Jeremy Grantham Calls U.S. Stocks Most Expensive in History
Veteran investor Jeremy Grantham warns AI-driven valuations have pushed U.S. equities to historic extremes, raising fresh bubble concerns.
Jeremy Grantham, the co-founder of asset management firm GMO and one of Wall Street's most closely watched market historians, is sounding a familiar but increasingly urgent alarm: American equities have never been more expensive. His assessment places current valuations above every prior peak in U.S. market history — a claim that carries weight given Grantham's track record of identifying the dot-com and housing bubbles before they burst.
At the center of Grantham's concern is artificial intelligence. The excitement surrounding AI has propelled a narrow set of technology-linked stocks to stratospheric price levels, compressing earnings yields and stretching price-to-earnings multiples well beyond historical norms. The dynamic echoes the late 1990s tech euphoria, when investor enthusiasm for transformative technology outpaced the underlying economics — at least in the near term — before a severe correction followed.
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What makes Grantham's warning analytically significant is its historical framing. He is not merely arguing that stocks are expensive by conventional metrics; he is arguing they have surpassed every prior valuation extreme on record in American market history. That framing sets a higher bar for dismissal. Bulls can reasonably counter that AI represents a genuine productivity revolution that justifies premium pricing, but Grantham's point is that markets historically overprice even real transformations in the short run.
For long-term investors, the practical implication is sober: elevated starting valuations are among the most reliable predictors of muted future returns over a 7-to-10 year horizon. Whether or not a dramatic crash materializes, those entering U.S. equity markets at current levels may be accepting lower forward returns than historical averages suggest. Grantham's view, controversial as it remains in bullish circles, is grounded in a framework that has proved prescient before — even if the precise timing of any correction remains, as always, unknowable.
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