Semiconductor Fund Outflows Rotate into Gold and Financial Stocks
Claire Weston
Bloomberg strategist Simon White argues that roughly $17 billion in retail money is rotating back from chip stocks into gold and bitcoin, while a structural shift toward asset-light financials signals the market is repricing its confidence in the AI narrative against harder economic realities.
Where is the $17 billion coming from — and going?
U.S.-listed gold and bitcoin ETFs have seen cumulative net outflows of roughly $17 billion this year — closely matching the net inflows into semiconductor ETFs over the same period.
This means → the retail money that previously left gold and bitcoin for chip stocks now has a motive to reverse course.
Gold is already about 25% off its highs; some investors appear to be rotating back in, trying to recoup chip-stock losses.
If not chips, which sectors are catching the flows?
Over the past month, S&P sector SPDR ETF data shows financials attracted the largest net inflows, followed by healthcare and utilities.
The common thread: all three sectors have relatively low exposure to the AI theme.
In plain terms = money is leaving the sectors most saturated with AI narrative and moving into industries that can earn without it.
Within financials, who wins and who loses?
The leaders are asset-light names: PayPal (reportedly in a joint takeover bid), Global Payments, and S&P Global.
Capital-markets-heavy firms were dragged down by chip-sector turbulence: Robinhood is flat over the past month, while Morgan Stanley, Interactive Brokers, and Citi all declined — Apollo Global Management fell the most, down 11%.
This reflects a clear dividing line: the more a financial firm depends on trading volumes and capital-markets sentiment, the more exposed it is to semiconductor contagion.
What real-world pressure test is the AI narrative about to face?
White warns the current memory cycle's structural significance is about to be tested by harder realities — rising mortgage rates, a slowing property market, tightening credit, and falling demand.
This means → no matter how high AI expectations run, the technology's trajectory is still constrained by the basic economic cycle; the narrative cannot operate independently of macro reality.
White also flags latent risk exposure in private credit; where money ultimately flows will, in part, price the market's verdict on whether AI can deliver.
Content is for reference only, not financial advice.