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Word power: A new approach for content analysis


  • Jegadeesh, Narasimhan
  • Wu, Di


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.

Suggested Citation

  • Jegadeesh, Narasimhan & Wu, Di, 2013. "Word power: A new approach for content analysis," Journal of Financial Economics, Elsevier, vol. 110(3), pages 712-729.
  • Handle: RePEc:eee:jfinec:v:110:y:2013:i:3:p:712-729 DOI: 10.1016/j.jfineco.2013.08.018

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    References listed on IDEAS

    1. Tinic, Seha M, 1988. " Anatomy of Initial Public Offerings of Common Stock," Journal of Finance, American Finance Association, vol. 43(4), pages 789-822, September.
    2. Kathleen Weiss Hanley, 2010. "The Information Content of IPO Prospectuses," Review of Financial Studies, Society for Financial Studies, vol. 23(7), pages 2821-2864, July.
    3. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    4. Werner Antweiler & Murray Z. Frank, 2004. "Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards," Journal of Finance, American Finance Association, vol. 59(3), pages 1259-1294, June.
    5. Tim Loughran & Bill Mcdonald, 2011. "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks," Journal of Finance, American Finance Association, vol. 66(1), pages 35-65, February.
    6. Rock, Kevin, 1986. "Why new issues are underpriced," Journal of Financial Economics, Elsevier, vol. 15(1-2), pages 187-212.
    7. Feng Li, 2010. "The Information Content of Forward-Looking Statements in Corporate Filings-A Naïve Bayesian Machine Learning Approach," Journal of Accounting Research, Wiley Blackwell, vol. 48(5), pages 1049-1102, December.
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    Cited by:

    1. Keim, Donald B & Massa, Massimo & von Beschwitz, Bastian, 2015. "First to “Read” the News: News Analytics and Institutional Trading," CEPR Discussion Papers 10534, C.E.P.R. Discussion Papers.
    2. Buehlmaier, Matthias M. M. & Zechner, Josef, 2016. "Financial media, price discovery, and merger arbitrage," CFS Working Paper Series 551, Center for Financial Studies (CFS).
    3. repec:eee:pacfin:v:43:y:2017:i:c:p:151-172 is not listed on IDEAS
    4. Ahmed, Yousry & Elshandidy, Tamer, 2016. "The effect of bidder conservatism on M&A decisions: Text-based evidence from US 10-K filings," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 176-190.
    5. Ahmad, Khurshid & Han, JingGuang & Hutson, Elaine & Kearney, Colm & Liu, Sha, 2016. "Media-expressed negative tone and firm-level stock returns," Journal of Corporate Finance, Elsevier, vol. 37(C), pages 152-172.
    6. Chouliaras, Andreas, 2015. "Institutional Investors, Annual Reports, Textual Analysis and Stock Returns: Evidence from SEC EDGAR 10-K and 13-F Forms," MPRA Paper 65875, University Library of Munich, Germany.
    7. Bianconi, Marcelo & Hua, Xiaxin & Tan, Chih Ming, 2015. "Determinants of systemic risk and information dissemination," International Review of Economics & Finance, Elsevier, vol. 38(C), pages 352-368.
    8. Chouliaras, Andreas, 2016. "The Effect of Infomation on Financial Markets: A Survey," MPRA Paper 71396, University Library of Munich, Germany.
    9. repec:eee:jbfina:v:84:y:2017:i:c:p:25-40 is not listed on IDEAS
    10. Chouliaras, Andreas, 2015. "High Frequency Newswire Textual Sentiment: Evidence from international stock markets during the European Financial Crisis," MPRA Paper 62524, University Library of Munich, Germany.
    11. Li Guo & Yubo Tao & Jun Tu, 2017. "Media Network and Return Predictability," Papers 1703.02715,, revised Dec 2017.
    12. Ming Jia & Li Tong & P. V. Viswanath & Zhe Zhang, 2016. "Word Power: The Impact of Negative Media Coverage on Disciplining Corporate Pollution," Journal of Business Ethics, Springer, vol. 138(3), pages 437-458, October.
    13. Matthew Gentzkow & Bryan T. Kelly & Matt Taddy, 2017. "Text as Data," NBER Working Papers 23276, National Bureau of Economic Research, Inc.
    14. Chouliaras, Andreas, 2015. "The Pessimism Factor: SEC EDGAR Form 10-K Textual Analysis and Stock Returns," MPRA Paper 65585, University Library of Munich, Germany.

    More about this item


    Content analysis; Lexicons; Term weighting;

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G19 - Financial Economics - - General Financial Markets - - - Other


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