272 citations · 850 across the 27 of their papers we have counts for
6 papers · 1 filter
Asymptotic equivalence of Principal Components and Quasi Maximum Likelihood estimators in Large Approximate Factor Models
Matteo Barigozzi
This paper investigates the properties of Quasi Maximum Likelihood estimation of an approximate factor model for an -dimensional vector of stationary time series. We prove that…
Hierarchical DCC-HEAVY Model for High-Dimensional Covariance Matrices
Emilija Dzuverovic, Matteo Barigozzi
We introduce a HD DCC-HEAVY class of hierarchical-type factor models for high-dimensional covariance matrices, employing the realized measures built from higher-frequency data. The…
Robust Tensor Factor Analysis
Matteo Barigozzi, Yong He, Lingxiao Li +1
We consider (robust) inference in the context of a factor model for tensor-valued sequences. We study the consistency of the estimated common factors and loadings space when using…
Quasi Maximum Likelihood Estimation of High-Dimensional Factor Models: A Critical Review
Matteo Barigozzi
We review Quasi Maximum Likelihood estimation of factor models for high-dimensional panels of time series. We consider two cases: (1) estimation when no dynamic model for the facto…
Multidimensional dynamic factor models
Matteo Barigozzi, Filippo Pellegrino
This paper generalises dynamic factor models for multidimensional dependent data. In doing so, it develops an interpretable technique to study complex information sources ranging f…
fnets: An R Package for Network Estimation and Forecasting via Factor-Adjusted VAR Modelling
Dom Owens, Haeran Cho, Matteo Barigozzi
The package fnets for the R language implements the suite of methodologies proposed by Barigozzi et al. (2022) for the network estimation and forecasting of high-dimensional time s…