Distorted equity markets: a generational opportunity in quality compounders
We see a compelling opportunity for active global equity investors to exploit the market’s chronic short-sightedness.
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A key insight of our “growth gap” investment philosophy is that market participants consistently suffer from terminal value short-sightedness. When appraising the long-term growth outlook for truly exceptional companies, investors routinely fail to look far enough ahead. They assume a standard, linear fade in competitive advantage and growth when often the reality is that well managed franchises with competitive advantages possess extraordinary compounding power. These companies successfully reinvest capital at high incremental returns, allowing them to consistently “beat the fade” and outgrow the market’s mean reversion assumptions. These “core” investment cases can be found in almost all industries, and their long-term returns have long powered our portfolios.
The stock market opportunity to exploit this myopia has rarely been more compelling. In the immediate aftermath of the COVID-19 pandemic, these steady, faster-growing compounders became highly sought after, driving their valuations to large premiums that compressed our required margin of safety. Today the opposite is true. A major regime shift has taken place; the valuation premium for high-quality compounders has compressed drastically, dragging typical valuations much closer to the broader market average than historical norms.
The catalyst for this disconnected pricing is a pervasive fear of change and disruption to established moats (competitive advantages) by generative AI and the new competition it enables. The market is currently pricing very low growth into many exceptional companies, but history and our own fundamental analysis suggest that in many cases this fear is unwarranted. This severe structural valuation dislocation represents an extraordinary opportunity for disciplined, long-term quality-growth investors to buy outstanding compounding engines at average business prices.
2026 market dynamics: the three-legged equity market
To understand today’s equity market, it is helpful to segment it into three broad and distinct categories:
Category 1: The artificial intelligence winners (AI infrastructure & large language model companies)
This cohort encompasses the artificial intelligence infrastructure value chain, hardware providers, and AI model developers. These stocks continue to exhibit powerful momentum, supported by robust business fundamentals, positive earnings revisions, and exceptional top-line growth. Many AI-driven businesses also either already are, or will be, “beat the fade” businesses and therefore can be seen as both core compounders and quality growth stocks. Indeed, one of the startling realities in today’s equity market is the concentration towards technology companies with extremely high profitability and re-investment rates.
The pace of improvement and hence the scale of the opportunity and infrastructure required in AI has continually surprised investors to the upside, making this a classic “growth gap” group where both near and long-term forecasts continue to be revised upwards. While the outlook remains strong for the foreseeable future, these are mostly heavily capital-investment-driven businesses. Investors must remain cognisant that once the global build-out of data centres and AI-related hardware infrastructure nears an adequate supply level, growth will slow considerably and competitive intensity will rise significantly. Our portfolios remain and have been consistently overweight this group, and we remain positive while watching for signs of maturity.
Category 2: Tangible asset plays & "safe havens"
This group includes mostly utilities, materials, certain asset-heavy industrials, telecommunications networks, and major banking institutions with large balance sheets. These stocks have experienced a significant positive valuation re-rating as investors moved capital into areas perceived to have low direct exposure to the AI disruption debate. Essential physical infrastructure and hard assets are not something that AI can easily replace or compete with, so money has been parked here as a safe-haven from the (perceived) disruption-affected companies.
However, re-rating asset-heavy stocks without an underlying, fundamental improvement in return on invested capital (ROIC) carries severe risk. The valuation premium paid over invested capital must ultimately be earned back in future years through returns above the cost of capital and in most cases ROIC has not increased commensurate with valuations. Because in many cases now investors have paid an excessive premium purely for temporary shelter, the long-term forward outlook for this group has become structurally much less appealing. As Howard Marks once wrote, "Investment risk comes primarily from overpaying, and overpaying usually happens when investors bid up asset prices because they perceive that the future is certain and risk-free."
Banks have also been a very strong sector in recent years and are in many analysts’ “AI winners” category. The theory goes that banks can use AI to take out costs, thereby improving cost / income ratios and profits. The trouble with this hypothesis is that these cost benefits are transitory. Banking is a competitive industry and excess profits are routinely competed away. Furthermore, AI is likely to rewire the global economy, leading to new business formation and increased business failures. Jobs will also shift, with an uncertain impact on employment and labour markets. These are not good developments for future loan delinquencies, and we can expect the credit cycle to normalise upwards from today’s trough levels of bank provisioning. Banks could easily flip from the “AI winners” to the “AI losers” basket as that transpires. In aggregate, we believe implied expectations are too high for this group of tangible asset plays and safe havens.
