According to analysis, Simon Webber, Global Head of Equities at Schroders Investment, points out that when assessing the long-term growth prospects of truly exceptional companies, investors generally fail to look far enough ahead. They often assume that a company's competitive advantages and growth pace will only gradually diminish, overlooking the remarkable compound growth capability of well-managed, high-quality franchise businesses with entrenched competitive advantages. These types of enterprises can successfully reinvest capital into high-return growth projects, striving to achieve extremely high returns, thereby repeatedly "defying expectations of diminishing advantages." Their actual growth rates often significantly surpass the market's preset mean reversion assumptions. These core investment cases are found across various industries, and their long-term returns have consistently been the cornerstone supporting portfolio performance.
The catalyst for the disconnect between valuation and fundamentals is widespread panic in the market regarding the transformative impact of generative artificial intelligence. There is concern that competition spurred by new technologies will disrupt existing corporate moats. Currently, the market prices many excellent companies with extremely low growth rate assumptions. However, both historical experience and in-depth fundamental analysis suggest that, in most cases, this collective fear is unwarranted. This severe structural valuation mispricing precisely provides a rare golden opportunity for disciplined, long-term "quality growth" investors to acquire top-tier compound growth companies at "bargain" prices.
To understand the current equity market, it is helpful to divide it into three distinct categories.
The first category comprises the AI winners (AI infrastructure and large language model companies). This group encompasses the AI infrastructure value chain, hardware suppliers, and AI model developers. Supported by robust business fundamentals, upward revisions to earnings forecasts, and peer-leading revenue growth, the upward momentum for these stocks remains strong. Many AI-driven enterprises are already, or are on the path to becoming, enduring companies capable of "defying expectations of diminishing advantages," thus possessing the dual attributes of core potential multi-baggers and quality growth stocks.
In fact, a surprising reality of the current stock market is the high concentration of capital in technology giants with ultra-high profitability and capital reinvestment rates. The rapid pace of AI technological iteration, and the scale of opportunities and infrastructure demand it generates, have repeatedly exceeded market expectations, leading to continuous upward revisions in both their short-term and long-term profit forecasts.
Although their prospects remain strong for the foreseeable future, most of these businesses are capital-intensive and driven by heavy investment. Investors must remain clear-headed; once the construction of global data centers and AI-related hardware infrastructure nears a supply-demand balance, their growth rates will slow significantly, and competitive intensity will surge markedly. Their portfolios have long maintained a positive view on this sector but are simultaneously closely monitoring signals of its maturation.
The second category consists of real asset stocks and market "safe havens." This category primarily includes utilities, materials, some capital-intensive industrial stocks, telecom networks, and large banking institutions with substantial balance sheets. These stocks have experienced significant valuation re-ratings as investors shift funds into sectors perceived to be less directly impacted by AI disruption. Essential physical infrastructure and hard assets are not areas AI can easily replace or directly compete in, leading funds to flow into these havens to avoid companies seen as highly vulnerable to technological disruption.
However, blindly pushing up the valuations of capital-intensive stocks in the absence of fundamental improvements, such as in Return on Invested Capital (ROIC), carries significant risks. The valuation premium investors pay for these stocks above invested capital must ultimately be justified by returns exceeding the cost of capital over the coming years. Yet, the reality is that the ROIC of most companies has not grown in tandem with their valuations. As many investors are paying excessive premiums merely for temporary shelter, this makes the sector structurally unattractive for the long-term outlook.
Banking stocks have also performed very strongly in recent years and are classified by many analysts as "AI winners." The core logic is that banks can use AI to compress costs, thereby improving cost-to-income ratios and boosting profits. However, the flaw in this assumption is that cost benefits are often fleeting. The banking sector is highly competitive, and excess profits are quickly eroded. Furthermore, AI is poised to reshape the global economic landscape, creating new enterprises while accelerating the demise of those unable to adapt. Workplace structures will also face changes, bringing unknown impacts on employment and labor markets. These potential variables do not bode well for future loan defaults. It is expected that the credit cycle will gradually normalize from its current historically low levels of bank provisions. As these factors emerge, banking stocks could easily shift overnight from being "AI winners" into the "AI losers" camp.
In summary, the market's implied expectations for these real asset and safe-haven stocks are somewhat overly optimistic. The market's polarized fervor—blindly chasing pure AI infrastructure stocks on one hand and rushing towards geopolitical hedge commodities on the other—has precisely created a highly unusual structural valuation gap in those global top-tier franchise businesses with strong cash flows.
Investors should cut through the fog of short-term macro noise and refocus on the fundamentals of long-term wealth creation. Paying high premiums for capital-intensive safe havens or cyclical stocks at the peak of supply constraints is a high-risk strategy that historical cycles often punish. Conversely, being able to purchase high-returning, compound growth companies that are actively embracing and integrating digital capabilities at compressed valuations close to the market average not only provides a substantial margin of safety but can also generate exceptional long-term real returns for capital.
Comments