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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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    References listed on IDEAS

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    Cited by:

    1. David Iselin & Boriss Siliverstovs, 2013. "Using Newspapers for Tracking the Business Cycle," KOF Working papers 13-337, KOF Swiss Economic Institute, ETH Zurich.
    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.

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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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