Category 3: The out-of-favour "quality growth" group (or AI "losers")
This segment represents the core of our focus for alpha generation and is probably the single largest opportunity in global equities today. The market has aggressively de-rated these often high-quality franchises, compressing their valuations as it prices in structural obsolescence, slower growth, or negligible terminal value.
Generative AI will undoubtedly fundamentally change ways of working and trigger a wave of new competition from agile startups approaching target markets in novel ways. However, exceptional businesses do not solely rely on static barriers to entry or rest on their laurels; those that do will inevitably fail. Instead, elite franchises actively invest, adapt, and evolve. They will leverage their established competitive advantages, deep workflow integration, and strong customer relationships to deploy new AI-driven products that better serve their existing user base. The payoff for identifying the businesses that can successfully navigate this transition will be handsome: because the valuation starting point is so depressed, the reward for skilled, active stock picking is significantly higher than usual.
The valuation spread for the best companies is now approaching multi-decade lows, as shown in the chart below, illustrating the opportunity in these stocks if they prove the doubters wrong.
Developed markets (ex-US) valuation spreads (top quintile compared to the market average) 1987 to April 2026
Source: Empirical Research Partners as at April 2026.
A case study in adaptability and AI implementation: Recruit Holdings (Indeed)
A pristine example of this dynamic is Recruit Holdings, owner of the global job-matching platform Indeed. Last year, the stock was aggressively dumped into the "AI losers" bucket on market fears that generative AI job boards would rapidly render the platform obsolete, alongside wider anxieties regarding an AI-driven jobs recession.
Management recognised the market disconnect and used the share price weakness to accelerate their stock buybacks at highly opportunistic prices. Rather than being disrupted, Indeed has integrated advanced AI functionality into its offering to drive deeper value for both employers and jobseekers, facilitating and optimising more of the end-to-end hiring process.
Consequently, instead of suffering structural decline, Recruit has seen its revenue per job posted accelerate in each of the last three quarters, increasing by 17% year-on-year in the last 12 months, accompanied by accelerating earnings growth and upward consensus revisions. The hugely positive earnings (see below) are forcing the market to reconsider its assumptions and wake up to the idea that Recruit may actually be an AI winner, ending a five-year de-rating (see below).
Past performance is not a guide to future performance. The value of investments can go down as well as up and is not guaranteed.
Source: Schroders, Bloomberg, FactSet as at 27 May 2026 shown in JPY. Forward estimates for EPS shown for Bloomberg consensus estimates. The value of investments can go down as well as up and is not guaranteed. The security shown was a holding in the strategy but the timing of purchases, size of position and the return may vary amongst portfolios within the same strategy. Although purchase and sale dates are not shown, the price chart reflects past performance, which gives no assurance of future returns. You should not assume that recommendations made in the future will be profitable or will equal the performance of the security discussed above. The securities shown above are for illustrative purposes only and are not to be viewed as a recommendation to buy or sell.
Echoes of the 1999 tech boom & market exuberance
The current polarisation of the equity market shares profound parallels with the peak of the 1999/2000 dot-com expansion, though there are also of course differences. Both eras experienced high index concentration driven by a narrow cohort of thematic leaders, alongside massive, front-loaded capital expenditure cycles—such as the telecom fibre-optic buildout of 1999 and the $660 billion+ hyperscaler data centre rush today.
Just as today’s “AI losers” are being aggressively de-rated to historic lows on fears of terminal obsolescence, the late 1990s saw high-quality, “old economy” franchises starved of capital and discarded at deeply depressed forward multiples, despite many possessing robust cash flows and defensive moats. More individual stocks actually fell than rose in 1999 as investors indiscriminately liquidated the broader market to fund internet infrastructure.
The current concentration and very strong market performance has been accompanied by signs of systemic late-cycle exuberance such as use of margin debt and ultra short-dated options trading (margin debt is the amount of money investors have borrowed from their brokerage to buy securities, using existing investments as collateral). Investor leverage is expanding faster than the appreciation of the overall market itself. For example, margin debt surged to $1.23 trillion in December 2025 (source: FINRA), pushing total outstanding investment leverage to a record high—even when fully adjusted for inflation.
Historically, such explosive spikes in margin debt have marked the exhaustion phases of major structural bull markets. We saw this pattern build and break at the peak of the 1999/2000 tech bubble, the multi-year crescendo of the US housing boom in 2007, and the liquidity-fuelled, post-COVID peak of late 2021. The current scale of margin debt underscores that while core institutional growth appears selective, the underlying financial plumbing is highly leveraged and vulnerable to sudden deleveraging events. As Warren Buffett noted recently, "We've never had people in a more gambling mood than now." He distinguished this behaviour from traditional capital allocation, concluding that the widespread use of high-leverage instruments to chase immediate momentum "is not investing. It’s not speculating. It’s gambling, just totally."
