Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Xia, Ningning"'
We establish central limit theorems for principal eigenvalues and eigenvectors under a large factor model setting, and develop two-sample tests of both principal eigenvalues and principal eigenvectors. One important application is to detect structura
Externí odkaz:
http://arxiv.org/abs/2405.06939
Due to the mechanism of recording, the presence of multiple transactions at each recording time becomes a common feature for high-frequency data in financial market. Using random matrix theory, this paper considers the estimation of integrated covari
Externí odkaz:
http://arxiv.org/abs/1908.08670
Autor:
Xu, Yangchang, Xia, Ningning
Publikováno v:
In Journal of Multivariate Analysis January 2023 193
Publikováno v:
In Journal of Multivariate Analysis May 2022 189
Publikováno v:
In Journal of Multivariate Analysis March 2022 188
Autor:
Xia, Ningning, Bai, Zhidong
In this paper, we adopt the eigenvector empirical spectral distribution (VESD) to investigate the limiting behavior of eigenvectors of a large dimensional Wigner matrix W_n. In particular, we derive the optimal bound for the rate of convergence of th
Externí odkaz:
http://arxiv.org/abs/1611.06744
This paper examines the usefulness of high frequency data in estimating the covariance matrix for portfolio choice when the portfolio size is large. A computationally convenient nonlinear shrinkage estimator for the integrated covariance (ICV) matrix
Externí odkaz:
http://arxiv.org/abs/1611.06753
Autor:
Xia, Ningning, Zheng, Xinghua
In practice, observations are often contaminated by noise, making the resulting sample covariance matrix a signal-plus-noise sample covariance matrix. Aiming to make inferences about the spectral distribution of the population covariance matrix under
Externí odkaz:
http://arxiv.org/abs/1604.03638
Autor:
Xia, Ningning, Zheng, Xinghua
In practice, observations are often contaminated by noise, making the resulting sample covariance matrix to be an information-plus-noise-type covariance matrix. Aiming to make inferences about the spectra of the underlying true covariance matrix unde
Externí odkaz:
http://arxiv.org/abs/1409.2121
Publikováno v:
Annals of Statistics 2013, Vol. 41, No. 5, 2572-2607
The eigenvector Empirical Spectral Distribution (VESD) is adopted to investigate the limiting behavior of eigenvectors and eigenvalues of covariance matrices. In this paper, we shall show that the Kolmogorov distance between the expected VESD of samp
Externí odkaz:
http://arxiv.org/abs/1311.5000