Investment Radar: Don't Panic Over Taiwan Stock Plunge, Look at Long-Term AI Trends Instead

Due to heightened concerns over AI financing and simultaneous corrections in global tech stocks, Taiwan's stock market has experienced significant short-term volatility. The market is worried that tech giants are expanding capital expenditures, squeezing free cash flow, and spreading credit risk from AI companies to the supply chain and bond market. However, increased credit risk does not mean AI demand has disappeared, nor can it be directly inferred that the AI construction cycle has ended. To judge whether long-term trends have reversed, one should return to corporate profits, policy directions, and supply chain demand.

1. AI Construction Faces Capital Test Taiwan's stock market plunge was primarily influenced by simultaneous corrections in global tech and semiconductor stocks. This selling pressure is not due to a sudden disappearance of AI demand but rather reflects industry development bottlenecks shifting from chips, power, and land to capital. Recently, it has been reported that NVIDIA may provide approximately $250 billion in financing guarantees for OpenAI's large data centers and discuss providing financing for chip purchases worth up to $350 billion. Such arrangements can help customers overcome the construction threshold of AI factories but will also transfer part of the credit risk originally borne by model companies to chip suppliers and the entire financing chain. As a result, the bond market has begun to worry whether companies can afford the increasing interest and capital expenditures if the cash flow generated by AI services falls short of expectations. Observing the change in the proportion of Duration Times Spread (DTS), the risk contribution of super-large-scale cloud providers and broad AI investment-grade bonds to the U.S. corporate bond market has rapidly increased and has already surpassed the six largest U.S. banks. This does not mean that tech giants are about to default, but rather that after AI companies issue a large number of long-term bonds, they become more sensitive to changes in interest rates and credit spreads.

Data Source: Bloomberg, "Capital Securities Fund" compilation. Data Date: 2015/12/31 to 2026/7/23. The numbers in the chart represent the proportion of various corporate bonds in the overall U.S. investment-grade corporate bond market's DTS. DTS (Duration Times Spread) is an investment portfolio risk indicator that simultaneously considers credit spreads and bond duration; the higher the proportion, the greater the impact of that type of bond on the risk and return of the corporate bond index, not equivalent to the actual default probability of the enterprise. Broad AI-related investment-grade bonds include memory, network communication, super-large-scale cloud providers, and other AI-related companies.

2. Corporate Earnings Still Supportive, AI Becomes U.S. National Strategy Whether the market decline will evolve into a long-term bear market depends on whether corporate profits and industry demand reverse simultaneously. Since the third quarter of 2023, S&P 500 corporate earnings have resumed positive growth and have grown for multiple consecutive quarters; in the first quarter of 2026, earnings increased by 28.8% year-over-year; as of July 24, the second quarter blended earnings growth rate further reached 37.9%. This shows that corporate profits are still maintaining normalcy, and the market correction mainly reflects the rapid pace of AI capital expenditures, rising financing costs, and extended investment recovery periods, rather than a deterioration in overall fundamentals.

More importantly, AI has risen from corporate-level technology investment to a strategic industry concerning U.S. economic growth, technological dominance, and national security. U.S. Treasury Secretary Janet Yellen recently pointed out that AI infrastructure is crucial for the economy and national security, and the U.S.'s leading position in global computing power constitutes an important national advantage, reflecting that maintaining AI leadership has become a clear policy direction. Facing the enormous construction funds needed for data centers, power, and chips, the U.S. government can still reduce the investment threshold of infrastructure through policy resources and public-private cooperation. Therefore, at this stage, the increase in credit risk mainly reflects the market beginning to raise the requirements for financial discipline, which is not sufficient to determine that U.S. AI capital expenditures or the long-term construction cycle have reversed.

Data Source: FactSet Earnings Insight, "Capital Securities Fund" compilation. Data Date: 2026/7/24. The 2026 second-quarter earnings growth is FactSet's blended value, combining the actual earnings of 27% of companies that have been announced with the consensus estimates of the remaining companies.

3. Short-Term Plunge Does Not Equal Trend Reversal, Avoid Panic Selling For a long-term upward market, the biggest risk for investors is not experiencing short-term declines but panicking and exiting the market before being able to return in time. The chart below shows a backtest of the S&P 500, where the cumulative return rate for staying in the market reaches 333.4%; if converting to cash when VIX is above 33, the cumulative return rate drops to 204.2%; if converting to cash when VIX is above 20, the cumulative return rate is only 105.4%. The reason is that timing using VIX requires simultaneously judging when to sell and when to buy back; market gains often concentrate on a few trading days, and these big up days frequently follow sharp declines. Even if some declines are successfully avoided, missing key rebounds can still significantly lag long-term compounded returns.

The long-term upward foundation of Taiwan stocks comes from Taiwan's key position in the global AI supply chain. Continuous expansion of AI capital expenditures by U.S. cloud providers and governments around the world will ultimately translate into demand for advanced chips, advanced packaging, AI servers, network communication equipment, and key components, which are areas where Taiwanese companies have advantages. Currently, the market is re-evaluating the financing methods and investment recovery periods of AI construction, but there is no sign of a long-term reversal in global computing power construction or supply chain orders. Therefore, as long as the direction of AI capital expenditures and Taiwan's supply chain competitiveness do not change, maintaining reasonable allocation and continuing to hold is usually more beneficial than repeatedly guessing market highs and lows.

Data Source: Bloomberg, "Capital Securities Fund" compilation. Data Period: 2015/01/01-2026/07/24. Using the S&P 500 total return index and VIX closing values for backtesting, daily decisions are made based on the "previous trading day's VIX": convert to cash if above the threshold, otherwise hold stocks. The "extreme VIX" threshold is 33, and the "high VIX" threshold is 20, fixed throughout the period. Investors entering at different times will have different investment performance, and past performance does not guarantee future performance.

Capital Investment Strategy This correction reflects that the AI industry has entered a more stringent financial verification period. Investors need to pay attention to corporate debt, free cash flow, and capital expenditure returns but do not need to exit entirely due to short-term credit market volatility. In the long term, AI has been viewed by the U.S. as a key industry concerning economic competitiveness and national security, and government and private capital will continue to promote the construction of computing power, energy, and data centers; Taiwan holds advanced processes, advanced packaging, AI servers, network communication, and key components, and its position in the global AI supply chain has not changed. For investors who are optimistic about the long-term development of AI, they can consider using Capital Securities Fund's "Super Bottom King" regular savings plan to disperse the risk of a single entry point through disciplined investment and adjust the weight according to their own risk attributes, investment period, and asset allocation.

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