Historical lessons in obsolescence panic
History shows that the terminal value myopia in good businesses can create large alpha generation opportunities. When the internet bubble burst, unloved, highly cash-generative franchises emerged as very strong market compounders. Excellent examples include global agricultural machinery leader John Deere and autoparts retailer Autozone. The latter was penalised at the turn of the millennium as investors convinced themselves that early e-commerce would rapidly render physical retail obsolete. At the absolute peak of the tech bubble in March 2000, Autozone and Deere were sold down to 12-month forward P/E ratios of under 12x, stark de-ratings relative to a technology sector trading at an aggregate forward P/E of ~50x.
By defending their moats, scaling operations, and effectively integrating digital tools, both companies thrived over the subsequent decades. From these low starting valuation multiples, Autozone and Deere compounded at 17% and 12% annualised returns in the 2010s, while the S&P 500 produced a -1% annualised return.
10-year returns for John Deere, Autozone, and the S&P500, 2000-2010
Past performance is not a guide to future performance and may not be repeated.
Source: Schroders, Refinitiv DataStream as at December 2010. The securities shown above are for illustrative purposes only and are not to be viewed as a recommendation to buy or sell
The prevailing view of 1999 presumed that these businesses would be eroded by digital disruptors because their physical footprints were cost-inefficient, or simply that the businesses were uninteresting in terms of growth relative to the “new economy”. In reality, physical footprints, scale economies, brand, and industry know-how remained strong defensive moats when combined with balance sheet capital and internal cash flow generation. Deere transformed tractors into software-enabled precision instruments. These “old economy” companies quietly reinvested their unloved cash flows into high incremental returns on capital, while shrinking their shares outstanding. When the market multiple compressed for speculative growth, the reality of earnings compounding drove excellent returns for shareholders.
The lesson for disciplined allocators is clear: some of the most stellar long-term returns are captured by going against the market and buying strong, adaptable franchises exactly when the market is pricing them as structural casualties.
Conclusion: A huge opportunity in core compounders
With our investment process focused on fundamentals and core growth investments, the divergence of the “safe havens” and “AI losers” categories has been challenging for recent performance of most strategies managed on the team. The short-term underperformance generated by our quality-growth holdings has been overwhelmingly driven by valuation multiple compression, rather than a degradation of core corporate earnings power or reported growth.
We can see this visually when looking at a style skyline of one of our flagship strategies. The chart below shows the exposure, relative to the benchmark of the portfolio across a range of style characteristics, with the dots being the latest point in a three-year historical range. The portfolio of holdings is exhibiting positive earnings revision momentum relative to market, yet negative price momentum, illustrating the highly unusual disconnect of fundamental earnings and price momentum in the current market.
The de-rating of quality means that we can be invested in very high quality businesses, characterised by high returns on capital, strong profitability and low leverage, at multi-decade low valuations which simultaneously enables the portfolio to be less underweight overall to value characteristics. This is a highly attractive profile.
Style skyline for representative international (ex-US) equity portfolio – current versus last three years
Past Performance is not a guide to future performance and may not be repeated.
Source: Style Research, Schroders, Skyline represents style factor exposures for a representative Schroder International Equity portfolio versus MSCI EAFE as of 26 May 2026. Red mark represents current factor exposure. Bar represents range over the past 3 years.
After extensive research, we have reduced exposure across our portfolios sold investments where we perceive a genuine risk of disruption or material increase in competitive forces. Where we have judged the outlook to be strong or even accelerating, we have increased our greater conviction has generally been and reflected in increased position sizes.
The market's obsession with pure-play AI infrastructure on one hand, and geopolitical commodity hedges on the other, has created an extraordinary structural air pocket in the valuations of elite, cash-generative global franchises. We believe investors should look past the short-term macro noise and focus on the fundamentals of long-term wealth creation. Paying steep premiums for asset-heavy safe havens or cyclical components at the peak of their supply squeeze is a high-risk strategy that historical cycles have routinely penalised. Conversely, purchasing high return, compounding businesses that are actively adapting and integrating digital capabilities at compressed, market-average multiples provides a significant margin of safety and positions capital for superior long-term real returns.
We retain high conviction in our positioning, aligned with businesses that "beat the fade," and highly optimistic about the potential for above-benchmark returns embedded within our portfolios today.
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