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1309.4889
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Optimal sparse volatility matrix estimation for high-dimensional Itô processes with measurement errors
19 September 2013
Minjing Tao
Yazhen Wang
Harrison H. Zhou
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Papers citing
"Optimal sparse volatility matrix estimation for high-dimensional Itô processes with measurement errors"
10 / 10 papers shown
Title
Likelihood theory for the Graph Ornstein-Uhlenbeck process
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26 May 2020
De-biased graphical Lasso for high-frequency data
Yuta Koike
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9
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04 May 2019
Time series models for realized covariance matrices based on the matrix-F distribution
Jiayuan Zhou
Feiyu Jiang
K. Zhu
W. Li
13
8
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26 Mar 2019
Optimal covariance matrix estimation for high-dimensional noise in high-frequency data
Jinyuan Chang
Qiao Hu
Cheng Liu
C. Tang
70
8
0
19 Dec 2018
Mixed-normal limit theorems for multiple Skorohod integrals in high-dimensions, with application to realized covariance
Yuta Koike
78
5
0
13 Jun 2018
A frequency domain analysis of the error distribution from noisy high-frequency data
Jinyuan Chang
A. Delaigle
P. Hall
C. Tang
23
7
0
20 Jan 2018
Sparse covariance matrix estimation in high-dimensional deconvolution
Denis Belomestny
Mathias Trabs
Alexandre B. Tsybakov
73
10
0
30 Oct 2017
Optimal large-scale quantum state tomography with Pauli measurements
Tony Cai
Donggyu Kim
Yazhen Wang
M. Yuan
Harrison H. Zhou
39
31
0
24 Mar 2016
Low-rank diffusion matrix estimation for high-dimensional time-changed Lévy processes
Denis Belomestny
Mathias Trabs
67
12
0
15 Oct 2015
Principal Components Analysis for Semimartingales and Stochastic PDE
A. Ohashi
Alexandre B. Simas
25
1
0
19 Mar 2015
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