Scholarlink

<p>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.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

News-based investor disagreement and stock returns

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月22日

查看全文
  • Sophia Zhengzi Li,
  • Zeyao Luan

摘要

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.