当前位置:
X-MOL 学术
›
Stat. Probab. Lett.
›
论文详情
Our official English website, www.x-mol.net, welcomes your
feedback! (Note: you will need to create a separate account there.)
Estimation of high-dimensional integrated covariance matrix based on noisy high-frequency data with multiple observations
Statistics & Probability Letters ( IF 0.9 ) Pub Date : 2021-03-01 , DOI: 10.1016/j.spl.2020.108996 Moming Wang , Ningning Xia
Statistics & Probability Letters ( IF 0.9 ) Pub Date : 2021-03-01 , DOI: 10.1016/j.spl.2020.108996 Moming Wang , Ningning Xia
Abstract In this paper, we study the estimation of integrated covariance matrix based on noisy high-frequency data with multiple transactions using random matrix theory. We further prove that the proposed estimator is also asymptotically optimal for portfolio selection.
中文翻译:
基于多观测噪声高频数据的高维综合协方差矩阵估计
摘要 在本文中,我们使用随机矩阵理论研究了基于多事务噪声高频数据的集成协方差矩阵的估计。我们进一步证明,所提出的估计量对于投资组合选择也是渐近最优的。
更新日期:2021-03-01
中文翻译:
基于多观测噪声高频数据的高维综合协方差矩阵估计
摘要 在本文中,我们使用随机矩阵理论研究了基于多事务噪声高频数据的集成协方差矩阵的估计。我们进一步证明,所提出的估计量对于投资组合选择也是渐近最优的。