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 dependency extends across the region, with two stocks driving 40% of South Korea’s index performance and TSMC alone responsible for over half of Taiwan’s Taiex gains. Valuation extremes are particularly notable among Chinese chipmakers, with Cambricon Technologies trading at a price-to-earnings ratio of 506.2 compared to Nvidia’s 57.7 multiple. This concentration has investors warning that a potential US AI sector downturn could easily drag down Asian markets, with Société Générale’s Frank Benzimra noting “If you assume you have a bubble in the US then you have one in Asia.” Despite these concerns, some investors point to structural demand drivers and more reasonable broader valuations in Asian tech.
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The Concentration Risk Reality
What makes this concentration particularly concerning isn’t just the percentage figures, but the underlying market structure. When a handful of stocks drive half of an index’s performance, you’re looking at systemic risk that transcends individual company fundamentals. This isn’t merely about AI enthusiasm—it’s about market mechanics where passive investing and thematic funds amplify momentum effects. The situation creates a feedback loop where index-tracking funds must buy more of these stocks as they rise, further concentrating the market and creating vulnerability to sudden sentiment shifts. This dynamic played out during the dot-com bubble and again during the 2022 tech correction, and Asian markets appear to be setting up for a similar pattern.
Valuation Disparities Tell a Complex Story
The extreme valuation multiples for Chinese AI stocks like Cambricon (506x P/E) versus more established players like TSMC (24.7x) reveal a market bifurcation that’s often misunderstood. This isn’t simply about overvaluation—it’s about different growth expectations and risk premiums. Chinese semiconductor companies are trading on potential domestic substitution and government support narratives, while Taiwanese and Korean companies are valued on actual global market leadership and proven technology. The gap also reflects different investor bases, with domestic Chinese investors often having fewer alternatives for tech exposure and different return expectations than international institutional investors.
Structural Demand Versus Cyclical Hype
The critical question for investors is whether we’re witnessing a genuine structural shift in technology demand or another cyclical bubble. The argument for structural change is compelling: AI represents the most significant computing architecture shift in decades, requiring entirely new infrastructure from specialized chips to data centers to memory architecture. Companies like TSMC aren’t just riding a trend—they’re building the fundamental plumbing for the next generation of computing. However, even structural shifts can experience speculative excess, and the current concentration suggests we’re seeing both genuine transformation and speculative froth simultaneously.
Regional Differences in AI Exposure
Not all Asian AI exposure is created equal. Taiwan and South Korea’s concentration in semiconductor manufacturing represents a different risk profile than China’s focus on AI applications and domestic chip development. The former benefits from global demand and technological leadership, while the latter faces geopolitical headwinds and technological catch-up challenges. This distinction matters because a potential US AI slowdown would affect these markets differently—Taiwan and Korea might see demand delays, while Chinese companies face additional regulatory and technology access constraints that could compound any downturn.
Investment Implications and Risk Management
For investors navigating this landscape, the concentration risk demands sophisticated portfolio construction. Simply avoiding AI stocks means missing genuine structural growth, while overconcentrating creates bubble exposure. The solution lies in understanding the different layers of the AI value chain and diversifying across hardware, software, and enabling technologies. Companies building fundamental infrastructure like SK Hynix in memory or TSMC in manufacturing represent different risk profiles than application-focused companies trading on future AI revenue potential. The current market structure suggests that active management and selective exposure will be crucial as the AI investment theme matures.
Broader Market Impact Beyond Tech
The concentration in AI stocks creates spillover effects across Asian markets that extend far beyond the technology sector. As these stocks command increasing index weight, they drain capital from other sectors, potentially creating undervaluation opportunities in traditional industries. This dynamic also affects currency markets, corporate financing conditions, and even government policy decisions across the region. The risk isn’t just that AI stocks might correct—it’s that their current dominance distorts capital allocation across entire economies, potentially creating longer-term structural imbalances beyond the immediate bubble concerns.
