Are disagreements agreeable? Evidence from information aggregation

Are disagreements agreeable? Evidence from information aggregation

Disagreement measures are known to predict cross-sectional stock returns but fail to predict market returns. This paper proposes a partial least squares disagreement index by aggregating information across individual disagreement measures and shows that this index significantly predicts market retur...

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Bibliographic Details
Main Authors: HUANG, Dashan, LI, Jiangyuan, WANG, Liyao
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2021
Subjects:
Disagreement
Market risk premium
Return predictability
Information aggregation
PLS
Machine learning
Finance and Financial Management
Portfolio and Security Analysis
Online Access:https://ink.library.smu.edu.sg/lkcsb_research/6693
https://ink.library.smu.edu.sg/context/lkcsb_research/article/7689/viewcontent/DisagreementsAgreeable_2021_sv.pdf
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Institution: Singapore Management University
Language: English
Description
Summary:Disagreement measures are known to predict cross-sectional stock returns but fail to predict market returns. This paper proposes a partial least squares disagreement index by aggregating information across individual disagreement measures and shows that this index significantly predicts market returns both in- and out-of-sample. Consistent with the theory in Atmaz and Basak (2018), the disagreement index asymmetrically predicts market returns with greater power in high-sentiment periods, is positively associated with investor expectations of market returns, predicts market returns through a cash flow channel, and can explain the positive volume-volatility relationship.

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