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News aggregators, volatility and the stock market

Author

Listed:
  • Hans Byström

    (Department of Economics, Lund University)

Abstract

In this paper we employ the news aggregator Google News to demonstrate a strong link between the volatility in the stock market and the amount of news available to market participants. The paper also highlights some other areas, in finance and elsewhere, where news aggregators could be useful.

Suggested Citation

  • Hans Byström, 2009. "News aggregators, volatility and the stock market," Economics Bulletin, AccessEcon, vol. 29(4), pages 2673-2682.
    • Handle: RePEc:ebl:ecbull:eb-09-00625
    as

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    File URL: http://www.accessecon.com/Pubs/EB/2009/Volume29/EB-09-V29-I4-P20.pdf
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    References listed on IDEAS

    as
    1. Berry, Thomas D & Howe, Keith M, 1994. "Public Information Arrival," Journal of Finance, American Finance Association, vol. 49(4), pages 1331-1346, September.
    2. Mitchell, Mark L & Mulherin, J Harold, 1994. "The Impact of Public Information on the Stock Market," Journal of Finance, American Finance Association, vol. 49(3), pages 923-950, July.
    3. Ederington, Louis H & Lee, Jae Ha, 1993. "How Markets Process Information: News Releases and Volatility," Journal of Finance, American Finance Association, vol. 48(4), pages 1161-1191, September.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Yang, Xiaolan & Zhu, Yu & Cheng, Teng Yuan, 2020. "How the individual investors took on big data: The effect of panic from the internet stock message boards on stock price crash," Pacific-Basin Finance Journal, Elsevier, vol. 59(C).
    2. Byström, Hans, 2016. "Language, news and volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 42(C), pages 139-154.

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    More about this item

    Keywords

    news aggregator; volatility;

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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