Citations (7)



Word Power: A New Approach for Content Analysis

Narasimhan Jegadeesh

Emory University - Department of Finance

Andrew Di Wu

University of Pennsylvania - The Wharton School

July 1, 2013

Journal of Financial Economics (JFE), Forthcoming
AFA 2012 Chicago Meetings Paper

We present a new approach for content analysis to quantify document tone. We find a significant relation between our measure of the tone of 10-Ks and market reaction for both negative and positive words. We also find that the appropriate choice of term weighting in content analysis is at least as important as, and perhaps more important than, a complete and accurate compilation of the word list. Furthermore, we show that our approach circumvents the need to subjectively partition words into positive and negative word lists. Our approach reliably quantifies the tone of IPO prospectuses as well, and we find that the document score is negatively related to IPO underpricing.

Number of Pages in PDF File: 50

Keywords: Content analysis, 10-Ks, Filing date, term-weighting

JEL Classification: G10, G14

Open PDF in Browser Download This Paper

Date posted: March 18, 2011 ; Last revised: July 15, 2013

Suggested Citation

Jegadeesh, Narasimhan and Wu, Andrew Di, Word Power: A New Approach for Content Analysis (July 1, 2013). Journal of Financial Economics (JFE), Forthcoming; AFA 2012 Chicago Meetings Paper. Available at SSRN: http://ssrn.com/abstract=1787273 or http://dx.doi.org/10.2139/ssrn.1787273

Contact Information

Narasimhan Jegadeesh (Contact Author)
Emory University - Department of Finance ( email )
Atlanta, GA 30322-2710
United States
Di Wu
University of Pennsylvania - The Wharton School ( email )
3641 Locust Walk
Philadelphia, PA 19104-6365
United States

Feedback to SSRN

Paper statistics
Abstract Views: 6,972
Downloads: 1,615
Download Rank: 7,103
Citations:  7

© 2016 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright   Contact Us
This page was processed by apollobot1 in 0.250 seconds