U.S. technology shares extended a broad decline this week as traders punished companies that missed expectations and sold others even after strong results, a sign that the market’s tolerance for high artificial intelligence valuations has narrowed sharply.
The pressure was most visible in chips, storage hardware, cloud infrastructure and other areas tied closely to AI spending. The Nasdaq Composite fell 1.5% on Thursday, led lower by semiconductor and data-storage names, while the broader weakness pointed to a deeper shift in market positioning rather than a simple reaction to earnings headlines.
The selloff has raised the stakes for both equity and digital-asset traders. Technology shares and major cryptocurrencies have increasingly traded as part of the same risk cycle during periods of stress, with Bitcoin and other large tokens often moving in the same direction as high-growth technology stocks when leverage is being reduced across markets.
The latest declines suggest that traders are no longer rewarding AI-linked companies simply for beating forecasts. Instead, they are questioning whether current valuations already assume years of rapid growth, heavy infrastructure spending and generous profit margins.
At the same time, leveraged funds, momentum strategies and options-driven positioning appear to be adding pressure. When crowded trades begin to reverse, selling can feed on itself as funds cut exposure, reduce borrowed money and close positions that had worked well during the earlier rally.
Strong numbers meet a tougher market
Taiwan Semiconductor Manufacturing Co. reported a 77% year-on-year increase in second-quarter net profit and lifted its 2026 revenue outlook to above 40%, yet its U.S.-listed shares still fell 2.3% on Thursday. The reaction showed how difficult it has become for leading AI hardware companies to satisfy market expectations after a long advance in share prices.
TSMC remains one of the most important companies in the global AI supply chain. Its advanced chips are central to data-center expansion, graphics processors and high-performance computing. In a calmer market, results of that scale would normally be enough to support the stock. This week, they were not.
The same pattern appeared across other hardware names. Recent quarterly reports from ASML, Micron and TSMC exceeded analyst projections, but their shares faced selling after the announcements. That reaction suggested that the earnings bar for the sector has moved exceptionally high.
For traders, the problem is not only whether companies are growing. It is whether their growth is strong enough to justify share prices that had already priced in a near-perfect outlook for AI demand.
IBM offered the opposite case. Its shares fell more than 20% on Tuesday after a profit warning, a one-day percentage drop that exceeded the decline the stock suffered during the 1987 crash. The size of that move showed how aggressively the market is punishing disappointment, particularly when companies fail to convince traders that profit growth can keep pace with spending needs.
Hardware names lead the retreat
Semiconductor and storage stocks took some of the heaviest losses. Western Digital, Seagate and SanDisk each dropped more than 9% on Thursday. Intel and Micron fell about 6%, extending a broader retreat across the chip complex.
The semiconductor sector has now fallen roughly 22% from its mid-June highs, putting it in a technical bear market. A decline of 20% or more from a recent peak is often viewed as a sign that sentiment has shifted from routine profit-taking to a more serious reassessment of future returns.
The selling has not been limited to weaker companies. It has reached firms that play central roles in AI infrastructure, data storage and advanced computing. That breadth matters because it suggests that traders are reducing exposure to the entire AI hardware theme, not merely rotating out of individual names.
Goldman Sachs data showed that AI-related segments such as optical networking, AI semiconductors and data-center components have each fallen between 5% and 12% over the past two sessions. Those are large moves for areas that had become central to the market’s growth narrative.
The sharp reversal also comes after months in which money flowed heavily into companies expected to benefit from AI adoption. When a trade becomes crowded, even good news can become a selling event because many traders already own the shares and need new buyers to push prices higher.
Momentum unwind amplifies the move
The weakness has been especially severe in momentum stocks, a group that includes many of the market’s strongest performers from earlier in the year. Goldman Sachs’ momentum stock index fell 6% in a single session and has lost about one-fifth of its market value this month.
The firm’s data showed that volatility in this group has risen to a five-year high. It is now around ten times the realized three-week volatility of the S&P 500. That gap signals unusually unstable trading in shares that had previously benefited from trend-following strategies.
Momentum strategies are vulnerable when leadership changes quickly. These trades often involve buying stocks that have been rising and selling those that have been falling. When the strongest names begin to drop, the same models that once supported the rally can accelerate the reversal.
The pressure can become more intense when leverage is involved. Funds using borrowed money may be forced to reduce exposure as volatility rises. Options positions can also add to the move when market makers adjust hedges during fast declines.
Strategists have said the drawdown remains linked to a system-wide deleveraging phase that began in June. JPMorgan strategist Nikolaos Panigirtzoglou has estimated that there is still room for further deleveraging across leveraged exchange-traded funds, options and margin accounts. He described those areas as continuing headwinds for U.S. equities.
That matters because deleveraging is not always tied to company fundamentals. A strong business can see its stock fall if traders are forced to raise cash or reduce risk. This is one reason strong earnings have failed to protect some of the market’s best-known technology names.
