Disagreement about fundamentals: measurement and consequences

Paul Fischer, Chongho Kim and Frank Zhou ()
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Paul Fischer: University of Pennsylvania
Chongho Kim: New York University
Frank Zhou: University of Pennsylvania

Review of Accounting Studies, 2022, vol. 27, issue 4, No 10, 1423-1456

Abstract: Abstract 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.

Keywords: Disagreement; Divergence of opinion; Expected returns; Analyst forecasts (search for similar items in EconPapers)
JEL-codes: G14 M41 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11142-021-09627-3

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