Earnings Forecasts and Price Efficiency After Earnings Realizations: Reduction in Information Asymmetry through Learning from Price Guojin Gong, Hong Qu, and Ian Tarrant
Contemporary Accounting Research Vol. 38, No. 1 (March 2021), pp. 654-675
Overview Financial analysts and corporate managers frequently forecast earnings prior to their realization. Do public forecasts matter after the facts are known? We find that when information asymmetry is a major market friction, earnings forecasts can lead to higher price efficiency even after the earnings become public knowledge. In an experimental market characterized by information asymmetry—that is, some traders have private information—earnings forecasts reduce information asymmetry and lead to prices that reflect a greater amount of private information. Information aggregated in past prices continues to reduce information asymmetry and improve price efficiency even after earnings realizations. We contribute to the disclosure literature by showing that the learning-from-price effect amplifies the impact of public disclosure on price efficiency.
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