Investor Attention and Stock Returns
57 Pages Posted: 26 Jun 2018 Last revised: 14 Oct 2019
Date Written: October 10, 2019
This paper examines whether investor attention can predict the aggregate stock market. We find that individual investor attention proxies proposed in the literature collectively have a common component that has significant power in predicting stock market excess returns, both in-sample and out-of-sample. This common component is well extracted by using partial least squares and scaled principal component analysis approaches. Moreover, this component can deliver sizable economic gains for mean-variance investors in asset allocation. We identify two economic sources of the predictability: the predictive power of investor attention for aggregate stock market primarily stems from its ability to predict returns in down markets and returns of bad-news driven 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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