Anomalies, Management Expectations, and Stock Returns

March 22, 2022        

Theme: Anomalies, Management Expectations, and Stock Returns

Speaker: Dexin Zhou (Baruch College, CUNY)

Host: Yan Li (Associate Dean of School of Accounting, SWUFE)

Time: 10:0011:30am, March 28, 2022, Tuesday

Place: Tencent ID983-044-7835

Sponsor: School of Accounting, SWUFE

Introduction of the speaker:

Dr. Dexin Zhou is currently an Assistant Professor of Economics and Finance at Baruch College, City University of New York. His work examines the roles of media, social networks, and institutional investors in financial markets. His research has been published in top finance and accounting journals, including Journal of Financial Economics, Review of Financial Studies, and Accounting Review, and mentioned by Wall Street Journal, The Economist, Financial Times, and Harvard Forum Law School Forum on Corporate Governance. He obtained a Ph.D. in Finance from Emory University and a BA in Mathematics from Bard College.


We investigate the extent to which managers incorporate public information in their earnings expectations and its implications for capital market efficiency. We find that management earnings forecasts are biased upward (downward) for stocks that are over-valued (undervalued) based on anomaly signals. On average, these biases are more severe than those in consensus analyst forecasts. Anomaly returns are higher (lower) when managers issue forecasts that update the market in the direction that is consistent (inconsistent) with the anomaly information. This return difference is about two percent in the month after anomaly portfolio formation and persists for over 12 months. Consistent with managers' biases exacerbating anomaly-related mispricing, the return difference is more salient during high sentiment periods and when there are firm news events.

Welcome faculty and students to attend!

Previous:Unsolved uncertainty and corporate voluntary disclosures
Next:Bank Institutions and Hidden Loan Loss: Evidence from Mandatory Shift to Expected Credit Loss Provisioning in China