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Trading volume, realized volatility and jumps in the Australian stock market

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  • Shahzad, Hassan
  • Duong, Huu Nhan
  • Kalev, Petko S.
  • Singh, Harminder

Abstract

We study the volume–volatility relation by splitting volume into the number of trades and the average trade size at individual and institutional level, and realized volatility into its continuous and jump components. We find that the number of trades is the most important variable driving realized volatility. The number of trades by the individual investors carries more explanatory power in explaining volatility compared to the number of trades by institutional investors. The average trade size cannot be entirely disregarded, though; its importance compared to the number of trades is limited. Order imbalance plays a minimal role in driving volatility.

Suggested Citation

  • Shahzad, Hassan & Duong, Huu Nhan & Kalev, Petko S. & Singh, Harminder, 2014. "Trading volume, realized volatility and jumps in the Australian stock market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 414-430.
    • Handle: RePEc:eee:intfin:v:31:y:2014:i:c:p:414-430
    DOI: 10.1016/j.intfin.2014.04.009
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    8. Zhang, Chris H. & Frijns, Bart, 2019. "Noise trading and informational efficiency," EconStor Preprints 198037, ZBW - Leibniz Information Centre for Economics.
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    More about this item

    Keywords

    Volatility; Information flow; Jump;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage

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