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Intra-day Patterns in the Returns, Bidask Spereads, and Trading Volume of Stocks Traded on the New York Stock Exchange

Author

Listed:
  • Chris Brooks

    (ICMA Centre, University of Reading)

  • Melvin. J. Hinich

    (University of Texas at Austin)

  • Douglas M. Patterson

    (Virginia Tech)

Abstract

Much research has demonstrated the existence of patterns in high-frequency equity returns, return volatility, bid-ask spreads and trading volume. In this paper, we employ a new test for detecting periodicities based on a signal coherence function. The technique is applied to the returns, bid-ask spreads, and trading volume of thirty stocks traded on the NYSE. We are able to confirm previous findings of an inverse J-shaped pattern in spreads and volume through the day. We also demonstrate that such intraday effects dominate day of the week seasonalities in spreads and volumes, while there are virtually no significant periodicities in the returns data. Our approach can also leads to a natural method for forecasting the time series, and we find that, particularly in the case of the volume series, the predictions are considerably more accurate than those from naïve methods.

Suggested Citation

  • Chris Brooks & Melvin. J. Hinich & Douglas M. Patterson, 2003. "Intra-day Patterns in the Returns, Bidask Spereads, and Trading Volume of Stocks Traded on the New York Stock Exchange," ICMA Centre Discussion Papers in Finance icma-dp2003-14, Henley Business School, University of Reading.
    • Handle: RePEc:rdg:icmadp:icma-dp2003-14
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    File URL: http://www.icmacentre.ac.uk/pdf/discussion/DP2003-14.pdf
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    References listed on IDEAS

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    Cited by:

    1. Andreas Park, 2008. "Bid-Ask Spreads and Volume:The Role of Trade Timing," Working Papers tecipa-309, University of Toronto, Department of Economics.
    2. I. Marta Miranda García & María‐Jesús Segovia‐Vargas & Usue Mori & José A. Lozano, 2023. "Early prediction of Ibex 35 movements," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1150-1166, August.
    3. F. DePenya & L. Gil-Alana, 2006. "Testing of nonstationary cycles in financial time series data," Review of Quantitative Finance and Accounting, Springer, vol. 27(1), pages 47-65, August.
    4. Katya Malinova & Andreas Park, 2009. "Intraday Trading Patterns: The Role of Timing," Working Papers tecipa-365, University of Toronto, Department of Economics.

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    More about this item

    Keywords

    spectral analysis; peridocities; seasonality; intraday paterns; bid-ask spread; trading volume;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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