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Earnings Forecasts and Price Efficiency after Earnings Realizations: Reduction in Information Asymmetry through Learning from Price *
Author(s) -
Gong Guojin,
Qu Hong,
Tarrant Ian
Publication year - 2020
Publication title -
contemporary accounting research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.769
H-Index - 99
eISSN - 1911-3846
pISSN - 0823-9150
DOI - 10.1111/1911-3846.12615
Subject(s) - earnings , information asymmetry , private information retrieval , economics , asymmetry , public information , market efficiency , differential (mechanical device) , financial economics , monetary economics , econometrics , microeconomics , finance , statistics , mathematics , physics , public administration , quantum mechanics , political science , engineering , aerospace engineering
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.