Show simple item record

dc.contributor.authorHenze, Norbert
dc.contributor.authorMeintanis, Simos G.
dc.contributor.authorJimenez-Gamero, M. Dolores
dc.date.accessioned2019-05-22T08:42:09Z
dc.date.available2019-05-22T08:42:09Z
dc.date.issued2019
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. [https://doi.org/10.1017/S0266466618000154]en_US
dc.identifier.issn0266-4666
dc.identifier.issn1469-4360 (Online)
dc.identifier.urihttp://hdl.handle.net/10394/32418
dc.identifier.urihttps://doi.org/10.1017/S0266466618000154
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.language.isoenen_US
dc.publisherCambridge Univ Pressen_US
dc.titleCharacterizations of multinormality and corresponding tests of fit, including for GARCH modelsen_US
dc.typeArticleen_US
dc.contributor.researchID21262977 - Meintanis, Simos George


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record