Nasdaq falls 3.4% as concerns grow over AI costs and returns
Key Facts
The Nasdaq Composite fell 3.4% at 2:15 p.m. Eastern time on October 30, leading losses in U.S. stocks, while the S&P 500 fell 2.2%, according to The Associated Press. The sell-off came amid investor concern that the AI investment frenzy had driven stock prices to levels beyond what results justified. Reuters reported that Amazon’s plans for heavy AI spending and Intel’s warning about cash burn added to concerns over the cost of building infrastructure and how long it would take to generate returns. Questions have thus shifted from the scale of spending to companies’ ability to demonstrate its payoff. The Nasdaq was at risk of ending a two-month streak of monthly gains, while the three major U.S. indexes were heading for weekly losses.
The pressure spread to chip stocks, with Intel down about 29%, on track for its biggest one-day decline, according to Reuters. Nvidia fell 3.7%, while AMD dropped about 10%, and the broader semiconductor index fell 7%. The moves reflected growing concern that expanding data centers and AI-related spending could raise costs before the pace of returns becomes clear. Losses among companies directly tied to chips also made the sell-off broader than a simple reassessment of major technology stocks. The pressure was not confined to one sector, with the S&P 500’s decline pointing to a wider retreat across the U.S. market.
A portfolio manager, describing the shift in investors’ view of the sector, said the market was “moving from the hopes-and-dreams phase of the AI trade to: show us the results.” The assessment comes as companies’ capital spending on the infrastructure needed to develop and operate these technologies rises, while markets focus on when the investments might begin to generate returns. The Associated Press linked the sell-off to concerns that investment enthusiasm had pushed stock prices too high. Reuters’ reporting on Amazon’s plans and Intel’s warning reinforces those concerns from the perspectives of cost and financing. Companies’ ability to turn spending into measurable results has therefore become a central factor in the market’s assessment of the sector.
Against this market backdrop, the Federal Reserve on October 28 kept the target range for the federal funds rate at 3.75% to 4%, according to the central bank’s statement. Two members of the monetary policy committee voted to raise the range by a quarter of a percentage point, dissenting from the decision to leave it unchanged. The decision came as compensation costs for civilian workers rose 0.8% in the three months ended in September, on a seasonally adjusted basis, according to the Bureau of Labor Statistics. Wages and salaries rose 0.7%, while benefit costs increased 0.9% over the same period. Year over year, compensation costs rose 3.4% in the 12 months ended in September, with wages up 3.1% and benefits up 3.9%.
In other asset markets, the yield on the 10-year U.S. Treasury fell to 4.92% on October 30, from 4.98% late in Thursday’s session, as investors turned to safer assets, according to The Associated Press. By contrast, Brent crude rose 2.4% to $113.50 a barrel. Oil’s gains kept price-related inflation concerns in focus alongside falling bond yields. The moves showed a divergence between demand for safe havens and the inflationary pressure accompanying the rise in crude. This coincided with technology stock losses and a broader decline in U.S. indexes.
Investors will next turn their attention to the Institute for Supply Management’s manufacturing purchasing managers’ index report, scheduled for release on November 2, according to the institute’s calendar. The report follows the sell-off, the release of September compensation-cost data and the Fed’s decision in late October. Its timing will provide another checkpoint for tracking economic developments after sharp market moves. No open source confirmed the forecast for the index reading included in the old draft, so no expected value is given here. In the coming days, attention will remain on manufacturing activity data and whether companies offer indicators that explain the costs and returns of their AI expansion.