AI spending faces a longer-payback question
Alphabet and Amazon also declined as traders questioned the payoff timeline for heavy spending on data centers, cloud capacity and AI infrastructure. Alphabet fell 4.4%, while Amazon lost 1.2%.
The concern is not that demand for AI computing has disappeared. Rather, the market is asking how long it will take for the spending boom to produce returns large enough to support current valuations.
Building AI infrastructure is expensive. It requires chips, power, networking equipment, storage, real estate and engineering talent. For the largest cloud-service providers, capital spending has surged as they race to serve corporate demand for AI tools and computing capacity.
That spending has also affected credit markets. Corporate bonds issued by large cloud-service providers have come under pressure as debt loads rise in connection with AI expansion programs. Higher debt costs can complicate the market’s view of future profits, especially if revenue growth takes longer than expected to catch up with infrastructure spending.
In the equity market, traders have become more selective. Companies that can show immediate revenue growth and margin strength may hold up better. Those with less clear returns on AI spending may face more scrutiny.
The shift represents a more mature phase of the AI trade. Earlier rallies were driven by excitement about future adoption. The current market is demanding evidence that the spending cycle can convert into durable cash flow.
Why digital assets are exposed
The decline in technology shares carries a direct warning for digital-asset markets. During broad risk-off periods, major cryptocurrencies often behave less like havens and more like high-beta technology trades.
Bitcoin, Ethereum and other large tokens are not tied to corporate earnings, but they are highly sensitive to liquidity, leverage and risk appetite. When traders reduce exposure to speculative growth assets, digital assets can be sold alongside technology stocks.
Recent market behavior has shown that correlations between large cryptocurrencies and the Nasdaq can rise sharply during selloffs. Correlation is not stable, and it can weaken during calmer periods. But when markets are under stress, digital assets have frequently moved in line with the same forces pressuring expensive growth shares.
That makes leverage especially dangerous. Crypto traders using borrowed funds or derivatives face a higher risk of forced liquidation when prices move quickly. If U.S. technology stocks continue to fall, pressure can spill into token markets through margin calls, risk-model adjustments and the need to raise cash.
The key issue is liquidity. When liquidity is abundant, traders are often willing to pay higher prices for assets with long-term growth stories. When liquidity tightens, those same assets can reprice quickly. This applies to AI-linked equities, momentum stocks and cryptocurrencies.
For that reason, traders in digital assets should treat the technology selloff as a meaningful risk signal. A decline in AI hardware shares may not directly change the fundamental case for Bitcoin or Ethereum, but it can change the short-term trading environment. In leveraged markets, that difference matters.
Deleveraging is now the central risk
The broader market is not yet showing signs of outright panic. Cross-factor correlations remain unusually low, according to Goldman data, suggesting that the volatility is more connected to structural repricing than a full-scale rush for the exits.
That distinction is important. In a panic, almost everything tends to fall together as traders sell first and assess later. In the current move, losses are concentrated in crowded, AI-linked and momentum-heavy areas. That points to an unwind of specific trades rather than a complete breakdown in market function.
Still, broad stability has not returned. The speed of the decline has made risk management more difficult, particularly for traders who entered positions late in the rally or used leverage to increase exposure.
The fast fall in share prices suggests that large funds are pulling real cash out of hot technology themes. As volatility rises, the cost of holding leveraged risk also rises. That can push more traders to reduce positions, creating further pressure on prices.
This is why strong earnings have not been enough to stop the selling. The market is no longer focused only on whether a company beat quarterly estimates. It is also focused on whether too much money had already crowded into the same trade.
When positioning becomes the main driver, prices can move beyond what earnings alone would suggest. That creates sharp declines in high-quality companies and even sharper drops in weaker names.
What would calm the market
A more stable market would likely require several changes. Technology earnings would need to keep supporting the long-term AI growth story. Companies would need to show that spending on data centers and chips is translating into revenue, margins and cash generation. Volatility would also need to ease enough for leveraged traders to stop cutting exposure.
A lower level of bond-market pressure would help as well. If borrowing costs stabilize, markets may become more comfortable with large infrastructure spending plans. But if debt concerns continue to build, traders may demand lower valuations for companies funding rapid AI expansion.
For now, the market’s message is cautious. AI remains one of the most important growth themes in global markets, but enthusiasm is no longer enough. Traders are asking harder questions about price, timing and balance-sheet risk.
The same caution applies to digital assets. Major tokens may recover quickly if technology shares stabilize and liquidity improves. But if the deleveraging process continues, crypto markets could remain vulnerable to abrupt declines.
The current selloff does not mean the AI trend is over. It does mean the trade has entered a more demanding phase. Companies must deliver more than strong headlines, and traders must manage risk in a market that is no longer forgiving crowded positions.
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