TY - JOUR
T1 - Earnings Forecasts and Price Efficiency after Earnings Realizations
T2 - Reduction in Information Asymmetry through Learning from Price*
AU - Gong, Guojin
AU - Qu, Hong
AU - Tarrant, Ian
N1 - Funding Information:
* Accepted by Jeffrey Hales. We thank the editor and two anonymous referees for helpful comments and suggestions. We thank the Smeal College of Business at Pennsylvania State University for financial support, Financial Trading System for allowing us to use its FTS trading software, and the LEMA Lab at Pennsylvania State University for allowing us to use its facilities. We appreciate helpful comments from Lucy Ackert, Orie Barron, Keith Crocker, Kai Du, Dan Givoly, Apoorv Gogar, Dana Hermanson, Steven Huddart, Brian Kluger, Tony Kwasnica, Brian Mittendorf, Velina Popova, Darren Roulstone, Kathy Rupar, Steven Schwartz, Bin Srinidhi, Jack Stecher, Shyam Sunder, Andrew Van Buskirk, Nathaniel Wilcox, Richard Young, and Ran Zhao. We thank participants for comments provided at the AAA 2016 Annual Meeting, 2016 Experimental Finance Meeting, 2017 ABO meeting, Ph.D. seminar on research methods, and brownbag seminar at Pennsylvania State University, brownbag seminar at Kennesaw State University, and research workshops at Chapman University, Florida State University, Ohio State University, Rutgers University, SUNY Bingham-ton, and the University of Texas at Arlington. † Corresponding author.
PY - 2020
Y1 - 2020
N2 - When information asymmetry is a major market friction, earnings forecasts can lead to higher price efficiency even after the information in forecasts completely dissipates upon earnings realizations. We show this in an experimental market that features information asymmetry (i.e., some traders possess differential private information). Earnings forecasts reduce information asymmetry and lead to prices that reflect a greater amount of private information. Traders can learn more about others' information from prices. This information learned from past prices continues to reduce information asymmetry and improve price efficiency even after earnings realizations. We contribute to the disclosure literature by showing the evidence that the learning-from-price effect amplifies the impact of public disclosure on price efficiency.
AB - When information asymmetry is a major market friction, earnings forecasts can lead to higher price efficiency even after the information in forecasts completely dissipates upon earnings realizations. We show this in an experimental market that features information asymmetry (i.e., some traders possess differential private information). Earnings forecasts reduce information asymmetry and lead to prices that reflect a greater amount of private information. Traders can learn more about others' information from prices. This information learned from past prices continues to reduce information asymmetry and improve price efficiency even after earnings realizations. We contribute to the disclosure literature by showing the evidence that the learning-from-price effect amplifies the impact of public disclosure on price efficiency.
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U2 - 10.1111/1911-3846.12615
DO - 10.1111/1911-3846.12615
M3 - Article
AN - SCOPUS:85096634105
JO - Contemporary Accounting Research
JF - Contemporary Accounting Research
SN - 0823-9150
ER -