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Modelling multivariate volatilities via conditionally uncorrelated components

Fan, Jianqing, Wang, Mingjin and Yao, Qiwei (2008) Modelling multivariate volatilities via conditionally uncorrelated components. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 70 (4). pp. 679-702. ISSN 1369-7412

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Abstract

We propose to model multivariate volatility processes on the basis of the newly defined conditionally uncorrelated components (CUCs). This model represents a parsimonious representation for matrix-valued processes. It is flexible in the sense that each CUC may be fitted separately 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 method is proposed for testing the existence of CUCs. The methodology proposed is illustrated with both simulated and real data sets.

Item Type: Article
Official URL: http://www.rss.org.uk/main.asp?page=1711
Additional Information: © 2008 The Royal Statistical Society
Library of Congress subject classification: H Social Sciences > HA Statistics
Sets: Collections > Economists Online
Departments > Statistics
Rights: http://www.lse.ac.uk/library/usingTheLibrary/academicSupport/OA/depositYourResearch.aspx
Funders: National Science Foundation, National Science Foundation, Chinese National Science Foundation, Engineering and Physical Sciences Research Council, Chinese National Science Foundation, Engineering and Physical Sciences Research Council, Engineering and Physical Sciences Research Council
Projects: DMS-0355179, DMS-0704337, 10628104, GR/R97436, 70201007, GR/R97436, EP/C549058
Date Deposited: 18 Feb 2009 16:27
URL: http://eprints.lse.ac.uk/22875/

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