European, Asian stocks tumble as AI rout rocks US markets

The selloff became a global retreat from technology and AI-related shares. US markets fell sharply overnight, Asia opened with even steeper losses, and European exchanges moved lower the next morning. Investors shifted toward bonds, viewed as safer assets, as political and financial uncertainty increased.

The Nasdaq dropped 5.5%, while $3 trillion was wiped from S&P 500 companies. Japan’s Nikkei fell 6%, its biggest one-day decline since April 2025. South Korea and Taiwan initially lost more than 8%. London’s FTSE fell 1.4%, Paris’s CAC dropped 1%, and Frankfurt’s DAX lost 1.3%.

Authorities then tried to calm markets. Taiwan’s index recovered somewhat but still closed 4.5% lower. South Korea temporarily eased rules on leveraged retail investing. The losses show how quickly concerns about US politics, AI spending, and financing conditions can cross borders and hit markets simultaneously.

The selloff was large across several major markets, but the figures differed by region and time period. The Nasdaq fell 5.5% overnight, while the Nikkei dropped 6% in Japan. South Korea and Taiwan each plunged more than 8% after opening, although both later recovered some ground.

Taiwan’s benchmark eventually closed 4.5% lower. Across the week, however, it lost 12.2%, the index’s biggest weekly decline since 1991, according to LSEG data. The falls also hit individual technology companies, including TSMC, Samsung Electronics, SK Hynix, Kioxia, and SoftBank Group.

The overall US loss was especially striking: $3 trillion was wiped from S&P 500 companies. These numbers show both the immediate shock and the accumulated damage. A single day produced dramatic falls, while the weekly figures revealed that investors had been retreating from AI-related shares for longer.

An AI-stock rout means a rapid, broad decline in shares associated with artificial intelligence. It matters because these companies had helped drive a wider market rally. When investors lose confidence in that group, selling can spread to chipmakers, cloud providers, technology firms, and broader stock indexes.

The article links the rout to two worries. Investors feared Democrats’ victory would bring greater regulation and slow data-centre construction. They also questioned whether enormous spending on AI infrastructure would produce enough returns. CoreWeave, a heavily borrowed AI cloud provider, fell 10%, while its credit default swap spreads reached a record level.

The damage was not limited to the United States. Samsung Electronics and SK Hynix fell sharply in South Korea, while TSMC declined in Taiwan. The article says AI stock prices had been built on “rosy illusions.” As those expectations weakened, investors sold both major companies and more financially vulnerable businesses.

AI companies depend on large infrastructure projects, especially data centres, to expand computing capacity. If regulation slows or blocks new construction, companies may have less room to provide AI services. Investors therefore feared slower growth, fewer customers, and lower future profits.

The concern also involved costs imposed on local communities. The article reports growing local opposition to data centres and quotes Texas Governor-elect Gina Hinojosa saying the state would introduce protections for residents. Analysts said markets had not fully considered these community costs. Political scrutiny could make projects slower, more expensive, or harder to approve.

These fears arrived when investors were already questioning the returns on massive AI infrastructure spending. A political shift therefore reinforced an existing financial concern. The selloff shows that markets were reassessing whether today’s large investments would create enough future earnings to justify high AI stock prices.

A margin call happens when an investor who borrowed money to buy securities no longer has enough account value to support that loan. The broker or lender demands additional cash or assets. If the investor cannot meet the demand, positions may be sold to reduce the debt. This explanation uses the standard meaning of margin calls.

Falling prices make the problem worse. A leveraged investor loses not only on the shares but also against borrowed money. Forced sales then add supply to a falling market. Those sales can push prices lower, causing other investors to breach their requirements. The process can become a self-reinforcing cycle.

The article says the selloff caused client margin calls, complaints, and further liquidation. South Korea temporarily eased rules on retail investors’ leveraged investments as authorities tried to calm markets. Analysts believed margin-account liquidation might represent the final stage of capitulation, though underlying concerns remained.

Financial markets are connected through investors, lenders, suppliers, and shared expectations. When major technology companies fall, investors may sell related shares, reduce borrowed positions, or move money into bonds. Losses in one market can therefore affect companies and indexes elsewhere, even when their businesses are not identical.

The article gives several examples. Samsung Electronics, SK Hynix, and TSMC fell sharply as investors reassessed AI demand. CoreWeave, an AI cloud provider, dropped 10%, while its five-year credit default swap spreads reached a record. SoftBank Group also fell 11%, and the cost of insuring against its default rose to a four-year high.

These moves show the spread from stocks into credit markets and across borders. Margin calls added forced selling, while retail investors and hedge funds became more nervous. Authorities in South Korea and Taiwan intervened to soothe markets. Continued weakness could expose smaller firms with limited access to funding.

Investors buy shares partly because they expect companies to generate profits in the future. Those expected profits help determine what a share seems worth today. If investors think future earnings will be larger, prices can rise. If they expect weaker earnings or greater risks, prices can fall. This is a general financial principle.

The article identifies several threats to those expectations. Higher interest rates and tighter financial conditions make borrowing harder, especially for smaller companies. Massive AI infrastructure spending raises questions about whether returns will justify the costs. Political risks, including regulation and opposition to data centres, could slow expansion or increase expenses.

When several risks appear together, investors may revise their forecasts quickly. That helps explain the sharp falls in AI shares and related markets. The article says the underlying questions cannot simply be erased, even if markets become temporarily oversold. Future performance will depend on whether AI companies can turn heavy investment into sustainable returns.