Asai, ManabuMcAleer, Michael2023-06-182023-06-1820162341-2356https://hdl.handle.net/20.500.14352/27597The paper considers various extended asymmetric multivariate conditional volatility models, and derives appropriate regularity conditions and associated asymptotic theory. This enables checking of internal consistency and allows valid statistical inferences to be drawn based on empirical estimation. For this purpose, we use an underlying vector random coefficient autoregressive process, for which we show the equivalent representation for the asymmetric multivariate conditional volatility model, to derive asymptotic theory for the quasi-maximum likelihood estimator. As an extension, we develop a new multivariate asymmetric long memory volatility model, and discuss the associated asymptotic properties.engAtribución-NoComercial-CompartirIgual 3.0 Españahttps://creativecommons.org/licenses/by-nc-sa/3.0/es/Asymptotic Theory for Extended Asymmetric Multivariate GARCH Processestechnical reporthttps://www.ucm.es/icaeopen accessC13C32C58Multivariate conditional volatilityVector random coefficient autoregressive processAsymmetryLong memoryDynamic conditional correlationsRegularity conditionsAsymptotic properties.Econometría (Economía)5302 Econometría