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The Variance Ratio Test with Stable Paretian Errors

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  • Y. K. TSE
  • X. B. ZHANG

Abstract

This paper examines the distribution of the overlapping variance ratio (OVR) statistic when the errors are distributed with thick tails as described by the family of stable Paretian distributions. The asymptotic distribution of the OVR statistic, which depends on the characteristic exponent, can be estimated using simulation. It is found that the convergence of the distribution of the OVR statistic to its asymptotic limit is extremely slow. Thus, the asymptotic results will not be able to provide any useful approximation in finite samples. To facilitate the OVR statistic as a test for the random walk hypothesis, the tail quantiles are estimated for several finite sample sizes.

Suggested Citation

  • Y. K. Tse & X. B. Zhang, 2002. "The Variance Ratio Test with Stable Paretian Errors," Journal of Time Series Analysis, Wiley Blackwell, vol. 23(1), pages 117-126, January.
  • Handle: RePEc:bla:jtsera:v:23:y:2002:i:1:p:117-126
    DOI: 10.1111/1467-9892.01664
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    Cited by:

    1. Donald Brown & Rustam Ibragimov, 2005. "Sign Tests for Dependent Observations and Bounds for Path-Dependent Options," Yale School of Management Working Papers amz2581, Yale School of Management, revised 01 Jul 2005.
    2. Donald Brown & Rustam Ibragimov, 2005. "Sign Tests for Dependent Observations and Bounds for Path-Dependent Options," Yale School of Management Working Papers amz2581, Yale School of Management, revised 01 Jul 2005.
    3. Donald J. Brown & Rustam Ibragimov, 2005. "Sign Tests for Dependent Observations and Bounds for Path-Dependent Options," Cowles Foundation Discussion Papers 1518, Cowles Foundation for Research in Economics, Yale University.

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