Are disagreements agreeable? Evidence from information aggregation

Dashan Huang, Jiangyuan Li and Liyao Wang

Journal of Financial Economics, 2021, vol. 141, issue 1, 83-101

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; Return predictability; PLS; LASSO; Machine learning (search for similar items in EconPapers)
JEL-codes: G12 G14 G17 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jfinec:v:141:y:2021:i:1:p:83-101

DOI: 10.1016/j.jfineco.2021.02.006

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