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Are disagreements agreeable? Evidence from information aggregation

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  • Huang, Dashan
  • Li, Jiangyuan
  • Wang, Liyao

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.

Suggested Citation

  • Huang, Dashan & Li, Jiangyuan & Wang, Liyao, 2021. "Are disagreements agreeable? Evidence from information aggregation," Journal of Financial Economics, Elsevier, vol. 141(1), pages 83-101.
    • Handle: RePEc:eee:jfinec:v:141:y:2021:i:1:p:83-101
    DOI: 10.1016/j.jfineco.2021.02.006
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    More about this item

    Keywords

    Disagreement; Return predictability; PLS; LASSO; Machine learning;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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