Finance Seminar: Huseyin Gulen, Purdue University
Extrapolation Bias and the Predictability of Stock Returns by Price-Scaled Variables
Using survey data on expectations of future stock returns, we recursively estimate the degree of extrapolation bias (DOX) in investor expectations. There is considerable time-series variation in the DOX, and it interacts significantly with price-scaled variables in predictive regressions. In particular, we show that the ability of the dividend-price ratio to predict the equity premium is contingent on the DOX. There is strong predictability when the DOX is high, while the predictability disappears when the degree of extrapolation bias is low. Additionally, following the intuition from the present-value identity, we find that the lack of return predictability in low-DOX states comes with higher persistence of the D/P ratio. These results extend to the use of the book-to-market and earnings-to-price ratios, and are corroborated by out-of-sample evidence. Our findings have important implications. They support the interpretation of price-scaled variables as proxies for asset mispricing, and they help answer a critical question: when will an overvalued asset, or even a bubble, experience a correction?
Finance Seminars at Caltech are funded through the generous support of The Ronald and Maxine Linde Institute of Economic and Management Sciences and Stephen A. Ross.
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