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

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.

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