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Garch And Volume Effects In The Australian Stock Markets

Author

Listed:
  • JINGLIANG XIAO

    (Department of Econometrics and Business, Statistics/Centre of Policy Studies, Monash University, Australia)

  • ROBERT D BROOKS

    (Department of Econometrics and Business Statistics, Monash University, Australia)

  • WING-KEUNG WONG

    (Department of Economics, National University of Singapore, Singapore)

Abstract

This paper explores the relationship between volume and volatility in the Australian Stock Market in the context of a generalized autoregressive conditional heteroskedasticity (GARCH) model. In contrast to other studies who only examine the interaction of GARCH and volume effects on a small number of stocks, we examine these effects on the entire available data for the Australian All Ordinaries Index. We also emphasize on the impact of firm size and trading volume. Our results indicate that GARCH model testing and estimation is impacted by firm size and trading volume. Specifically, our analysis produces the following major findings. First, generally, daily trading volume, used as a proxy for information arrival time, is shown to have significant explanatory power regarding the variance of daily returns. Second, the actively traded stocks which may have a larger number of information arrivals per day have a larger impact of volume on the variance of daily returns. Third, we find that low trading volume and small firm lead to a higher persistence of GARCH effects in the estimated models. Fourth, unlike the elimination effect for the top most active stocks, in general, the elimination of both autoregressive conditional heteroskedasticity (ARCH) and GARCH effects by introducing the volume variable on all other stocks on average is not as much as that for the top most active stocks. Fifth, the elimination of both ARCH and GARCH effects by introducing the volume variable is higher for stocks in the largest volume and/or the largest market capitalization quartile group. Our findings imply that the earlier findings in the literature were not a statistical fluke and that, unlike most anomalies, the volume effect on volatility is not likely to be eliminated after its discovery. In addition, our findings reject the pure random walk hypothesis for stock returns.

Suggested Citation

  • Jingliang Xiao & Robert D Brooks & Wing-Keung Wong, 2009. "Garch And Volume Effects In The Australian Stock Markets," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 5(01), pages 1-20.
  • Handle: RePEc:wsi:afexxx:v:05:y:2009:i:01:n:s2010495209500055
    DOI: 10.1142/S2010495209500055
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    References listed on IDEAS

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    5. Lam, Kin & Liu, Taisheng & Wong, Wing-Keung, 2010. "A pseudo-Bayesian model in financial decision making with implications to market volatility, under- and overreaction," European Journal of Operational Research, Elsevier, vol. 203(1), pages 166-175, May.
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    More about this item

    Keywords

    GARCH models; volatility; volume; Australian stock market; individual stock; G11; G14;

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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