Chip stocks lead the decline in U.S. stocks, is AI trading being double-hit by interest rates and returns?

Headline: Chip Stocks Lead US Stocks Lower, Is AI Trading Being Hit by Both Interest Rates and Returns?

Author: Rhythm BlockBeats

Source:

Repost: Mars Finance

According to AP reports, on June 23, U.S. tech stocks and AI-related sectors collectively declined, with the Nasdaq down 2.2% and the S&P 500 falling 1.4%. This pullback is not due to issues with a single chip company, but rather the most crowded AI hardware trades of the past year facing two types of pressure simultaneously. One is the sudden rise in Federal Reserve rate hike expectations, and the other is investors questioning when the AI capital expenditures by cloud providers, which have been continuously increasing, will translate into sufficiently clear profits.

The most direct pressure falls on the hardware supply chain. Market data shows that Nvidia (NVDA) dropped about 4% on Tuesday, with its market cap falling below $5 trillion. Micron plunged 13.2%, Qualcomm fell about 8%, and SanDisk and Western Digital also declined significantly. Memory, storage, AI chips, and mobile phone chips all weakened together, indicating that the sell-off is not limited to a specific niche.

Asian markets also came under pressure simultaneously. The Korea KOSPI index fell nearly 10% on June 23, with SK Hynix and Samsung Electronics both recording double-digit declines. Over the past few months, HBM and storage chip supply shortages have supported Korean tech stocks, but this time, the market chose to realize profits first.

The first to be sold off was the AI hardware chain

The sequence of this decline is quite indicative. Investors did not retreat first from software or internet platforms but instead targeted the chip and memory stocks that had benefited most from AI capital expenditure.

Nvidia remains the core target of the AI boom. Its GPUs have almost defined this round of data center expansion cycles and have become the market’s most concentrated risk preference outlet. While its market cap falling below $5 trillion does not change the company's industry position, it is a notable price signal from a trading perspective. When interest rates and return cycles are both being questioned, the assets with the largest gains and most crowded positions tend to be sold first.

Micron’s decline was even larger, partly due to upcoming earnings reports. The company announced that it will release its Q3 FY2026 results and hold an earnings call on June 24. The market had previously bet that AI servers would drive sustained high bandwidth memory demand. If guidance is not strong enough, investors worry that the previous gains lack new earnings catalysts; even if guidance is robust, they need to see proof that high-priced memory and AI demand are not just short-term rushes.

The reaction in the Korean market further amplified these concerns. SK Hynix and Samsung, key players in the global storage and HBM supply chain, both experienced double-digit declines, indicating that this correction has spread from U.S. tech giants to the global AI hardware supply chain.

Earlier, Broadcom’s AI revenue guidance did not meet the most optimistic expectations, triggering a round of chip stock sell-offs. Tuesday’s market movements seem to be a concentrated release of such worries. AI demand is still present, but the market is no longer willing to pay increasingly high prices just for a “big future.”

Rate hike expectations turn hawkish, putting pressure on high-valuation tech stocks

The macro trigger comes from changes in Federal Reserve policy expectations.

The Federal Reserve announced that Kevin Warsh was sworn in as Fed Chair on May 22. Reuters cites forecasts from U.S. banks suggesting the Fed may raise interest rates by 25 basis points in September, October, and December 2026, totaling a 75 basis point increase for the year. Reasons include resilient labor markets and persistent inflation pressures that have not fully subsided.

This is especially unfriendly to tech stocks. Valuations of AI leaders rely on long-term growth expectations, and rising interest rates increase the discounting of future cash flows, making low-risk assets like U.S. Treasuries more attractive again. Recently, U.S. Treasury yields have remained high, and futures markets have significantly increased bets on rate hikes within the year, indicating that market expectations for policy paths are rapidly adjusting.

The market is not suddenly doubting AI’s existence but is recalculating a more realistic question. If capital costs are higher and future profits are more distant, how much are investors willing to pay now for AI assets?

This is also why the correction in chip, memory, and high-growth tech stocks has been so synchronized. They previously benefited together from the combination of “AI demand continuing to explode” and “interest rates eventually declining.” Once one pillar weakens, the most inflated and highest valuation parts are the first to come under pressure.

Cloud providers are still spending, but investors are beginning to question returns

Another source of pressure comes from AI capital expenditures themselves.

Giant cloud and AI investors like Alphabet, Amazon, and Meta are still maintaining high-intensity data center construction. Over the past year, such spending has been viewed by the market as a demand guarantee for Nvidia, storage chips, power equipment, and data center assets. As long as cloud providers keep spending, the hardware supply chain will generate revenue.

But now the question is, will these investments ultimately pay off?

Training and inference of AI models require enormous computing power, electricity, and server investments. Cloud providers can monetize through enterprise clients, advertising tools, developer platforms, and consumer subscriptions, but whether service pricing can cover capital expenditures has not been fully proven. The market is beginning to scrutinize AI product prices, customer usage intensity, and whether companies are willing to pay high costs for generative AI over the long term.

This is also why “selling out heavy spenders” trades are becoming popular. Investors are not only selling chip stocks but are also becoming more cautious about those internet and cloud giants that continue to increase AI budgets. The more aggressive the spending, the more likely they are to be questioned on profit margins and free cash flow.

Volatility in high-valuation assets is also amplifying this sentiment. According to Axios, SpaceX’s stock price fell over 16% on its IPO Monday, erasing about $400 billion in market value. While not the main cause of this round of chip stock declines, it indicates that high-story, high-valuation assets are facing more rigorous market scrutiny.

The bubble has not burst yet, but Micron and inflation data will provide answers

This correction is more accurately described as a concentrated pullback after a huge rally in AI trading, rather than a confirmed bubble burst.

AI hardware demand still exists, and cloud provider capital expenditures have not stopped. The fundamentals of companies like Nvidia, Micron, and SK Hynix remain closely tied to data center construction, HBM supply, and AI server shipments. The real question is whether current stock prices have already priced in too many positive news.

The first validation point is Micron’s earnings report. The market will focus on three things: whether AI-driven server memory demand remains strong, whether price increases can be sustained, and whether management’s guidance for upcoming quarters is sufficient to support previous gains. If earnings are strong, the chip supply chain may get some relief; if guidance falls short, the sell-off could spread to more AI supply chain companies.

The second validation point is interest rates. Whether the Fed, under Warsh’s leadership, will actually start raising rates from September depends on inflation, employment, and energy prices. If inflationary pressures remain stubborn, growth stock valuations will continue to be pressured; if data cools, markets may reprice policy shifts, allowing tech stocks to recover.

The current market divergence lies in whether this is just a normal profit-taking in the AI bull market or the beginning of investors shifting from “buying only growth” to “needing to see returns.” Tuesday’s decline at least shows that the AI narrative remains strong but can no longer alone offset the pressure from higher interest rates and longer profit realization periods.