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Volume, Volatility and Public News Announcements

Listed author(s):
  • Tim Bollerslev

    ()

    (Duke University, NBER and CREATES)

  • Jia Li

    ()

    (Duke University)

  • Yuan Xue

    ()

    (Duke University)

Registered author(s):

    We provide new empirical evidence for the way in which financial markets process information. Our results are based on high-frequency intraday data along with new econometric techniques for making inference on the relationship between trading intensity and spot volatility around public news announcements. Consistent with the predictions derived from a theoretical model in which investors agree to disagree, our estimates for the intraday volume-volatility elasticity around the most important news announcements are systematically below unity. Our elasticity estimates also decrease significantly with measures of disagreements in beliefs, economic uncertainty, and textual-based sentiment, further highlighting the key role played by differences-of-opinion.

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    File URL: ftp://ftp.econ.au.dk/creates/rp/16/rp16_19.pdf
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    Paper provided by Department of Economics and Business Economics, Aarhus University in its series CREATES Research Papers with number 2016-19.

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    Length: 44
    Date of creation: 23 Jun 2016
    Handle: RePEc:aah:create:2016-19
    Contact details of provider: Web page: http://www.econ.au.dk/afn/

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