Modelling multivariate volatilies via conditionally uncorrelated components

Simple item page
dc.creatorFan, Jianqing
dc.creatorWang, Mingjin
dc.creatorYao, Qiwei
dc.date2005-06-02
dc.date.accessioned2026-07-07T08:06:58Z
dc.date.available2026-07-07T08:06:58Z
dc.descriptionWe propose to model multivariate volatility processes based on the newly defined conditionally uncorrelated components (CUCs). This model represents a parsimonious representation for matrix-valued processes. It is flexible in the sense that we may fit each CUC with any appropriate univariate volatility model. Computationally it splits one high-dimensional optimization problem into several lower-dimensional subproblems. Consistency for the estimated CUCs has been established. A bootstrap test is proposed for testing the existence of CUCs. The proposed methodology is illustrated with both simulated and real data sets.
dc.description37 pages, 8 figures
dc.identifierhttps://arxiv.org/abs/math/0506027
dc.identifierhttp://arxiv.org/abs/math/0506027
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/130786
dc.subjectStatistics Theory
dc.subject62H12
dc.titleModelling multivariate volatilies via conditionally uncorrelated components
dc.typetext

Files

Collections

arXiv