Dynamic Attention Behavior Under Return Predictability
Daniel Andrei () and
Michael Hasler ()
Additional contact information
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
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.
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:66:y:2020:i:7:p:2906-2928
Access Statistics for this article
More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Matthew Walls ().