Disagreement About Fundamentals: Measurement and Consequences

46 Pages Posted: 31 Jan 2020 Last revised: 21 Jul 2021

See all articles by Paul E. Fischer

Paul E. Fischer

University of Pennsylvania; University of Pennsylvania - Accounting Department

Chongho Kim

New York University

Frank Zhou

University of Pennsylvania - The Wharton School

Date Written: January 6, 2020

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, Disclosures

JEL Classification: G14, M41

Suggested Citation

Fischer, Paul E. and Fischer, Paul E. and Kim, Chongho and Zhou, Frank, Disagreement About Fundamentals: Measurement and Consequences (January 6, 2020). Available at SSRN: https://ssrn.com/abstract=3515685 or http://dx.doi.org/10.2139/ssrn.3515685

Paul E. Fischer

University of Pennsylvania ( email )

PA
United States
215 573 7533 (Phone)

University of Pennsylvania - Accounting Department ( email )

3641 Locust Walk
Philadelphia, PA 19104-6365
United States

Chongho Kim

New York University ( email )

40 West 4th Street
Suite 10-180
New York, NY 10012
United States
5129987313 (Phone)

Frank Zhou (Contact Author)

University of Pennsylvania - The Wharton School ( email )

3641 Locust Walk
Philadelphia, PA 19104-6365
United States

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