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Testing for independence in heavy-tailed time series using the codifference function

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  • Rosadi, Dedi

Abstract

In this paper, we consider a Portmanteau-type test of randomness for symmetric [alpha] stable random variables with exponent 0

Suggested Citation

  • Rosadi, Dedi, 2009. "Testing for independence in heavy-tailed time series using the codifference function," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4516-4529, October.
    • Handle: RePEc:eee:csdana:v:53:y:2009:i:12:p:4516-4529
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    References listed on IDEAS

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    1. Piotr S. Kokoszka & Murad S. Taqqu, 1994. "Infinite Variance Stable Arma Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 15(2), pages 203-220, March.
    2. Runde, Ralf, 1997. "The asymptotic null distribution of the Box-Pierce Q-statistic for random variables with infinite variance an application to German stock returns," Journal of Econometrics, Elsevier, vol. 78(2), pages 205-216, June.
    3. Hesse, C. H., 1990. "Rates of convergence for the empirical distribution function and the empirical characteristic function of a broad class of linear processes," Journal of Multivariate Analysis, Elsevier, vol. 35(2), pages 186-202, November.
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    Cited by:

    1. Karling, Maicon J. & Lopes, Sílvia R.C. & de Souza, Roberto M., 2023. "Multivariate α-stable distributions: VAR(1) processes, measures of dependence and their estimations," Journal of Multivariate Analysis, Elsevier, vol. 195(C).
    2. Chen, Zhanshou & Jin, Zi & Tian, Zheng & Qi, Peiyan, 2012. "Bootstrap testing multiple changes in persistence for a heavy-tailed sequence," Computational Statistics & Data Analysis, Elsevier, vol. 56(7), pages 2303-2316.

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