Are disagreements agreeable? Evidence from information aggregation

Dashan Huang*, Jiangyuan Li, Liyao Wang

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

17 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)83-101
Number of pages19
JournalJournal of Financial Economics
Issue number1
Early online date6 Feb 2021
Publication statusPublished - Jul 2021

Scopus Subject Areas

  • Accounting
  • Finance
  • Economics and Econometrics
  • Strategy and Management

User-Defined Keywords

  • Disagreement
  • Machine learning
  • PLS
  • Return predictability


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