Publication Type
Journal Article
Version
submittedVersion
Publication Date
7-2021
Abstract
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.
Keywords
Disagreement, Market risk premium, Return predictability, Information aggregation, PLS, Machine learning
Discipline
Finance and Financial Management | Portfolio and Security Analysis
Research Areas
Finance
Publication
Journal of Financial Economics
Volume
141
Issue
1
First Page
83
Last Page
101
ISSN
0304-405X
Identifier
10.1016/j.jfineco.2021.02.006
Publisher
Elsevier
Embargo Period
4-20-2021
Citation
HUANG, Dashan; LI, Jiangyuan; and WANG, Liyao.
Are disagreements agreeable? Evidence from information aggregation. (2021). Journal of Financial Economics. 141, (1), 83-101.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/6693
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1016/j.jfineco.2021.02.006