Factor-based imputation of missing values and covariances in panel data of large dimensions
From MaRDI portal
Publication:2688654
DOI10.1016/j.jeconom.2022.01.006OpenAlexW4220973851MaRDI QIDQ2688654
Serena Ng, Jushan Bai, Ercument Cahan
Publication date: 3 March 2023
Published in: Journal of Econometrics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2103.03045
Statistics (62-XX) Game theory, economics, finance, and other social and behavioral sciences (91-XX)
Related Items (3)
Machine learning techniques for cross-sectional equity returns' prediction ⋮ Determining the number of change-points in high-dimensional factor models by cross-validation with matrix completion ⋮ Factor Extraction in Dynamic Factor Models: Kalman Filter Versus Principal Components
Uses Software
Cites Work
- Matrix Completion, Counterfactuals, and Factor Analysis of Missing Data
- High-dimensional covariance matrix estimation in approximate factor models
- Maximum likelihood estimation for dynamic factor models with missing data
- On factor models with random missing: EM estimation, inference, and cross validation
- Bootstrapping factor models with cross sectional dependence
- Exact matrix completion via convex optimization
- Large dimensional latent factor modeling with missing observations and applications to causal inference
- Confidence Intervals for Diffusion Index Forecasts and Inference for Factor-Augmented Regressions
- Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets
- Forecasting Using Principal Components From a Large Number of Predictors
- Analysis of Semiparametric Regression Models for Repeated Outcomes in the Presence of Missing Data
- Inferential Theory for Factor Models of Large Dimensions
- Determining the Number of Factors in Approximate Factor Models
This page was built for publication: Factor-based imputation of missing values and covariances in panel data of large dimensions
