Vast volatility matrix estimation using high-frequency data for portfolio selection

Jianqing Fan Yingying Li Ke Yu

Statistics Theory and Methods´╝îData Analysis mathscidoc:1912.43299

Journal of the American Statistical Association, 107, (497), 412-428, 2012.3
Portfolio allocation with gross-exposure constraint is an effective method to increase the efficiency and stability of portfolios selection among a vast pool of assets, as demonstrated by Fan, Zhang, and Yu. The required high-dimensional volatility matrix can be estimated by using high-frequency financial data. This enables us to better adapt to the local volatilities and local correlations among a vast number of assets and to increase significantly the sample size for estimating the volatility matrix. This article studies the volatility matrix estimation using high-dimensional, high-frequency data from the perspective of portfolio selection. Specifically, we propose the use of pairwise-refresh time and all-refresh time methods based on the concept of refresh time proposed by Barndorff-Nielsen, Hansen, Lunde, and Shephard for the estimation of vast covariance matrix and compare their merits in the portfolio selection. We
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@inproceedings{jianqing2012vast,
  title={Vast volatility matrix estimation using high-frequency data for portfolio selection},
  author={Jianqing Fan, Yingying Li, and Ke Yu},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191221113551746320859},
  booktitle={Journal of the American Statistical Association},
  volume={107},
  number={497},
  pages={412-428},
  year={2012},
}
Jianqing Fan, Yingying Li, and Ke Yu. Vast volatility matrix estimation using high-frequency data for portfolio selection. 2012. Vol. 107. In Journal of the American Statistical Association. pp.412-428. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191221113551746320859.
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