News-based investor disagreement and stock returns

Sophia Zhengzi Li () and Zeyao Luan ()
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Sophia Zhengzi Li: Rutgers University
Zeyao Luan: Rutgers University

Review of Accounting Studies, 2025, vol. 30, issue 3, No 4, 2312-2375

Abstract: Abstract We estimate investors’ disagreement regarding firm news and assess its ability to predict stock returns. Specifically, we quantify firm-level investor disagreement through the volume-volatility elasticity surrounding firm news; higher elasticity is associated with less investor disagreement. Intuitively, disagreement introduces additional trading motives that are not driven by price changes, weakening the connection between volume and volatility. Our findings indicate that investor disagreement on news negatively predicts cross-sectional returns. We also present empirical evidence aligned with the theoretical predictions of a recently developed model by Atmaz and Basak (Journal of Finance 73 (3): 1225–1279 2018) that the negative disagreement-stock relation strengthens when the optimism effect dominates the uncertainty effect. Importantly, this predictive relationship remains robust after controlling for news heterogeneity, other volume- and volatility-based measures, and alternative channels.

Keywords: News announcements; Disagreement; High-frequency; Trading volume; Volatility (search for similar items in EconPapers)
JEL-codes: G12 G14 G17 G40 M41 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11142-025-09897-1

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