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Table 1. Root mean squared errors for RGARCH model parameters when the noise distribution is N(0,1) and-estimates and QMLEs ofstandardized t3
Figure 1, which reports the efficiency of the estimators ofconfirms our conjecture since the latter is always worse than theunrestricted ML estimator that simultaneously estimatesfor fixed degrees of freedomν− ϑ1 ν relative to the Gaussian PMLE, η =1, whose pseudo-true values are indicated by thick dots.
Figure 1. Relative efficiency of t-based PMLE versus Gaussian PMLE.
Table 1. Monte Carlo experiment. True distribution: Laplace(GED(1.0)) T = 2000; NREPS = 10,000
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