Abstract
This research paper investigates the role of managerial sentiment in predicting future stockreturns by constructing firm characteristics based on sentiment words. Through the analysis of all Securities and Exchange filings submitted by publicly traded companies from 2001 to 2022, this study demonstrates that certain sentiment words provide a robust and significant cross-sectional predictor of future monthly stock returns. The paper utilizes a unique ap- proach by leveraging a long time frame and analyzing all available filings. This allows for a comprehensive analysis of the impact of managerial sentiment on stock returns, highlighting the importance of sentiment analysis in financial markets.
Committee Chair
Guofu Zhou
Committee Members
Xing Huang, Xiumin Martin,
Degree
Doctor of Business Administration (DBA)
Author's Department
Finance
Document Type
Dissertation
Date of Award
Spring 5-15-2023
Language
English (en)
Recommended Citation
Horn, James, "Edgar 10X filings’ sentiment and predicting a firm’s stock return" (2023). Olin Business School Theses and Dissertations. 15.
The definitive version is available at https://doi.org/10.7936/kr11-s473