Fragility: Balancing high valuations and strong earnings

An important part of our Asset Allocation Committee’s process is to run an anonymous survey before each meeting. Research shows that bringing independent thinking to the table reduces groupthink and improves decisions.¹

In our last survey, one member captured the committee’s mood in a nutshell: “I am nervous, but the data are holding for now.”

When it comes to equities, we face a heavyweight showdown between high valuations and strong fundamentals:

• In the blue corner stands the S&P 500’s price-to-earnings ratio, weighing in at 22 following a 30% price bulk in just four months!²
• In the red corner stands earnings growth, weighing in at +12% year over year, strengthened by artificial intelligence (AI) stimulants!³

Having sized up these competing forces, committee members are comfortable remaining neutral between stocks and bonds.

The bull case

We prefer to not step in front of the AI momentum train. Plus, “This administration wants to engineer strong capital markets into the midterms. Don’t underestimate the deregulation that’s likely to follow. Meanwhile, M&A and buybacks are accelerating,” said a committee member.

Maybe we’re too worried about valuation (how’s that for a peak market statement?). The high price-to-earnings (P/E) ratio for the S&P 500 Index is in part justified by high profit margins and a tech-heavy composition. The following chart shows how profit margins for the index have trended higher and are now more than double what they were in the early 1990s (Fig. 1). The S&P has built lean muscle mass.

In a prior analysis⁴, with the help of our research team (William Liu, Rob Panariello, and other contributors), I explained that high profit margins justify high valuations if the margins are tech-driven and don’t revert toward the mean. In these cases, high margins represent pricing power, or moats, if you will. Historically, moats have led to high sustainable earnings growth.

This is not the case for all sectors. For example, in commodities-linked sectors like energy, high profit margins may merely indicate high commodity prices, which tend to mean revert.

Historical lessons (using AI)

Another bullish argument is that counterintuitively, all-time highs historically have been followed by strong, not weak, market returns (on average).

But high valuations, despite the narrative that “valuations don’t work” in the short run, have indicated fragility.

Let me present some data to support these statements. In an example of AI efficiency, here’s a question I asked ChatGPT 5.0:

Here's a file with dates, S&P 500 price index values, and P/E ratios. Can you calculate average 12-month returns overall, average forward 12-month returns when the S&P 500 is at an all-time high, and average forward 12-month returns when the P/E ratio is above 20?

I provided ChatGPT with monthly data, sourced from Bloomberg, spanning from January 31, 1990, to August 15, 2025. I used the forward 12-month P/E ratio. In about three seconds, I obtained the following results:

1. Average forward 12-month returns overall: 9.9%
2. Average forward 12-month returns when the S&P is at an all-time high: 11.8%
3. Average forward 12-month returns when the P/E ratio is above 20: 1.2%

It was my first time trying this, so I checked the numbers. They were correct. (I recommend that you always spot-check AI results and ask it to use real sources and cite them. Sometimes it helps to ask the AI to double-check its own work as well.)

This analysis raises the question: What happens when the S&P 500 is at an all-time high and the P/E ratio is above 20? ChatGPT identified 32 such instances and measured the average forward 12-month return at 6.2%.

Again, high valuations signal fragility. The committee is concerned about two significant macro risks in particular. First, a growth scare. I’m watching employment and Institute for Supply Management (ISM) data. Recent prints were weak. Second, inflation. “Risk assets should go higher until we hit an inflation constraint,” said a committee member.

Tactical asset allocation positioning

U.S. rates are another risk we’re watching closely. The long end of the U.S. Treasury curve has stayed mostly rangebound this year. But an inflation pickup (or deficit fears) could send longer-term yields meaningfully higher, threatening a one-two punch to fragile equity valuations. Consequently, we continue to underweight long-dated Treasuries.

While we’re neutral on risk assets, we remain long diversification. We debated our broadening trades. Should we take profits on our overweight international value position? Should we consider neutralizing our long position in U.S. mid-caps versus small-caps, given likely rate cuts? In both cases, we decided to stay the course.

Takeaways

Now, ChatGPT, could you write the last paragraph? And please, don’t use those annoying em dashes that will reveal I used AI to write it.

Markets are riding a mix of strong fundamentals and high valuations, a combination that has historically delivered both opportunity and vulnerability. While all-time highs often precede strong returns, elevated valuations can temper those gains. Macro risks from slowing growth and persistent inflation remain in focus, even as momentum, policy, and corporate activity keep risk assets buoyant. In this environment, we see merit in patience, discipline, and a commitment to diversification as the best tools for navigating what comes next.

(I should have added: Don’t make it too wordy.)