Dynamic Attention Behavior Under Return Predictability

• 成果类型: Article
• 署名作者: Andrei, Daniel; Hasler, Michael
• 署名单位: McGill University; University of Texas System; University of Texas Dallas
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2019.3328
• 发表日期: 2020
• 页码: 2906-2928
• 关键词: Asset pricing; portfolio choice; investors' attention; information acquisition; Return predictability

摘要

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.