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dc.contributor.authorHenze, Norbert
dc.contributor.authorMeintanis, Simos G.
dc.contributor.authorJimenez-Gamero, M. Dolores
dc.identifier.citationHenze, N. et al. 2019. Characterizations of multinormality and corresponding tests of fit, including for GARCH models. Econometric theory, 35(3):510-546. []en_US
dc.identifier.issn1469-4360 (Online)
dc.description.abstractWe provide novel characterizations of multivariate normality that incorporate both the characteristic function and the moment generating function, and we employ these results to construct a class of affine invariant, consistent and easy-to-use goodness-of-fit tests for normality. The test statistics are suitably weighted L2-statistics, and we provide their asymptotic behavior both for i.i.d. observations as well as in the context of testing that the innovation distribution of a multivariate GARCH model is Gaussian. We also study the finite-sample behavior of the new tests and compare the new criteria with alternative existing testsen_US
dc.publisherCambridge Univ Pressen_US
dc.titleCharacterizations of multinormality and corresponding tests of fit, including for GARCH modelsen_US
dc.contributor.researchID21262977 - Meintanis, Simos George

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