New Research Combines Valuation and Investor Expectations to Identify Stock Market Bubbles

Elisabetta Basilico introduces new research on stock market bubble identification by Andreasen and Bro, published in the Review of Finance (2026). This study combines traditional valuation data with investor expectation surveys to propose a new method for distinguishing between fundamentally driven price increases and speculative bubbles. Based on monthly U.S. data from January 1971 to December 2024, the study estimates that the bubble factor can explain 61% of the variation in the S&P 500 price-dividend ratio. The study also notes that this is a model-based historical estimate and cannot be used as evidence that AI-related stocks are necessarily overvalued or that the market will necessarily correct in the future. The study's model estimates show that after a positive one-standard-deviation bubble shock occurs, the policy rate response will peak at 8 months, with a magnitude of approximately 48 basis points.

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