High-dimensional covariance matrices under dynamic volatility models: asymptotics and shrinkage estimation
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Publication:6608678
DOI10.1214/24-AOS2381MaRDI QIDQ6608678
Publication date: 20 September 2024
Published in: The Annals of Statistics (Search for Journal in Brave)
spectral distributionsample covariance matrixhigh-dimensionnonlinear shrinkagedynamic volatility model
Estimation in multivariate analysis (62H12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)
Cites Work
- Nonlinear shrinkage estimation of large-dimensional covariance matrices
- Large sample behaviour of high dimensional autocovariance matrices
- On the estimation of integrated covariance matrices of high dimensional diffusion processes
- Limiting spectral distribution of large sample covariance matrices associated with a class of stationary processes
- Eigenvectors of some large sample covariance matrix ensembles
- A note on a Marčenko-Pastur type theorem for time series
- On the empirical spectral distribution for matrices with long memory and independent rows
- Limiting spectral distribution of large-dimensional sample covariance matrices generated by VARMA
- Spectrum estimation for large dimensional covariance matrices using random matrix theory
- Spectral analysis of large dimensional random matrices
- Maximum likelihood estimation of pure GARCH and ARMA-GARCH processes
- Limiting spectral distribution for a class of random matrices
- On the empirical distribution of eigenvalues of a class of large dimensional random matrices
- Strong convergence of the empirical distribution of eigenvalues of large dimensional random matrices
- Analytical nonlinear shrinkage of large-dimensional covariance matrices
- On the Marčenko-Pastur law for linear time series
- Spectrum estimation: a unified framework for covariance matrix estimation and PCA in large dimensions
- Quasi-maximum likelihood estimation in GARCH processes when some coefficients are equal to zero
- Testing high-dimensional covariance matrices under the elliptical distribution and beyond
- High dimensional minimum variance portfolio estimation under statistical factor models
- On the Spectrum of Sample Covariance Matrices for Time Series
- Multivariate variance targeting in the BEKK-GARCH model
- DISTRIBUTION OF EIGENVALUES FOR SOME SETS OF RANDOM MATRICES
- Fitting Vast Dimensional Time-Varying Covariance Models
- Large Dynamic Covariance Matrices
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