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The Wharton professor who called tech stocks a ‘sucker’s bet’ in 2000 before the dotcom crash says we aren’t in another bubble—yet

Will Daniel
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Will Daniel
Will Daniel
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Will Daniel
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Will Daniel
Will Daniel
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February 14, 2024, 3:26 PM ET
Jeremy Siegel
Wharton professor Jeremy Siegel.Scott Mlyn—CNBC/NBCU Photo Bank/NBCUniversal/Getty Images
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The recent rise of AI-linked tech stocks has been compared to the late-’90s, early 2000s dotcom era by more than a few experts. But Wall Street’s bulls and bears can’t seem to agree on what phase of history we’re repeating.

The optimists argue that the AI gold rush is just getting started, and the firms creating the “picks and shovels” of the modern era are set to benefit for years to come. As Wedbush’s tech analyst Dan Ives put it last year, it’s “a 1995 moment with a long runway of growth ahead” and not a “1999 moment” where markets are on the verge of collapse. But the bears warn that the AI hype is overdone. Recalling the internet boom that drew in crowds of investors to high-flying, but often unprofitable, tech stocks in the late 1990s, Jeremy Grantham even warned this month that AI stocks are in a bubble that will soon burst. The Dow’s 500-point wobble on CPI data suggesting higher-for-longer inflation (and interest rates) has some observers wondering if the beginning of the bubble popping is nearing in 2024.

Even Jeremy Siegel, a veteran market watcher and Wharton finance professor known for his sober takes, warned in his weekly WisdomTree commentary Wednesday that he’s starting to see “overspeculation” in semiconductor stocks linked to AI.

“I won’t call this a bubble at these levels, but there is a frenzy of excitement and many trend followers are piling on the AI wagon,” he warned. “This can continue a long time until we get a big earnings miss, but we know if these trends last long enough, it does not end well.”

Still, when it comes to comparisons to the dotcom bust, Siegel is skeptical. And since he was right there, making prescient predictions just before the tech bubble popped, his words are likely worthy of attention.

“Many make analogies of the AI hype today to the internet boom in 2000,” Siegel wrote Wednesday. “I called out many of the big-cap tech stocks as a sucker’s bet in March 2000 in my Wall Street Journal op-ed at that time. I don’t think we are anywhere near levels that motivated that view.”

Nowhere near ‘sucker’s bet’ territory

Siegel noted Wednesday that the S&P 500 traded at over 30 times earnings in March of 2000, and large-cap tech stocks were selling at double those levels. “Internet firms that had no earnings and traded at huge valuations” were emblematic of the problem, he wrote, adding that “the market as a whole is much more reasonably priced now” at roughly 20 times forward earnings. 

Siegel believes that the economy is currently in a “Goldilocks” phase, with relatively low inflation and a strong labor market. If hiring starts to slow, he said he has faith that the Fed will cut interest rates to support growth.

The economy is proving its resilience, and stocks are not yet at bubble levels, according to Siegel, but he still recommended investors look for opportunities in the “unloved non-tech segments” instead of highly valued AI stocks, arguing there are “real pockets of value” in small-caps.

“While I don’t think we’re in a bubble yet, I think investors should be looking for broader participation in the markets,” he wrote. “If the AI revolution is as real as I think it can be, it will not just benefit the megacap tech stocks. All firms will learn how to use and benefit from this great technology.”

Echoing Siegel’s point about AI benefiting more than just megacap tech firms, Goldman Sachs’ chief global equity strategist and head of macro research in Europe, Peter Oppenheimer, recently detailed the rise of technological revolutions throughout the past few centuries in his book Any Happy Returns. 

In a follow-up conversation with Fortune, he explained how investors can learn how to navigate the AI era by understanding the history of an underappreciated invention: canals. The canal boom of the 1700s revolutionized the transportation of cargo in the U.K., leading investors to flock to the companies that owned them. That eventually led to a boom and bust cycle in canal stocks on the London Stock Exchange. But while canal stocks weren’t always winning investments, the canals themselves led to a huge productivity boom that helped the entire economy and stock market grow.

The big lesson of it all: The long-term winners of the AI boom might not be the companies developing the technology, but the ones who can use it to create something new and profitable. Choose wisely.

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