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Annastiina, Silvennoinen ; Anthony D, Hall ; Timo, Terasvirta ; Annastiina, Silvennoinen ; Anthony, Hall ; Timo, Teräsvirta. (2021) Four Australian Banks and the Multivariate Time-Varying Smooth Transition Correlation GARCH model.
In: CREATES Research Papers. RePEc:aah:create:2021-13.
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B Simulations of test statistics B.1 Tests of GARCH equations The test for slow moving baseline volatility has a statistic whose distribution is sensitive to the high frequency, GARCH, volatility. For this reason, one cannot use the asymptotic distribution, rather the distribution must be generated via simulation. Further, Silvennoinen and TeraÌsvirta (2016) showed that the size of the test is distorted if the GARCH parameterisation deviates from the true one. For this reason a few alternative approaches to estimate the GARCH parameters, and especially the persistence, are investigated. It should be noted that estimating GARCH without taking the nonstationarity into account will yield overestimated persistence, thereby impacting the test statistic distribution and thus rendering the test outcomes unreliable. These estimates are given in Table 3.
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