A Structural Model of Analyst Forecasts: Applications to Forecast Informativeness and Dispersion

63 Pages Posted: 12 Jun 2020

See all articles by Jonathan Clarke

Jonathan Clarke

Georgia Institute of Technology - Scheller College of Business

Soohun Kim

College of Business, Korea Advanced Institute of Science and Technology (KAIST)

Kyuseok Lee

College of Business, Korea Advanced Institute of Science and Technology (KAIST)

Kyoungwon Seo

Seoul National University

Date Written: May 18, 2020

Abstract

We modify Morris and Shin (2002) to develop a structural model of analyst earnings forecasts. The model allows for analysts to herd due to informational effects and non-informational incentives. The benefits of our model are twofold: (1) we can decompose earnings forecasts into informational and bias components, and measure the stock price response to each component, and (2) we can estimate the impact of bias on the dispersion in analyst forecasts. In a pair of empirical exercises, we find a strong relation between the informational component of analyst forecasts and announcement period stock returns. We also find that analyst biases do not have an impact on forecast dispersion.

Keywords: Analyst, herding, EPS forecast, structural model

JEL Classification: G24

Suggested Citation

Clarke, Jonathan and Kim, Soohun and Lee, Kyuseok and Seo, Kyoungwon, A Structural Model of Analyst Forecasts: Applications to Forecast Informativeness and Dispersion (May 18, 2020). Available at SSRN: https://ssrn.com/abstract=3604705 or http://dx.doi.org/10.2139/ssrn.3604705

Jonathan Clarke (Contact Author)

Georgia Institute of Technology - Scheller College of Business ( email )

800 West Peachtree St.
Atlanta, GA 30308
United States
404-894-4929 (Phone)
404-894-6030 (Fax)

HOME PAGE: http://mgt.gatech.edu/directory/clarke.html

Soohun Kim

College of Business, Korea Advanced Institute of Science and Technology (KAIST) ( email )

85 Hoegiro Dongdaemun-Gu
Seoul 02455
Korea, Republic of (South Korea)

Kyuseok Lee

College of Business, Korea Advanced Institute of Science and Technology (KAIST) ( email )

85 Hoegiro, Dongdaemoon-gu
Seoul 02455
Korea, Republic of (South Korea)

Kyoungwon Seo

Seoul National University ( email )

Seoul
Korea, Republic of (South Korea)

HOME PAGE: http://https://sites.google.com/site/seo8240/

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