The stock market makes just as much sense as it usually does right now

In a recent opinion piece for The New York Times, author and financial commentator Kyla Scanlon offered her case for why “markets are not properly pricing risk” and how, when it comes to disruptions to global energy supplies, “the stock market has decided this available information is not relevant.”

I disagree, and would like to address many of the arguments she makes point by point:

“More broadly, the markets are showing the single lesson that the past 40 years have taught them.

It will always be saved.”

Scanlon continued that the so-called “Greenspan put” is irrelevant in the current circumstances because policymakers are not well positioned to respond. I’d first note that the Greenspan put, as an empirical matter, has always been ineffective in dealing with significant shocks.

The two biggest drawdowns in the S&P from a record high since the Great Depression, and two of the seven longest bear markets ever, have come in the past 30 years: the bursting of the dot-com bubble and the fallout from the global financial crisis.

Imagine getting beaten half to death twice in 30 years, and despite receiving the best medical attention money can buy, taking years to regain your health. “It’s dangerous out there and I should be careful!” may be the more relevant lesson than “I’m invincible!”

While I’m sympathetic to the idea that these examples only apply to those of a certain age, we’re less than four years removed from the end of a 282-day S&P bear market. And depending on who you ask, policy not only failed to come to the rescue, but also played a role in exacerbating the downturn, to the extent that fiscal stimulus enhanced inflation. In 2022, Fed Chair Jerome Powell said “pain” would be involved in bringing price pressures to heel. 

We’re past the point of pretending that the only environment investors have ever known is one where fiscal and monetary policymakers unambiguously have their backs.

Now, the potential for an about-face in policy from the Trump administration to undo a self-inflicted market downturn is likely among the reasons for the muted downside in the S&P 500 — particularly one year after traders saw the exact same thing occur. That episode is also a learning lesson in that traders saw the negative catalyst everyone was worried about actually come to pass — effective tariff rates went up a ton! — and the world didn’t fall apart. 

One reason, as Scanlon rightly noted, is due to the earnings power of the AI boom:

“The only real backstop, if you look at where the money is going, is artificial intelligence.”

“This reliance on A.I. looks like an extraordinary concentration of bets. The Magnificent 7 (Google’s parent, Alphabet; Amazon; Apple; Facebook’s parent, Meta; Microsoft; Nvidia; and Tesla) are over 30 percent of the S&P 500, up from about 12 percent a decade ago.”

“The implicit argument embedded in current valuations across both public and private markets is that A.I. will be productive enough to offset an economic downturn as the economy loses jobs from A.I. The valuations also suggest that the A.I. industry will be efficient enough to navigate an energy crisis with the knowledge to reroute supply chains disrupted by, say, war.”

“The productivity miracle hasn’t come close to what valuations require. Now, it may happen. But the distance between ‘may’ and ‘has’ is the distance between a thesis and a prayer, and markets are very much pricing the prayer.”

“Behind that sits an even deeper assumption: that if A.I. falters, the government will do everything it can, even with its constraints, to save the industry through all elements of support. We already see this with accelerated data center permitting, major Pentagon contracts, a largely hands-off regulatory approach and state data center tax breaks. This redirects moral hazard from ‘the Fed will bail out the banks’ to ‘the government will bail out A.I.’ Call it the A.I. put — and this isn’t a critique of A.I. companies. They are responding to the incentives of a favorable policy environment.”

No edge in private markets; happy to concede that point.

But there is a major difficulty with making the argument that current valuations in public markets reflect a long-lived AI productivity boost: hyperscalers, the companies that are spending the most money to deploy computing power, have seen their valuations go absolutely nowhere for over two years.

This reflects a sense of unease that AI-juiced profits in the near term, as companies experiment with the nascent technology, may not have a high-ROI payoff in the years to come. All told, the so-called Magnificent 7 cohort has lagged the Nasdaq 100 by about 5% year to date, with the average forward price-to-earnings ratio for Microsoft, Meta, Amazon, and Google hitting its lowest level of the AI boom in March.

If investors are all in on the long-term earnings power of AI, why are they not willing to pay a higher price for these future earnings streams? Especially if AI is “heads, tech companies win; tails, the government doesn’t let them lose”?

Why have the AI winners in 2026 been slightly off the beaten path in a group of tech picks-and-shovels stocks poised to enjoy windfall profits because of supply-demand imbalances? 

The underbelly of the AI trade throughout 2026 shows the precise opposite of pricing in a prayer. It’s a pricing in instead enjoyed by companies selling umbrellas in a rainstorm, thanks to the weather forecast showing that this downpour isn’t on the verge of ending.

Based on the available data, it is much easier to make the case that AI has been a net negative rather than a net positive for the S&P 500’s valuations in 2026, based simply on how software companies have seen their multiples crushed amid the potential of AI-induced disruption (or at the very least, a loss of pricing power). 

Is there a length and intensity of the ongoing disruption to energy markets that drives the US and global economy into recession? Almost certainly yes.

But the current level of the S&P 500 can’t just be hand-waved as a function of the market not taking in and weighing all of the available information. It’s that the “available information” the market cares about is more than the number of ships that are currently (not) going through the Strait of Hormuz.

For starters, don’t count out the US consumer. 22V Research economist Peter Williams noted that banks’ card numbers show “possible signs of recent acceleration” in the Q1 reporting period with “little sign of immediate negative impacts for the US consumer or businesses” from the jump in oil prices.

“Wells Fargo noted that historically it takes consumers several months to reduce spending on other categories to adjust for higher oil prices, and they’d expect the same pattern in the second half,” he wrote. “The negative really depends on the extent and duration of the shock. There’s little reason to expect a short-term behavioral shift when balance sheets are strong, and some dissaving is easy enough.”

Investors did de-risk, and then added back exposure thinking the announcement of a ceasefire meant the odds of this geopolitical conflict causing the economy to go pear-shaped have decreased. Per Deutsche Bank, which flagged that its measure of equity positioning jumped sharply, but to levels not far above neutral: “The jump is comparable to those just after the Nov 2024 US election, and when exiting steep slumps in late 2018, the Brexit vote in 2016, China bubble fears in 2015 and the Japan nuclear scare in 2011.”

Anthropic’s seeming compute shortage, and the ferocity with which it’s scrambling to accumulate more, speaks to end user demand for AI tools (rather than a hyperscaler arms race) that has helped restore some of the shine to the boom’s marginal and established players alike.

Most importantly, perhaps, is that the day the S&P 500 bottomed coincided with an unprecedented divergence between stock prices (falling) and earnings estimates (rising).

Through this lens, the market’s sharp rebound is a function of unlocking upside that investors were too cautious to buy into — either down to concerns that the energy shock was indeed increasing downside risks to the economy, or that the AI build-out was America’s technological equivalent of China’s bridges to nowhere.

I don’t know if the stock market makes sense right now any more than it usually does. What I do know is that when earnings estimates are trending higher, the unemployment rate isn’t surging, and inflation isn’t generationally high, stocks usually go up.