Publication Type
Journal Article
Version
submittedVersion
Publication Date
8-2022
Abstract
This paper examines expected return information embedded in investors' information acquisition activity. Using a novel dataset containing investors' access of company filings through SEC's EDGAR system, we reverse engineer their expectations over future payoffs and show that the abnormal number of IPs searching for firms' financial statements strongly predict future returns. The return predictability stems from investors allocating more effort to firms with improving fundamentals and following exogeneous shock to underpricing. A long-short portfolio based on our measure of information acquisition activity generate monthly abnormal return of 80 basis points and does not reverse over the long-run.. In addition, the return predictability is stronger among firms with larger and lengthy financial filings that are more costly to process. Collectively, these findings support theoretical predictions that costly information acquisition reveals the value of information.
Keywords
Information Acquisition, EDGAR Search, Return Predictability, Market Efficiency
Discipline
Finance and Financial Management | Portfolio and Security Analysis
Research Areas
Finance
Publication
Journal of Economic Dynamics and Control
Volume
141
First Page
1
Last Page
20
ISSN
0165-1889
Identifier
10.1016/j.jedc.2022.104384
Publisher
Elsevier
Citation
LI, Frank Weikai and SUN, Chengzhu.
Information acquisition and expected returns: Evidence from EDGAR search traffic. (2022). Journal of Economic Dynamics and Control. 141, 1-20.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/5322
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1016/j.jedc.2022.104384