来源:会计
主 题:Estimation Uncertainty and Expectation Formation ─ Evidence from Sell-side Security Analyst
主讲人: 申睿(香港中文大学(深圳))
协调人: 廖冠民
时 间:2019-06-14 10:00
地 点:明德商学楼712室
语 言:中英文
讲座摘要:
In this study we examine how estimation uncertainty affects expectation formation. We consider a setting in which agents do not know the parameter determining the joint distribution of the public signal and the variable of interest. Agents estimate the parameter with noise so that they can incorporate the public signal into their expectations. Because of the estimation uncertainty, even though the agents form rational expectation based on all existing information, there is a significant correlation between the ex post forecasting error and the magnitude of the public signal (i.e. sticky expectation). Using earnings forecasts issued by sell-side security analysts, we provide empirical evidence consistent with the predictions of the analytical framework. The evidence shows that the magnitude of underreaction increases with the degree of estimation uncertainty. Further analyses using machine-learning forecasts and individual analyst forecasts show that our results are economically significant and cannot be explained by any existing theories. Taken together, this paper suggests that it is important to consider estimation uncertainty in the expectation formation process.
主讲人简介:
Before joining CUHK SZ, Rui worked as an assistant professor at NTU Singapore and Rotterdam School of Management (RSM), Erasmus University. He has taught Intermediate Financial Accounting for Bachelor students, Financial Analysis and Equity Valuation for master students in finance and Accounting for non-business master students. His main research interests are in the area of heterogeneous interpretations of public accounting information, market anomaly and corporate decisions. His research has been published in The Accounting Review, Journal of Financial and Quantitative Analysis and Strategic Management Journal.
人大商学院新闻网版权与免责声明:
① 凡本网未注明其他出处的作品,版权均属于人大商学院,未经本网授权不得转载、摘编或利用其它方式使用上述作品。已经本网授权使用作品的,应在授权范围内使用,并注明“来源:人大商学院”。违反上述声明者,本网将追究其相关责任。
② 凡本网注明其他来源的作品,均转载自其它媒体,转载目的在于传递更多信息,并不代表本网对其负责。
③ 有关作品内容、版权和其它问题请与本网联系。
※ 联系方式:中国人民大学商学院宣传信息事务办公室 邮箱:media@rmbs.ruc.edu.cn