Large-Dimensional Factor Analysis Without Moment Constraints
From MaRDI portal
Publication:6620853
DOI10.1080/07350015.2020.1811101zbMath1547.62753MaRDI QIDQ6620853
Unnamed Author, Unnamed Author, Xin Sheng Zhang, Xin-Bing Kong
Publication date: 17 October 2024
Published in: Journal of Business and Economic Statistics (Search for Journal in Brave)
Related Items (4)
Regularized covariance matrix estimation in high dimensional approximate factor models ⋮ Distributed debiased estimation of high-dimensional partially linear models with jumps ⋮ Statistical inference for GQARCH-Itô-jumps model based on the realized range volatility ⋮ Selecting the number of factors in multi-variate time series
Cites Work
- Unnamed Item
- Modeling high-frequency financial data by pure jump processes
- Statistical analysis of factor models of high dimension
- Covariance regularization by thresholding
- Transformed contribution ratio test for the number of factors in static approximate factor models
- Some robust estimates of principal components
- Robust factor number specification for large-dimensional elliptical factor model
- Testing for pure-jump processes for high-frequency data
- Large covariance estimation through elliptical factor models
- Theory and methods of panel data models with interactive effects
- Eigenvalue Ratio Test for the Number of Factors
- Testing Hypotheses About the Number of Factors in Large Factor Models
- Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets
- A multivariate version of kendall's τ
- Forecasting Using Principal Components From a Large Number of Predictors
- A Randomized Sequential Procedure to Determine the Number of Factors
- Empirical properties of asset returns: stylized facts and statistical issues
- ECA: High-Dimensional Elliptical Component Analysis in Non-Gaussian Distributions
- Scale-Invariant Sparse PCA on High-Dimensional Meta-Elliptical Data
- Inferential Theory for Factor Models of Large Dimensions
- Determining the Number of Factors in Approximate Factor Models
- Large Covariance Estimation by Thresholding Principal Orthogonal Complements
- Sign and rank covariance matrices
This page was built for publication: Large-Dimensional Factor Analysis Without Moment Constraints
