Are disagreements agreeable? Evidence from information aggregation

Dashan Huang*, Jiangyuan Li, Liyao Wang

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    9 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
    • LASSO
    • Machine learning
    • PLS
    • Return predictability


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