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Media Sentiment and UK Stock Returns

Author

Listed:
  • Nicky J. Ferguson

    (Durham Business School)

  • Jie Michael Guo

    (Durham Business School)

  • Nicky Herbert Y.T. Lam

    (Renmin University of China)

  • Dennis Philip

    (Durham Business School)

Abstract

This paper is the first to determine the effect that media sentiment has on stock returns for UK companies and tests whether there is any return predictability contained in the UK media sentiment data. We show that measures of positive and negative media sentiment have significant relationships with stock returns on the day news articles are published and that there is return predictability inherent in negative media sentiment the day following publication of media articles. We construct a news- based trading strategy to demonstrate the application of these results that earns significant positive abnormal returns.

Suggested Citation

  • Nicky J. Ferguson & Jie Michael Guo & Nicky Herbert Y.T. Lam & Dennis Philip, 2011. "Media Sentiment and UK Stock Returns," Working Papers 2011_06, Durham University Business School.
  • Handle: RePEc:dur:durham:2011_06
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    File URL: http://dro.dur.ac.uk/10346
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    References listed on IDEAS

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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. Alexander Dyck & Natalya Volchkova & Luigi Zingales, 2008. "The Corporate Governance Role of the Media: Evidence from Russia," Journal of Finance, American Finance Association, vol. 63(3), pages 1093-1135, June.
    3. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    4. Andrea Frazzini, 2006. "The Disposition Effect and Underreaction to News," Journal of Finance, American Finance Association, vol. 61(4), pages 2017-2046, August.
    5. Elizabeth Demers & Clara Vega, 2008. "Soft information in earnings announcements: news or noise?," International Finance Discussion Papers 951, Board of Governors of the Federal Reserve System (U.S.).
    6. 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.
    7. 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.
    8. 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.
    9. Alessandro Carretta & Vincenzo Farina & Duccio Martelli & Franco Fiordelisi & Paola Schwizer, 2011. "The Impact of Corporate Governance Press News on Stock Market Returns," European Financial Management, European Financial Management Association, vol. 17(1), pages 100-119, January.
    10. Shefrin, Hersh & Statman, Meir, 1985. "The Disposition to Sell Winners Too Early and Ride Losers Too Long: Theory and Evidence," Journal of Finance, American Finance Association, vol. 40(3), pages 777-790, July.
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    Cited by:

    1. Siganos, Antonios, 2013. "Google attention and target price run ups," International Review of Financial Analysis, Elsevier, vol. 29(C), pages 219-226.

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    More about this item

    Keywords

    media sentiment; stock returns; textual analysis; news-based trading strategy;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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