
TSMC, the world's largest chipmaker, announced record earnings and committed a fresh $100 billion(約16兆円) to US chip manufacturing, yet its stock fell and chip stocks globally tumbled on Thursday. The selloff reflects growing investor anxiety that AI spending growth no longer justifies valuations seen as stretched, with market sentiment shifting from pricing growth to demanding perfection in execution.
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TSMC, the world's largest chipmaker, reported record earnings and announced a fresh $100 billion(約16兆円) investment for US chip manufacturing facilities. However, its stock fell after the announcement, and chip stocks globally declined sharply on Thursday, pulling broader markets down with them.
Why it matters
Investors are increasingly concerned that AI spending growth may not justify current valuations. An investment executive noted the AI sector is now "being priced on perfection" rather than growth, signaling that the market expects flawless execution going forward—a high bar that is making even strong fundamentals like TSMC's investment insufficient to restore confidence.
What to watch
Chip stocks have shown "meaningful cracks" in recent weeks according to analysts, and a failure to rebound strongly soon could trigger broader market warning signals. TSMC's $100 billion(約16兆円) US investment commitment underscores the scale of capital being deployed in the sector.
TSMC announced record earnings Thursday alongside a fresh $100 billion(約16兆円) commitment to building chip fabrication facilities in the United States. The investment would ordinarily be viewed as powerful confirmation that demand for advanced semiconductors—particularly for AI applications—remains robust. Yet the market reacted the opposite way: TSMC's own stock declined following the announcement, and the weakness cascaded globally, pulling down chip equities across the board and dragging broader market indices lower. The disconnect between strong fundamentals and falling prices reflects a narrowing investor appetite for semiconductor exposure, despite record profitability. An investment executive captured the underlying sentiment, telling The Wall Street Journal that "the AI trade isn't being priced on growth anymore. It's being priced on perfection." This signals a dramatic tightening of expectations: the market no longer rewards companies for meeting or even exceeding growth assumptions; instead, any hint that future results might fall short of the most optimistic scenarios triggers selling. Analysts have noted that chip stocks have displayed "meaningful cracks" in recent weeks and warned these declines "will raise some real warning flags" unless a strong rebound materializes soon. The selloff reflects broader concern about whether elevated valuations remain justified given uncertainty over the true scale and durability of AI capital expenditures. TSMC's $100 billion(約16兆円) US investment, though strategically sound and demand-driven, appears to have spooked rather than reassured investors fearful of stretched valuations in a sector now priced for flawless execution.
The Thursday selloff reveals a critical shift in how the market is valuing the semiconductor and AI sectors. TSMC's announcement of a record-breaking $100 billion(約16兆円) investment in US fabs would normally be viewed as bullish evidence of sustained demand, yet it failed to stabilize prices—and in fact preceded sharp declines. This disconnect points to a deeper concern: the market has moved beyond evaluating AI spending on its merits and is now demanding near-flawless execution. Investors are fearful that current valuations assume everything will go perfectly, leaving no room for any disappointment. The "meaningful cracks" analysts have observed in chip stocks over recent weeks, coupled with warnings that a rebound failure could trigger "real warning flags," suggest this is not isolated profit-taking but a fundamental repricing of risk in the sector. Even a company as dominant and well-capitalized as TSMC could not reverse the mood, indicating the issue is not confidence in any single player but rather skepticism about whether the entire AI capex cycle has been overestimated.
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