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Dynamic Attention Behavior Under Return Predictability

Daniel Andrei () and Michael Hasler ()
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Daniel Andrei: Desautels Faculty of Management, McGill University, Montréal, Quebec H3A 1G5, Canada;
Michael Hasler: Naveen Jindal School of Management, University of Texas at Dallas, Richardson, Texas 75080

Management Science, 2020, vol. 66, issue 7, 2906-2928

Abstract: We investigate the dynamic problem of how much attention an investor should pay to news in order to learn about stock-return predictability and maximize expected lifetime utility. We show that the optimal amount of attention is U-shaped in the return predictor, increasing with both uncertainty and the magnitude of the predictive coefficient and decreasing with stock-return volatility. The optimal risky asset position exhibits a negative hedging demand that is hump shaped in the return predictor. Its magnitude is larger when uncertainty increases but smaller when stock-return volatility increases. We test and find empirical support for these theoretical predictions.

Date: 2020
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Handle: RePEc:inm:ormnsc:v:66:y:2020:i:7:p:2906-2928