Forecasting Conditional Covariance Matrices in High-Dimensional Time Series: A General Dynamic Factor Approach

Related Items (1)

Cites Work

Principal component analysis for second-order stationary vector time series
The Model Confidence Set
Nonlinear shrinkage estimation of large-dimensional covariance matrices
Indirect estimation of large conditionally heteroskedastic factor models, with an application to the Dow 30 stocks
High-dimensional covariance matrix estimation in approximate factor models
A forecasting performance comparison of dynamic factor models based on static and dynamic methods
On loss functions and ranking forecasting performances of multivariate volatility models
Improved penalization for determining the number of factors in approximate factor models
The general dynamic factor model: one-sided representation results
On asymptotic theory for multivariate GARCH models
Dynamic factor multivariate GARCH model
Optimal dimension reduction for high-dimensional and functional time series
Generalized dynamic factor models and volatilities: estimation and forecasting
Asymptotic theory for multivariate GARCH processes.
Generalized dynamic factor models and volatilities: consistency, rates, and prediction intervals
Dynamic factor models with infinite-dimensional factor spaces: one-sided representations
Dynamic factor models with infinite-dimensional factor space: asymptotic analysis
Factor models in high-dimensional time series: A time-domain approach
Dynamic Orthogonal Components for Multivariate Time Series
Modelling Multivariate Volatilities via Conditionally Uncorrelated Components
A full-factor multivariate GARCH model
Forecasting Using Principal Components From a Large Number of Predictors
Robust bootstrap densities for dynamic conditional correlations: implications for portfolio selection and Value-at-Risk
Generalized dynamic factor models and volatilities: recovering the market volatility shocks
Time Series in High Dimensions
GARCH Models
Determining the Number of Factors in the General Dynamic Factor Model
OPENING THE BLACK BOX: STRUCTURAL FACTOR MODELS WITH LARGE CROSS SECTIONS
Determining the Number of Factors in Approximate Factor Models
Large Covariance Estimation by Thresholding Principal Orthogonal Complements
The Generalized Dynamic Factor Model
High-dimensional covariance matrix estimation
Fitting Vast Dimensional Time-Varying Covariance Models
Large Dynamic Covariance Matrices

This page was built for publication: Forecasting Conditional Covariance Matrices in High-Dimensional Time Series: A General Dynamic Factor Approach