Feasible generalized least squares estimation of multivariate GARCH(1,1) models
type: Item
instance of: scholarly article
title: Feasible generalized least squares estimation of multivariate GARCH(1,1) models
zbMATH Open document ID: 1359.62379
author: Federico Poloni
author: Giacomo Sbrana
published in: Journal of Multivariate Analysis
publication date: 2014-06-18T00:00:00Z
review text: A feasible generalized least squares estimator for multivariate GARCH(1,1) models is suggested and its theoretical properties are investigated. Under mild assumptions the estimator is consistent and asymptotically normal distributed with the same variance as the quasi-maximum likelihood estimator. As a drawback the corresponding estimator can result in non-stationary models or conditional volatility matrices that are not positive semidefinite. The estimator relies on a consistent inital estimator such as the closed-form estimator by the authors [ibid. 120, 152--162 (2013; Zbl 1282.62202)], which is also used as a starting value in the accompanying simulation study. In these simulations, the mean squared error of the proposed procedure improves this closed-form estimator by a great deal but is usually somewhat outperformed by the quasi-maximum-likelihood estimator (where in some scenarios it can even achieve comparable results). On the plus side the proposed estimator is considerably faster than the quasi-maximum-likelihood estimator as it does not rely on advanced optimization techniques.
reviewed by: Claudia Kirch
Mathematics Subject Classification ID: 62M10
Mathematics Subject Classification ID: 62F12
zbMATH DE Number: 6305107
zbMATH Keywords: multivariate GARCH(1,1)
zbMATH Keywords: feasible generalized least squares
zbMATH Keywords: maximum likelihood
describes a project that uses: MFE toolbox
MaRDI profile type: Publication
full work available at URL: j.jmva.2014.04.015
OpenAlex ID: W2053300876
cites work: Q5708419
cites work: Ergodicity of Markov chains in an algebraic manifold: application to multivariate GARCH models
cites work: Multivariate GARCH estimation via a Bregman-proximal trust-region method
cites work: Asymptotic theory for multivariate GARCH processes.
cites work: Analytical quasi maximum likelihood inference in multivariate volatility models
cites work: On asymptotic theory for multivariate GARCH models
cites work: A CLOSED-FORM ESTIMATOR FOR THE GARCH(1,1) MODEL
cites work: Markov Chains and Stochastic Stability
cites work: A closed-form estimator for the multivariate GARCH(1,1) model
DOI: 10.1016/J.JMVA.2014.04.015
Recommended article: A closed-form estimator for the multivariate GARCH(1,1) model
Recommended article: Estimation of SEM with GARCH errors
Recommended article: Q5165905
Recommended article: Least‐squares estimation of GARCH(1,1) models with heavy‐tailed errors
Recommended article: A CLOSED-FORM ESTIMATOR FOR THE GARCH(1,1) MODEL
Recommended article: Generalized least squares estimation for cointegration parameters under conditional heteroskedasticity
Recommended article: Robust M-estimation of multivariate GARCH models
Recommended article: On moment conditions for quasi-maximum likelihood estimation of multivariate ARCH models
Recommended article: Q3368858
description: scientific article; zbMATH DE number 6305107