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On the Robustness of Ljung-Box and McLeod-Li Q Tests: A Simulation Study

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  • Yi-Ting Chen

    (Sun Yat-Sen Institute for Social Sciences and Philosphy, Academia Sinica)

Abstract

In financial time series analysis, serial correlations and the volatility clustering effect of asset returns are commonly checked by Ljung-Box and McLeod-Li Q tests and filtered by ARMA-GARCH models. However, this simulation study shows that both the size and power performance of these two tests are not robust to heavily tailed data. Further, these Q tests may reject processes without ARMA-GARCH structures simply because of nonlinearity and conditionally heteroskedastic higher-order moments. These results imply that, to avoid misleading interpretations on time series data, these two tests should be used with care in practical applications.

Suggested Citation

  • Yi-Ting Chen, 2002. "On the Robustness of Ljung-Box and McLeod-Li Q Tests: A Simulation Study," Economics Bulletin, AccessEcon, vol. 3(17), pages 1-10.
    • Handle: RePEc:ebl:ecbull:eb-02c40014
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    References listed on IDEAS

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    Cited by:

    1. Abdou Kâ Diongue & Dominique Guegan, 2008. "The k-factor Gegenbauer asymmetric Power GARCH approach for modelling electricity spot price dynamics," Post-Print halshs-00259225, HAL.

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    Keywords

    ARMA-GARCH;

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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