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Do Newspaper Articles Predict Aggregate Stock Returns?

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  • Ammann, Manuel
  • Frey, Roman
  • Verhofen, Michael

Abstract

We analyze whether newspaper content can predict aggregate future stock returns. Our study is based on articles published in the Handelsblatt, a leading German financial newspaper, from July 1989 to March 2011. We summarize newspaper content in a systematic way by constructing word-count indices for a large number of words. Wordcount indices are instantly available and therefore potentially valuable financial indicators. Our main finding is that the predictive power of newspaper content has increased over time, particularly since 2000. We find that a cluster analysis approach increases the predictive power of newspaper articles substantially. To obtain optimal predictive power, we need at least seven clusters. Our analysis shows that newspaper content is a valuable predictor of future DAX returns in and out of sample.

Suggested Citation

  • Ammann, Manuel & Frey, Roman & Verhofen, Michael, 2012. "Do Newspaper Articles Predict Aggregate Stock Returns?," Working Papers on Finance 1204, University of St. Gallen, School of Finance.
    • Handle: RePEc:usg:sfwpfi:2012:04
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    1. Sanjiv R. Das & Mike Y. Chen, 2007. "Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web," Management Science, INFORMS, vol. 53(9), pages 1375-1388, September.
    2. Paul C. Tetlock, 2011. "All the News That's Fit to Reprint: Do Investors React to Stale Information?," The Review of Financial Studies, Society for Financial Studies, vol. 24(5), pages 1481-1512.
    3. Paul C. Tetlock, 2010. "Does Public Financial News Resolve Asymmetric Information?," The Review of Financial Studies, Society for Financial Studies, vol. 23(9), pages 3520-3557.
    4. John M. Griffin & Nicholas H. Hirschey & Patrick J. Kelly, 2011. "How Important Is the Financial Media in Global Markets?," The Review of Financial Studies, Society for Financial Studies, vol. 24(12), pages 3941-3992.
    5. Lily Fang & Joel Peress, 2009. "Media Coverage and the Cross‐section of Stock Returns," Journal of Finance, American Finance Association, vol. 64(5), pages 2023-2052, October.
    6. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "When machines read the news: Using automated text analytics to quantify high frequency news-implied market reactions," Journal of Empirical Finance, Elsevier, vol. 18(2), pages 321-340, March.
    7. Paul C. Tetlock & Maytal Saar‐Tsechansky & Sofus Macskassy, 2008. "More Than Words: Quantifying Language to Measure Firms' Fundamentals," Journal of Finance, American Finance Association, vol. 63(3), pages 1437-1467, June.
    8. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    9. George Bulkley & Renata Herrerias, 2005. "Does the Precision of News Affect Market Underreaction? Evidence from Returns Following Two Classes of Profit Warnings," European Financial Management, European Financial Management Association, vol. 11(5), pages 603-624, November.
    10. Jon R. Kettenring, 2006. "The Practice of Cluster Analysis," Journal of Classification, Springer;The Classification Society, vol. 23(1), pages 3-30, June.
    11. Joseph E. Engelberg & Christopher A. Parsons, 2011. "The Causal Impact of Media in Financial Markets," Journal of Finance, American Finance Association, vol. 66(1), pages 67-97, February.
    12. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    13. 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.
    14. repec:bla:jfinan:v:59:y:2004:i:3:p:1259-1294 is not listed on IDEAS
    15. Andreas Schrimpf & Michael Schröder & Richard Stehle, 2007. "Cross‐sectional Tests of Conditional Asset Pricing Models: Evidence from the German Stock Market," European Financial Management, European Financial Management Association, vol. 13(5), pages 880-907, November.
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    2. Dirk Ulbricht & Konstantin A. Kholodilin & Tobias Thomas, 2017. "Do Media Data Help to Predict German Industrial Production?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(5), pages 483-496, August.
    3. David Iselin & Boriss Siliverstovs, 2013. "Using Newspapers for Tracking the Business Cycle," KOF Working papers 13-337, KOF Swiss Economic Institute, ETH Zurich.

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    More about this item

    Keywords

    Word Count; Text Mining; Expected Returns; Tactical Asset Allocation.;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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