According to Financial Times News, Asian markets are showing alarming concentration in AI-related stocks, with just six technology companies accounting for 50% of Hong Kong’s Hang Seng index returns this year. The analysis reveals that Alibaba, Xiaomi, and Kuaishou are among the key drivers, while in South Korea, only two stocks represent 40% of index returns. Taiwan’s market shows even greater concentration, with TSMC alone responsible for over half of Taiex gains year-to-date. The situation mirrors US markets where the “Magnificent Seven” tech stocks drove 42% of S&P 500 returns in early 2025, raising concerns that Asia’s AI dependency could lead to significant market vulnerability if US tech sentiment turns negative.
The Dangers of Extreme Market Concentration
What we’re witnessing in Asian markets represents one of the most concentrated equity environments in modern history. When just six stocks can drive half of an entire national index’s performance, we’re looking at systemic risk that extends far beyond typical sector rotation. Historical precedent isn’t encouraging – similar concentration patterns preceded both the dot-com bubble and the 2008 financial crisis, though the underlying drivers differ. The critical question isn’t whether AI represents real technological advancement, but whether current market structures can withstand the inevitable volatility that comes with such narrow leadership. Unlike previous bubbles where retail investors drove irrational exuberance, today’s concentration reflects institutional herding into a handful of perceived winners, potentially creating even more correlated risk.
The Troubling Valuation Disconnect
The valuation metrics highlighted in the Financial Times report reveal something deeply concerning about market psychology. Chinese chipmaker Cambricon trading at 506 times earnings while industry leader Nvidia sits at 57.7 times suggests either extraordinary growth expectations or complete detachment from fundamental analysis. This isn’t just premium pricing for quality assets – it’s pricing perfection into stocks with unproven commercial scalability. The semiconductor industry has always been cyclical, and while AI represents a structural shift, it doesn’t eliminate the inherent volatility of chip manufacturing and inventory cycles. When investors start justifying 200-500 P/E ratios with “exponential growth” narratives, we’ve entered territory where any earnings disappointment could trigger catastrophic revaluation.
Is This Time Really Different?
Proponents argue we’re witnessing a “supercycle” driven by fundamental demand for AI infrastructure, and there’s truth to this perspective. The computational requirements for training advanced AI models represent a step-function increase in demand that could sustain chip manufacturers for years. However, markets have a tendency to overestimate both the timing and magnitude of technological shifts. The mobile revolution was equally transformative, yet many early leaders failed to capture lasting value. The critical risk lies in assuming that current AI infrastructure demand will continue growing linearly when we’re already seeing efficiency improvements that could reduce computational requirements over time.
The Geopolitical Wild Card
What the analysis underemphasizes is how geopolitical tensions fundamentally alter the risk calculus for Asian tech stocks. US export controls on advanced semiconductors and manufacturing equipment create both artificial scarcity and dependency risks that don’t exist in other sectors. Companies like TSMC find themselves in the uncomfortable position of being indispensable to both Chinese and American tech ecosystems while navigating increasingly complex regulatory environments. This creates a scenario where political decisions could have immediate, dramatic impacts on valuations that have nothing to do with underlying business performance. The concentration risk becomes even more dangerous when combined with geopolitical uncertainty.
Navigating the AI Investment Landscape
For investors, the current environment requires distinguishing between companies building durable AI infrastructure and those simply riding the narrative wave. The foundational players like TSMC with reasonable valuations and proven technology likely represent safer exposure, while speculative Chinese chipmakers trading at extreme multiples warrant extreme caution. The broader lesson from market history is that technological revolutions create enormous wealth but also spectacular busts when expectations outpace reality. Diversification remains the investor’s best defense against concentration risk, even in what appears to be a transformative technological moment.
