Facultade de Fisioterapia

A new class of tests for multinormality with i.i.d. and garch data based on the empirical moment generating function

Henze, Norbert; Jiménez Gamero, María Dolores
Abstract:
We generalize a recent class of tests for univariate normality that are based on the empirical moment generating function to the multivariate setting, thus obtaining a class of affine invariant, consistent and easy-to-use goodness-of-fit tests for multinormality. The test statistics are suitably weighted L2 -statistics, and we provide their asymptotic behavior both for i.i.d. observations and in the context of testing that the innovation distribution of a multivariate GARCH model is Gaussian. We study the finite-sample behavior of the new tests, compare the criteria with alternative existing procedures, and apply the new procedure to a data set of monthly log returns.
Year:
2019
Type of Publication:
Article
Keywords:
Moment generating function Goodness-of-fit test Multivariate normality Gaussian GARCH model
Journal:
TEST
Volume:
28
Number:
2
Pages:
499-521
Month:
June
Note:
Q2 51/123 h-index 1,183 (JCR2018)
Comments:
MTM2014-55966-P and MTM2017-89422-P
DOI:
https://doi.org/10.1007/s11749-018-0589-z
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