Disagreement about fundamentals: measurement and consequences

• 成果类型: Article
• 署名作者: Fischer, Paul; Kim, Chongho; Zhou, Frank
• 署名单位: University of Pennsylvania; New York University
• 刊物名称: REVIEW OF ACCOUNTING STUDIES
• ISSN/ISSBN: 1380-6653
• DOI: 10.1007/s11142-021-09627-3
• 发表日期: 2022
• 页码: 1423-1456
• 关键词: cross-section; ANALYSTS FORECASTS; trading volume; INFORMATION; opinion; overconfidence; uncertainty; dispersion; investors; returns

摘要

We propose a measure of disagreement, which reflects differences of opinion as opposed to information asymmetry, that can be extracted from sequences of analyst forecasts. Using a Bayesian theoretical framework, we prove that when analysts agree, a regression of an analyst's forecast on the previous forecast issued by another analyst should have a slope coefficient of one. The magnitude of the estimated regression coefficient's deviation from one is then employed as a disagreement measure. We validate the measure using tests tied to predicted relations between disagreement and trading volume and bid-ask spreads. Finally, we employ our measure to test for associations between disagreement and expected returns predicted by antecedent theoretical studies.