The stock correction affecting AI-related stocks accelerated abruptly on Thursday, November 5. The Nasdaq 100 fell by 6.4%, wiping out about $2.5 trillion in market capitalization in a single session. Nvidia slid 9%, AMD 17%, and the US semiconductor index 12%. This move does not mean that $2.5 trillion of liquidity vanished: it measures the decline in the market’s valuation of these companies.
A extraordinary session
Nasdaq 100: −6.4%, about $2.5 trillion of market capitalization erased.
Nasdaq Composite: −5.52%.
S&P 500: −4.36%.
Nvidia: −9% ; AMD: −17%.
Semiconductor index: −12%, its lowest level in more than six months.
Why AI stocks fell
Several factors have added up. Investors have been wondering for several weeks about the extraordinary level of investment in data centers, processors, networks, and electricity required for artificial intelligence.
Results from large technology groups show still-strong growth in cloud and AI activities, but also sizable investment outlays. The market is now trying to determine how quickly these sums will translate into revenue, margins, and cash flow.
The American elections added a new uncertainty
The Democrats’ victory in both chambers of Congress has also weighed on the sector. Markets anticipate tighter scrutiny of certain data-center projects, especially regarding their electricity and water usage and their consequences for local grids.
This political dimension does not alone explain the drop, but it added regulatory uncertainty to valuations that were already high.
Nvidia and AMD among the steepest declines
Semiconductor manufacturers were hit particularly hard. Nvidia fell 9% and AMD 17%. The Philadelphia Semiconductor Index dropped 12%, hitting its lowest level in more than six months.
Companies specializing in financing and operating computing capacity also declined. CoreWeave lost around 10%, while the cost of its credit-default insurance reached a record level.
Cloud giants were not spared
Amazon and Alphabet each fell about 2.2%. These groups have diversified businesses and substantial cash flows, but also rank among the world’s leading investors in AI infrastructure.
The stock market debate is gradually shifting: the question is no longer only whether demand for artificial intelligence will grow, but how much must be invested to service it and what return those investments can generate.
A market that has become very concentrated
The dramatic rise in technology equities since 2023 has increased the weight of a few large companies in U.S. indices. When an investor reduces exposure to AI, selling can therefore simultaneously affect chipmakers, cloud operators, data-center builders, electricity suppliers, and software companies.
This concentration partly explains the speed of Thursday’s moves.
Volatility has risen sharply
The VIX index, often described as Wall Street’s fear gauge, rose to 28.36 points, its highest level in eight months. Its intraday move was the largest in more than eighteen months.
Reuters also reported that certain automated strategies and some levered funds had to trim their positions, which could have amplified the decline.
2.5 trillion “lost”: what this figure really means
A decline in market capitalization does not correspond to an equivalent destruction of liquidity. A company’s market capitalization results from the price of its last share multiplied by the total number of shares. When the price falls, the theoretical value of the entire company falls mechanically.
The figure of $2.5 trillion thus measures the scale of the market’s reevaluation in a single day, but does not represent a sum of money taken directly out of the companies’ accounts.
A challenge to AI? Not at this stage
The correction alone cannot conclude that the AI investment cycle is over or that a bubble is bursting. Banks and analysts continue to view some valuations as attractive again after recent declines.
The market signal is more precise: after rewarding AI spending growth for a long time, investors now demand more visibility into profitability, financing, and the timing of return on investment.
