Modern portfolio construction is under newfound scrutiny as AI has grown increasingly impactful for overall market returns. For decades, the most common way to think about building a stock portfolio was growth versus value. Growth stocks are companies investors expect to expand quickly, which is why they tend to trade at higher prices relative to what they earn today. Think fast-growing technology names. Value stocks are companies that look inexpensive relative to their current earnings, often more established or slower-growing businesses. Owning both was a simple way to diversify, because the two groups tended to perform well at different times. This growth versus value framework shaped how portfolios were built, how funds were marketed, and how investors evaluated risk. It was powerful because it isolated different companies that responded differently to the same economic conditions, and owning both sides of that spectrum provided diversification.
But growth versus value may no longer have the same utility. The S&P 500 Value Index holds 438 constituents and the S&P 500 Growth Index holds 145. 80 stocks are members of both indexes, a ~55% overlap.
Growth versus value style is getting blurred. If the same stocks are in both the growth bucket and the value bucket, then the labels are no longer cleanly separating different kinds of companies. The very thing that made growth versus value useful, sorting the market into two genuinely different groups, has started to break down.
The old framework worked because growth expectations and valuations were genuinely spread across the market. Different sectors and industries offered different risk profiles, so sorting by style gave you real diversification. That is no longer the case. The companies with the highest growth expectations are now clustered in a handful of related industries, while many of the companies that screen as value are cheap for very different reasons, some because they are stable and out of favor, others because they are in genuine decline.
Growth versus value was built for a market where valuation was the primary driver of returns. But in this environment, the market appears to care more about what a company's relationship to AI is.
Market construction has evolved significantly over the past few decades, and we believe style positioning must evolve with it. In today's market, what may matter most is how much of your portfolio is exposed to companies that AI could disrupt versus companies that are resistant to it.
As the world has become more digital, software, semiconductors, and data services have grown to nearly 40% of the S&P 500. The thread connecting those sectors is not valuation or growth rate, but their exposure to AI. On one side are the AI stocks, the companies whose fortunes rise and fall with the AI buildout. On the other are what we call HALO stocks, short for Heavy Asset, Low Obsolescence, companies whose value comes from physical, hard-to-replace assets that AI cannot easily disrupt. In our view, this is becoming an AI versus HALO market.
AI specifically, and technology broadly, have become critical contributors to the overall market’s profits and total return. Technology is now the S&P 500’s largest sector. The index most investors treat as their diversified core has quietly become heavily exposed to one of the most transformative thematic bets in market history.
To be clear, this is not a critique of AI as an investment thesis. While there will be volatility, the buildout is real and the earnings have validated it. The point is more fundamental. Most investors have significant AI exposure just from investing in the S&P 500. Passive index ownership combined with three years of AI price appreciation has mechanically increased concentration in virtually every standard portfolio. An investor who has not looked closely at what they actually own recently is almost certainly more concentrated in AI outcomes than they were two years ago.
What is a credible counterweight to AI exposure?
We believe it is HALO stocks, not value stocks as traditionally defined. Heavy Assets, Low Obsolescence (HALO) stocks offer a set of exposures with fundamentally different return drivers that behave differently in the specific environments that tend to stress AI most.
HALO describes companies whose value comes from physical characteristics: scarcity, capital intensity, and structural resistance to technological obsolescence. Their economics are driven by real asset pricing, supply constraints, and long-cycle capital allocation decisions.
This is where the framework has the potential to add value. Within a traditional equity screen, a steel producer and a struggling retailer could look similar with low multiples, lower growth expectations, and bucketed into the Value category. However, their relationship to AI is completely different. The retailer may be in structural decline as AI-enabled competitors capture market share. The steel producer owns physical assets that are scarce and capital-intensive to replicate, characteristics that AI cannot easily disrupt. In our view, this is the most important distinction in the market right now.
HALO does not mean defensive. Consumer Staples and Utilities are defensive because demand is stable regardless of the cycle. HALO is an asset characteristic. It is about irreplaceability, asset age and value that does not erode. The two categories behave differently when it matters, and investors who conflate them will find that out the hard way.
AI and HALO offer balance to exposures with structurally different return drivers. We believe that the right weighting towards both groups could produce a more efficient risk-adjusted outcome than either held alone. That is the foundational logic of diversification applied to a set of categories the growth and value may not perfectly capture anymore.
The recent stress events prove the mechanism in real time. The 2025 tariff shock hit AI-exposed names hard because valuations built on future growth are inherently sensitive to uncertainty and uncertainty can pull those prices back down. The early 2026 geopolitical disruption sent energy prices sharply higher with essentially no impact on AI infrastructure valuations, while real asset exposure benefited meaningfully. The two buckets did not move together. That is exactly the point.
A portfolio built around this framework is not a binary bet on whether AI wins or loses. It is structured to participate in the buildout while also owning assets whose value is grounded in physical reality rather than in the resolution of a technology cycle.
In a standard passive portfolio, most investors hold more AI exposure, and in a more concentrated form, than any fund label suggests. The flip side is just as important. Investors often assume they own meaningful real-economy exposure, but they likely own less than they think. As technology has taken a larger and larger share of the major indexes, the physical-asset sectors have quietly shrunk. For most portfolios, HALO characteristics are underweight by default rather than by design.
Every generation of investors gets a new way to build portfolios, usually in response to the blind spots of the one before it. Decades ago, Modern Portfolio Theory replaced gut-feel stock picking with the math of diversification. Later approaches tried to correct for the hidden concentration that can build up inside a portfolio that looks balanced on the surface.
The AI versus HALO framework is a response to a market that has concentrated risk in ways the old categories simply do not capture. The most important distinction between companies today is not how they are priced relative to earnings. It is whether they are building the AI-driven future or built from things that future cannot touch.
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