Global capital markets are experiencing a significant rally, reflecting renewed investor interest in technology stocks such as semiconductors. Market analysts believe technology hardware manufacturers are poised for sustained growth opportunities this year.
On May 6, following a strong surge in U.S. tech stocks the previous day, Asian markets saw a major uptick, with chip stocks leading the gains. South Korean listed company Samsung Electronics saw its shares surge 15% in early trading, pushing its market capitalization above the $1 trillion mark, making it the second Asian company after TSMC to achieve this milestone.
Technology stocks in the A-share market also rallied strongly. By the midday close, the SSE STAR 50 Index had surged over 9%, surpassing the peak level set in 2021. Chip stocks were among the top gainers. Montage Tech's Hong Kong shares (6809.HK) rose nearly 20%, while its A-shares (688008.SH) gained nearly 18%. Gigadevice's Hong Kong shares (3986.HK) rose over 16%, its A-shares (603986.SH) hit the daily upside limit, and ILUVATAR COREX (9903.HK) climbed over 12%.
Memory chips experienced a collective surge. Benefiting from a sharp increase in global demand for memory chips, South Korean chipmakers Samsung Electronics and SK Hynix also saw substantial share price increases, both rising over 10%, with Samsung's market capitalization breaking the $1 trillion barrier.
Samsung Electronics is the world's largest memory chip manufacturer. The company released strong earnings last month, with operating profit reaching 57.2 trillion won (approximately $39.2 billion) and revenue hitting a record high of 133.9 trillion won (approximately $90.8 billion).
Currently, Samsung and SK Hynix face intense competition in the High Bandwidth Memory (HBM) market. While SK Hynix holds an early advantage, Samsung is working to narrow the gap with SK Hynix in the rapidly growing AI memory sector.
Driven by the rise in tech stocks, South Korea's KOSPI index rose over 5% on the day, breaking through the 7,000-point mark for the first time.
Morningstar noted that strong demand related to AI infrastructure spending, coupled with supply constraints due to capacity limitations, is driving up prices for semiconductor chips and other input costs.
The previous day, propelled by factors including positive corporate earnings and rising AI demand, the U.S. Nasdaq index also hit a new high. Intel's stock price surged 13%, Super Micro Computer's stock rose 18%, AMD's stock gained 12%, and Micron Technology's stock increased over 11%, with its market capitalization surpassing $700 billion, entering the top ten largest U.S. tech stocks by market cap.
In European markets, one of the largest chipmakers, STMicroelectronics, also saw a significant share price increase this week following its earnings report. The company stated that it expects its semiconductor business to achieve a cumulative revenue target exceeding $30 billion between 2026 and 2028, with space chip-related revenue projected to reach nearly $1 billion this year.
AI benefits are spreading throughout the economy. The surge in global capital markets reflects renewed investor interest in technology stocks like semiconductors. Market analysts believe technology hardware manufacturers are set for continued growth opportunities this year.
Prominent U.S. financial commentator Jim Cramer stated on May 5 that the data center and AI boom is sweeping the globe and spreading to all corners of the market, with impacts extending far beyond tech companies. Cramer noted that corporate earnings reports show "explosive growth" in profits for companies related to AI and data centers, driving the market higher. He also suggested that an increasing number of stocks will benefit from this growth.
According to Q1 earnings reports from major U.S. tech giants, four leading tech firms—Google, Amazon, Microsoft, and Meta—plan to increase capital expenditure in the AI field to $725 billion by 2026, a 77% increase from the $410 billion planned for 2025, indicating the AI infrastructure race has intensified.
Cramer referenced the "five-layer cake" model proposed by NVIDIA CEO Jensen Huang to describe the AI economy. This theory posits that the AI economy consists of interconnected industries that all benefit from the same underlying architecture. The base layer is power, the foundation of the entire system. Above that are semiconductors, including memory chips and chip equipment manufacturers. The next layer comprises AI system hardware, such as servers, cooling technology, electrical equipment, networking, and suppliers of fiber optic cables connecting data centers. The fourth layer is the AI model layer, including cloud computing providers like Amazon AWS, Microsoft Azure, and Google Cloud. The top layer is the application layer, consisting of tools for direct interaction by consumers and businesses, including services like ChatGPT.
"A well-funded revolution has brought substantial profits to leading companies, and these gains are diffusing across nearly the entire economy," Cramer said.
Earlier this year, market participants debated the existence of an AI bubble, but optimism now prevails. Even conservative investor Warren Buffett has begun betting on AI, although his Berkshire Hathaway focuses more on "slow technology" within precise vertical applications of AI.
At this year's annual shareholders meeting, Berkshire Hathaway made several key observations. The company believes the commercialization path for general-purpose large models remains unclear, while the return on investment (ROI) for vertical applications is already quantifiable. Furthermore, the potential for intelligent transformation in the real economy is vast but requires specialized tools "embedded within the business." Technological sovereignty is considered more important than technological advancement; building systems in-house may be slower but offers control, iterative development, and the ability to create barriers.
Berkshire CEO Greg Abel stated at the meeting, "Everyone is talking about AI right now, but when it comes to applying it to our own businesses, each operation has specific opportunities. We do not advocate for generalized, boundless artificial general intelligence (AGI); we prefer narrow AI—we want intelligent tools embedded within the business that complement and synergize with our core operations." This indicates that AI is not a "free-for-all," and companies still need to hedge against potential "technology bubbles" in advance.
Comments