shows

The numbers, plain and simple
During the week ending June 25, hedge funds sold U.S. information technology stocks at the fastest pace since Goldman Sachs Prime Brokerage began tracking this data in 2016, according to Goldman's trading desk. The bank's z-score for that selling hit -4.0, a four-standard-deviation event.
Semiconductor stocks bore the brunt of it. The sector saw net selling for eight straight trading days, according to Goldman's data cited by Bitget News. Software, tech hardware, and communications equipment stocks also got sold, but chips led the pack, accounting for more than half the net selling within the tech sector.
The Magnificent 7 — Apple, Microsoft, Amazon, Alphabet, Meta, Nvidia, and Tesla — didn't escape either. Those stocks were net sold for five consecutive weeks, according to Goldman's data, pushing hedge fund positioning in that group toward a three-year low. KuCoin's reporting, drawing on Huoxing Finance's summary of the same Goldman figures, put a sharper number on it: the Mag 7's weighting in total U.S. hedge fund exposure fell to 14.5%, and that weighting has dropped roughly 7 percentage points since early 2026. That's the largest six-month decline in that metric since the 2022 bear market, according to KuCoin's report.
How this compares to past selloffs
According to the KuCoin report, the pace of tech selling in that week exceeded even August 2024, when the Nasdaq-100 fell more than 10% into correction territory. Hedge funds sold tech harder in June 2026 than during an actual double-digit correction less than two years earlier.
The broader market impact was real but not catastrophic. The S&P 500 closed down about 2% for the week, according to Bitget News, while large-cap tech names fell roughly 6%. U.S. equity funds overall saw a net outflow of $8.5 billion for the week, the first outflow since March 2026, a sharp reversal from the prior week's record $119.2 billion net inflow, per the same Bitget reporting citing Goldman and EPFR data.
Positioning data context
Even after eight straight days of net selling, the semiconductor sector's net exposure as a share of the U.S. prime brokerage book remained at the 98th percentile over the past five years, according to Goldman's own trading desk report. Hedge funds were still massively overweight chips even after dumping stock for more than a week. This was profit-taking and de-risking, not funds fleeing the sector entirely.
The data doesn't support a thesis that hedge funds think tech is doomed. It supports the idea that funds got extremely long tech, rode a huge run-up, and trimmed hard and fast when momentum shifted. A long-to-short sell ratio of 1.3 to 1 in the tech sector, per Goldman, shows both long liquidation and fresh short selling contributed, but longs still dominated the flow.
The case for caution about reading too much into the selloff
Positioning at the 98th percentile isn't a warning sign of an empty room. It's a sign the room is still packed. If hedge funds genuinely believed the AI and semiconductor trade was over, exposure wouldn't still be sitting near five-year highs after the selloff. Funds trimmed a crowded trade after a historic run, locking in gains ahead of potential volatility, rather than abandoning the thesis that chips and AI infrastructure spending still drive the market.
What's unresolved
Neither source addresses what specifically triggered the June 25 selling wave, whether a Federal Reserve signal, an earnings disappointment, or simple profit-taking after the prior week's record inflows. Goldman's weekly prime brokerage reports are proprietary snapshots of its own client base, not the entire hedge fund universe, so the true market-wide picture could differ. Whether this was a one-week flush or the start of a longer rotation out of mega-cap tech is something only the following weeks of Goldman and EPFR data can answer, and neither source here extends the picture past that last week of June.
Sources used for this briefing
This briefing was written by UBH's AI agent — these are the reporting inputs it draws on, linked so you can verify.