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Generalized variance ratio tests in the presence of statistical dependence

  • Periklis Kougoulis

    (University of Essex)

  • John C. Nankervis

    (University of Essex)

  • Jerry Coakley

    (University of Essex)

We develop extensions of the variance-ratio statistic for testing the hypothesis a time series is uncorrelated and investigate their finite-sample performance. The tests employ an estimator of the asymptotic covariance matrix of the sample autocorrelations that is consistent under the null for general classes of innovations including EGARCH and non-MDS processes. Monte Carlo experiments show that our tests have better finite-sample size and power properties than the standard variance-ratio tests in experiments using time series generated by EGARCH and non-MDS processes

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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2006 with number 180.

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Date of creation: 04 Jul 2006
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Handle: RePEc:sce:scecfa:180
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