Intel-led chip selloff wipes over $400 billion in a day as semiconductor rout hits $3.7 trillion

Chip stocks slide while the broader market climbs

US equities largely moved past last week's technology turbulence on Monday, but semiconductor companies sat out the recovery. According to Yahoo Finance, roughly seven in ten S&P 500 stocks closed higher, yet almost every chip stock finished lower, and the group lost more than $400 billion in market value in that single session by the outlet's calculations.

The session extends a slump that began in early October. Yahoo Finance estimates that chip and memory stocks have collectively shed about $3.7 trillion in market value since Oct. 6.

Intel's slide deepens

Intel took the heaviest blow once again. Its shares dropped roughly 9% on Monday, following Oct. 30, when a disappointing forecast produced the company's worst single day since 1974 and cut nearly 29% from the stock. Intel is now worth less than half of what it was at the end of September, which Yahoo Finance identifies as the steepest decline among the industry's giants, even though Nvidia has lost the most value in dollar terms.

Memory names and Marvell fall

The selling reached well beyond Intel. Micron, Sandisk, Seagate and Western Digital — the memory and storage companies that had powered this year's chip rally — each dropped between roughly 6% and 8%. Marvell fell harder still, on a day when it announced a deal to acquire Lumentum valued at $115 billion. Nvidia proved more resilient than peers but remains down about 16% since Oct. 6.

Not everything tied to AI declined. Yahoo Finance notes that SpaceX shares gained ground, though they remain well below where they started October, and software results were mixed. Cybersecurity firms such as Fortinet and CrowdStrike fell alongside the chipmakers.

Investors split on whether a bottom is in

Commentators quoted by Yahoo Finance disagree about what follows. Adam Johnson, founder of the Bullseye Brief and portfolio manager of the American Ingenuity Fund, argues the selloff has already absorbed the bad news. "They discounted everything that could go wrong. And when you do that, typically that's when you see a bottom," he told the outlet.

John Chambers, the former Cisco CEO who now runs JC2 Ventures, expects the gap between winners and losers to keep widening. "There will be major train wrecks," he said, adding that a rising tide "does not raise all boats" and that he would not bet against Nvidia.

Jeff Hirsch, editor of the Stock Trader's Almanac and the man who coined the term "Octoberphobia," told Yahoo Finance he bought the selloff on Oct. 30. History supports him: chips have climbed in all eight US midterm cycles since 1994, measured from the final October close through the following June, according to Yahoo Finance's calculations. The caveat is that in 2002 and 2018 they first dropped another 11% or so before turning around.

AMD reports next

The sector's next test comes Tuesday after the closing bell, when AMD publishes its third-quarter results on the same day as the US midterm vote. The report will give investors a fresh reading on demand across the industry at a moment when confidence in the AI hardware trade is under strain.

Why it matters

A $3.7 trillion wipeout concentrated in semiconductors is not a routine correction; it is a repricing of the layer of the technology stack that AI and cloud infrastructure are built on. The fact that chips fell while most of the broader market rose signals a rotation away from the AI hardware trade rather than general risk aversion, and the leadership of memory and storage names in the decline points to doubts about the durability of datacenter buildout spending. Intel's halving in about a month raises questions about its competitive position, while the divergence Nvidia is showing against peers will shape how investors judge the entire supply chain. With AMD's earnings landing on Election Day, the sector faces its next major catalyst amid already fragile sentiment, and the outcome will ripple through cloud capex plans, supplier pipelines and the wider AI ecosystem that depends on these components.