Nasdaq lurch sparks “2026 looks like 1999” warnings on earnings-expectations math

Friday’s Nasdaq lurch lower is being treated like a crack in a story that looked, until then, almost bulletproof. Tech stocks led the worst market sell-off since October, and AI-linked megacaps shed hundreds of billions of dollars in value in a single session. Two immediate nerves were hit at once: a stronger-than-expected jobs report rekindled fears of Federal Reserve rate hikes, and Broadcom’s recent weak guidance made traders question whether the AI boom can still justify tech-bubble valuation multiples without clearer signs of imminent rate cuts.

This is the context that makes a specific warning from earlier in June feel uncomfortably on-the-nose. On June 3, two days before the sell-off, Acadian Asset Management senior portfolio manager Owen Lamont posted on his Owenomics blog, “A pessimistic take on optimistic growth forecasts,” under the headline “Yet another way in which 2026 is looking like 1999.” Lamont’s argument was not that a bubble is detected first by price action. It is detected by the surge in the earnings expectations that are used to justify those prices.

Lamont’s math goes back to 1985. He calculated that analysts have on average predicted about 13% annual earnings growth for S&P 500 companies, while realized earnings growth has been closer to 7%. In other words, forecasts have tended to overreach, and the overreach itself can become the fuel for “irrational exuberance,” because investors project those earnings forward when the story feels believable enough. Lamont drew on research by Pedro Bordalo, Nicola Gennaioli, Rafael La Porta, and Andrei Shleifer, citing findings that shareholders get disappointed over the next five years when earnings do not grow as fast as expected, similar to what happened after the tech stock bubble.

Then Lamont anchored the claim to a concrete valuation backdrop: expected long-term S&P 500 earnings growth hit 20.2%, exceeding 2000’s high of 18.6%. He also referenced long-time stock watcher Ed Yardeni, originator of the “bond vigilantes” phrase, to underline how expectations and rates can collide. His punchline was blunt: maybe when 2031 rolls around, today’s valuation will look like another triumph of the efficient market hypothesis. But “for me,” he wrote, “today’s optimism is yet another way in which 2026 is looking like 1999.” The danger, in his framing, is less that the S&P 500 is “too high” in some abstract sense, and more that investors and analysts are once again getting out over their proverbial skis.

This theme of divergence and risk was echoed in JPMorgan Asset Management’s own forecasting, just a day earlier. On June 1, JPMorgan Asset Management chief global strategist David Kelly published his weekly note, “Investing in a Divergent Economy.” The averages sounded comforting at first glance: real U.S. GDP growth between 2.0% and 2.5% in 2026, easing to 1.5% to 2.0% in 2027; unemployment drifting slightly below 4%; and inflation falling back toward 2% over the next year. But Kelly stressed that those averages mask many dimensions of divergent trends, and he pointed to where Wall Street’s optimism may not match the economic reality experienced by many households.

Kelly’s examples were deliberately uneven, almost storyboard-like. Rich vs. poor: he cited work by Thomas Piketty and Emmanuel Saez that the top 10% of U.S. households received around 50% of total income in 2022, alongside Federal Reserve data showing they owned roughly 62% of household assets, with total household assets near 630% of GDP, higher than before the dot-com bust or the 1987 crash. Tech vs. the rest: the top 10 companies in the S&P 500, eight of them essentially tech names, account for more than 41% of index market cap and 33% of earnings, even as the broader economy shows unevenness. He also cited estimates that hyperscaler capital spending will jump 78% in 2026, from $416 billion to $739 billion. Sentiment vs. reality: consumer sentiment measured by the University of Michigan hit an all-time low, and the “misery index” of unemployment plus inflation is still better than more than half the time over the last 50 years, but the direction matters. He even included a personal anecdote about a road trip and a Jersey Mike’s line where a man had just gotten a job after five months, followed by difficulty booking restaurants in midtown Manhattan because OpenTable bookings were up 13% year over year in May. “As divergence grows across multiple dimensions,” Kelly concluded, “so do the risks of something going badly wrong.”

Now zoom out to how this looks from the other side of the desk. Even while Lamont and Kelly were making their case, influential forecasting shops leaned in the opposite direction. On June 1, Deutsche Bank’s global economics team framed 2026 as “anything but dull,” with “1999 meets 1990, but hopefully not 1973,” citing AI-driven optimism colliding with a Middle East energy shock. Deutsche reaffirmed its S&P 500 year-end target of 8,000 and a price/earnings multiple around 25x, and expected S&P 500 EPS to grow 14.2% in 2026, underpinned by strong tech and financial earnings and “sustained elevated valuations.” Four days earlier, on May 29, Goldman Sachs raised its forecast for 2026 U.S. IPO gross proceeds to $225 billion from $160 billion, estimated total U.S. corporate equity issuance at $675 billion, about 1% of Russell 3000 market capitalization, set a 12-month price target of 8,300, implying a forward P/E near 21x, and noted valuation charts placing major U.S. indices in the upper quartile of their 20- and 30-year ranges, with Nasdaq 100 at the very top. Both banks were careful to hedge: Deutsche flagged higher inflation and modestly higher long-term rates, and Goldman acknowledged slowing buyback growth as AI capex soars.

That’s where the sell-off becomes a governance and strategy issue, not just a trading story. If earnings expectations are doing more work than realized earnings can, then small shocks, like a jobs report that revives rate-hike fears or weak guidance from a chipmaker, can compress the multiple quickly. And if capital markets activity, deal flow, and IPO pipelines are built on the assumption that the current optimism is structurally sustainable, executives across tech, finance, and adjacent sectors face a risk: the market may reprice before companies can prove the next quarter, let alone the next five years.

To see that assumption challenged, look at the notes from the men at the top of the financial food chain. On May 27 at Bernstein’s Strategic Decisions Conference, JPMorgan CEO Jamie Dimon said, “It’s gung-ho, folks,” adding that deals are flowing, bankers are busy, sponsors are spending, and clients aren’t hesitating. He saw M&A tracking toward the best year in recent memory, and equity capital markets activity, including IPOs and follow-ons, as “huge.” In the week that followed, Anthropic confidentially filed for an IPO, Goldman raised its IPO forecast, and SpaceX formally filed to… The pattern is clear: optimism can become a funding ecosystem. The question Lamont and Kelly are implicitly asking is what happens to that ecosystem if earnings growth expectations keep running ahead of reality, and rates stop cooperating.