Pre-averaging estimate of high dimensional integrated covariance matrix with noisy and asynchronous high-frequency data
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Publication:4569339
DOI10.1142/S2010326318500053zbMath1395.62324MaRDI QIDQ4569339
Xiaochao Xia, Guoliang Zhou, Zhi Liu
Publication date: 28 June 2018
Published in: Random Matrices: Theory and Applications (Search for Journal in Brave)
Estimation in multivariate analysis (62H12) Asymptotic properties of nonparametric inference (62G20) Applications of statistics to actuarial sciences and financial mathematics (62P05)
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Cites Work
- Unnamed Item
- Nearly unbiased variable selection under minimax concave penalty
- A well-conditioned estimator for large-dimensional covariance matrices
- Quadratic covariation estimation of an irregularly observed semimartingale with jumps and noise
- High dimensional covariance matrix estimation using a factor model
- Optimal sparse volatility matrix estimation for high-dimensional Itô processes with measurement errors
- Limit theorems for the pre-averaged Hayashi-Yoshida estimator with random sampling
- Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data
- Quasi-maximum likelihood estimation of volatility with high frequency data
- Estimating covariation: Epps effect, microstructure noise
- Covariance regularization by thresholding
- A general version of the fundamental theorem of asset pricing
- On covariance estimation of non-synchronously observed diffusion processes
- Vast volatility matrix estimation for high-frequency financial data
- Microstructure noise in the continuous case: the pre-averaging approach
- Regularized estimation of large covariance matrices
- Efficient estimation of stochastic volatility using noisy observations: a multi-scale approach
- Adaptive Thresholding for Sparse Covariance Matrix Estimation
- Designing Realized Kernels to Measure the ex post Variation of Equity Prices in the Presence of Noise
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Vast Volatility Matrix Estimation Using High-Frequency Data for Portfolio Selection
- High-Frequency Covariance Estimates With Noisy and Asynchronous Financial Data
- Generalized Thresholding of Large Covariance Matrices
- FAST CONVERGENCE RATES IN ESTIMATING LARGE VOLATILITY MATRICES USING HIGH-FREQUENCY FINANCIAL DATA
- Econometric Analysis of Realized Covariation: High Frequency Based Covariance, Regression, and Correlation in Financial Economics
- A Tale of Two Time Scales