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Volume, Volatility and Public News Announcements

Author

Listed:
  • Tim Bollerslev

    (Duke University, NBER and CREATES)

  • Jia Li

    (Duke University)

  • Yuan Xue

    (Duke University)

Abstract
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.

Suggested Citation

  • Tim Bollerslev & Jia Li & Yuan Xue, 2016. "Volume, Volatility and Public News Announcements," CREATES Research Papers 2016-19, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:create:2016-19
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    References listed on IDEAS

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    More about this item

    Keywords

    Differences-of-opinion; high-frequency data; jumps; macroeconomic news announcements; trading volume; stochastic volatility; economic uncertainty; textual sentiment;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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