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Modelling multivariate volatilities via conditionally uncorrelated components

Jianqing Fan Mingjin Wang Qiwei Yao

Statistics Theory and Methods mathscidoc:1912.43307

Journal of the Royal Statistical Society: series B (statistical methodology), 70, (4), 679-702, 2008.9
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 matrixvalued 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.
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@inproceedings{jianqing2008modelling,
  title={Modelling multivariate volatilities via conditionally uncorrelated components},
  author={Jianqing Fan, Mingjin Wang, and Qiwei Yao},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191221113619225134867},
  booktitle={Journal of the Royal Statistical Society: series B (statistical methodology)},
  volume={70},
  number={4},
  pages={679-702},
  year={2008},
}
Jianqing Fan, Mingjin Wang, and Qiwei Yao. Modelling multivariate volatilities via conditionally uncorrelated components. 2008. Vol. 70. In Journal of the Royal Statistical Society: series B (statistical methodology). pp.679-702. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191221113619225134867.
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