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New Variance Ratio Tests to Identify Random Walk from the General Mean Reversion Model

Author

Listed:
  • Kin Lam

    (Department of Finance & Decision Sciences, Hong Kong Baptist University)

  • May Chun Mei Wong

    (Dental Public Health, The University of Hong Kong)

  • Wing-Keung Wong

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

Abstract

We develop some properties on the autocorrelation of the k-period returns for the general mean reversion (GMR) process in which the stationary component is not restricted to the AR(l) process but take the form of a general ARMA process. We then derive some properties of the GMR process and three new non-parametric tests comparing the relative variability of returns over different horizons to validate the GMR process as an alternative to random walk. We further examine the asymptotic properties of these tests which can then be applied to identify random walk models from the GMR processes.

Suggested Citation

  • Kin Lam & May Chun Mei Wong & Wing-Keung Wong, 2005. "New Variance Ratio Tests to Identify Random Walk from the General Mean Reversion Model," Departmental Working Papers wp0514, National University of Singapore, Department of Economics.
  • Handle: RePEc:nus:nusewp:wp0514
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    File URL: http://www.fas.nus.edu.sg/ecs/pub/wp/wp0514.pdf
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    References listed on IDEAS

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    More about this item

    Keywords

    mean reversion; variance ratio test; random walk; stock price; stock return;

    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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