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Return predictability following different drivers of large price changes

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  • Patel, Vinay
  • Michayluk, David

Abstract

This study uniquely examines return predictability following different drivers of large price changes. We use several novel features of the Australian information generation environment to overcome identification issues of large price changes inherent in earlier studies. In contrast to prior results, we find that large price changes are permanent when they are driven by public information consistent with the semi-strong efficient markets hypothesis and also when driven by private information. For large price changes which do not correspond with information, we show that investors could profit from the subsequent over-reaction in returns.

Suggested Citation

  • Patel, Vinay & Michayluk, David, 2016. "Return predictability following different drivers of large price changes," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 202-214.
    • Handle: RePEc:eee:finana:v:45:y:2016:i:c:p:202-214
    DOI: 10.1016/j.irfa.2016.03.004
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    References listed on IDEAS

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    Cited by:

    1. Bohmann, Marc & Michayluk, David & Patel, Vinay & Walsh, Kathleen, 2019. "Liquidity and earnings in event studies: Does data granularity matter?," Pacific-Basin Finance Journal, Elsevier, vol. 54(C), pages 118-131.
    2. Hadhri, Sinda & Ftiti, Zied, 2017. "Stock return predictability in emerging markets: Does the choice of predictors and models matter across countries?," Research in International Business and Finance, Elsevier, vol. 42(C), pages 39-60.

    More about this item

    Keywords

    Return predictability; Large price change; Information; Liquidity;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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