Investor Attention and Stock Returns
51 Pages Posted: 26 Jun 2018 Last revised: 23 Jul 2020
Date Written: July 23, 2020
We find that investor attention proxies proposed in the literature collectively have a common component that has significant power in predicting stock market risk premium, both in-sample and out-of-sample. This common component is well extracted by using partial least squares, scaled principal component analysis, and principal component analysis approaches. Moreover, this component can deliver sizable economic gains for mean-variance investors in asset allocation. The predictive power of investor attention for the aggregate stock market primarily stems from the reversal of temporary price pressure and from the stronger forecasting ability for high-variance stocks.
Keywords: Investor Attention, Stock Return Predictability, Partial Least Square (PLS), Principal Component Analysis (PCA), Out-of-sample Forecast
JEL Classification: C22, C53, G11, G12, G17
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