Summary of Key Points
Recently, there has been a divergent correction in global AI-related technology stocks. Stocks in the chip sector and tech giants (the “Big Seven”) that had seen significant gains earlier have declined. However, funds have not completely withdrawn from the tech sector; instead, they have shifted from cloud service providers, which are “burning money without generating profits,” to hardware suppliers (such as semiconductor equipment and chips) that have demonstrated clear performance. The market focus has shifted from chasing hot trends to verifying actual earnings, with the second-quarter reports becoming a critical point of observation. Institutions recommend investors diversify their portfolios to mitigate volatility and maintain long-term attention to AI innovation and opportunities for domestic substitution.
Detailed Analysis
1. Global Tech Stocks Cool Down: Both AI Hardware and Giants Are Falling, but for Different Reasons
Global tech stocks have experienced a sharp decline recently: the Philadelphia Semiconductor Index fell more than 11% in two days, the Nasdaq dropped by nearly 2%, Meta Platforms lost almost 5%, and Nvidia also fell 1.39%. The Japanese and Korean stock markets were even worse, with the Korean Composite Index falling 3.84% in a week and experiencing a 7.89% plunge on Thursday, which triggered a circuit breaker; SK Hynix and Samsung Electronics both saw weekly declines of over 8%.
The core reason for these declines is a change in expectations: previously, investors were eager to buy into AI-related stocks regardless of whether the companies were profitable or not. Now, there is skepticism about whether tech giants like Microsoft and Meta Platforms will be able to recoup their investment costs given the substantial funds they have spent on AI. Goldman Sachs data shows that the four major giants’ capital expenditures are expected to increase by 77% to $725 billion in 2026, but there is still no clear answer as to when AI will become profitable. As a result, investors are selling these companies that are “burning money without returns,” and even the previously surging AI hardware stocks (such as storage and semiconductor equipment) are experiencing temporary corrections due to their high valuations.
2. Funds Are Not Leaving the Market; They Are Just Shifting Focus
Although tech stocks have declined, funds have not disappeared; they have simply shifted to other areas. Previously, investors were interested in cloud service providers (such as Microsoft building data centers and Meta Platforms training AI models), which require significant investments without immediate profit generation. Now, they are turning to hardware companies, such as those involved in chip manufacturing, semiconductor equipment, and optical communications.
Why? Because hardware companies can generate tangible profits more quickly. AI requires computing power, which in turn depends on chips, and these companies are already seeing orders and profits. For example, Chinese optical communication manufacturers saw growth in their first-quarter earnings due to the global demand for AI computing power last year. BlackRock’s statement that “some Chinese hardware assets have entered a period of performance realization” reflects this trend.
3. Earnings Become the Test Bench: The Second Quarter Reports Will Be Crucial
The market no longer focuses on hype but on actual earnings. BlackRock emphasizes that the second-quarter reports will be critical, especially for companies with high valuations. Two key indicators to watch are:
- Sustainable growth in operating cash flow: Not just book profits, but actual revenue from sales (e.g., payments from chip sales);
- Whether performance meets expectations: If company earnings fall short of expectations, stock prices may continue to decline.
JPMorgan Chase even warns that the current situation resembles the pre-1999 internet bubble; if tech giants cannot prove that AI investments are profitable, market sentiment could turn even more negative in the fall.
4. The Chinese Market Follows the Trend: Semiconductor Hardware Stocks Are Being Highly Demanded
The A-share market has also been affected, with the ChiNext Index falling by more than 6% on Thursday, the largest decline of the year so far. However, funds are quietly increasing their holdings in semiconductor stocks: this week, there was a net inflow of $7.1 billion into semiconductor chip ETFs and $3.4 billion into communication ETFs. In the first half of the year, broad-based ETFs saw a net outflow of $1.85 trillion, while eight semiconductor equipment ETFs had a net inflow of over $130 billion, with the Yifangda Semiconductor Equipment ETF increasing in size from $1.6 billion to $17.1 billion.
The reason is the significant potential for domestic substitution in China’s semiconductor equipment sector: many companies previously relied on imports, but now domestic wafer factories are expanding production, creating a demand for more domestically produced equipment. The market’s shift from chasing hot trends to focusing on actual performance aligns with global trends.
5. Institutional Advice: Diversify to Mitigate Volatility and Focus on Two Long-Term Trends
To cope with market volatility, institutions offer the following advice:
- Defensive Strategy: Morgan Asset Management recommends buying companies with high cash flows and generous dividends (such as those in traditional industries) as well as undervalued sectors like consumer goods and pharmaceuticals.
- Wait and See or Choose the Right Time: Guotai Fund suggests waiting until July, when performance will be verified, for investors with lower risk tolerance.
- Long-Term Trends: Nuoan Fund recommends two main areas of investment: AI innovation (domestic AI chips and specialized computing power chips) and manufacturing equipment and materials (domestic substitution of semiconductor equipment and materials).
- Risk Warnings: Barclays predicts that the semiconductor cycle may continue until the first half of 2027, but there could be an oversupply in 2028. UBS warns about potential risks related to AI companies’ cash flow if capital expenditures slow down.
In summary, AI investment has moved from a focus on hype to a focus on actual performance. Hardware companies, which can generate profits more quickly, have become more attractive, while tech giants that are burning money need to prove the profitability of their AI initiatives to stabilize their stock prices. Investors can follow these institutional recommendations and diversify their portfolios to avoid relying too heavily on any single sector.