Structure and asymptotic theory for multivariate asymmetric conditional volatility

Various univariate and multivariate models of volatility have been used to evaluate market risk, asymmetric shocks, thresholds, leverage effects, and Value-at-Risk in economics and finance. This article is concerned with market risk, and develops a constant conditional correlation vector ARMA–asymme...

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Main Authors: Mcaleer, M., Hoti, S., Chan, Felix
Format: Journal Article
Published: Taylor and Francis 2009
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/16633
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author Mcaleer, M.
Hoti, S.
Chan, Felix
author_facet Mcaleer, M.
Hoti, S.
Chan, Felix
author_sort Mcaleer, M.
building Curtin Institutional Repository
collection Online Access
description Various univariate and multivariate models of volatility have been used to evaluate market risk, asymmetric shocks, thresholds, leverage effects, and Value-at-Risk in economics and finance. This article is concerned with market risk, and develops a constant conditional correlation vector ARMA–asymmetric GARCH (VARMA–AGARCH) model, as an extension of the widely used univariate asymmetric (or threshold) GJR model of Glosten et al. (1992), and establishes its underlying structure, including the unique, strictly stationary, and ergodic solution of the model, its causal expansion, and convenient sufficient conditions for the existence of moments. Alternative empirically verifiable sufficient conditions for the consistency and asymptotic normality of the quasi-maximum likelihood estimator are established under non-normality of the standardized shocks.
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publishDate 2009
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spelling curtin-20.500.11937-166332017-09-13T15:42:22Z Structure and asymptotic theory for multivariate asymmetric conditional volatility Mcaleer, M. Hoti, S. Chan, Felix Asymmetric effects C52 Multivariate structure Regularity conditions C51 C32 Conditional volatility Asymptotic theory Various univariate and multivariate models of volatility have been used to evaluate market risk, asymmetric shocks, thresholds, leverage effects, and Value-at-Risk in economics and finance. This article is concerned with market risk, and develops a constant conditional correlation vector ARMA–asymmetric GARCH (VARMA–AGARCH) model, as an extension of the widely used univariate asymmetric (or threshold) GJR model of Glosten et al. (1992), and establishes its underlying structure, including the unique, strictly stationary, and ergodic solution of the model, its causal expansion, and convenient sufficient conditions for the existence of moments. Alternative empirically verifiable sufficient conditions for the consistency and asymptotic normality of the quasi-maximum likelihood estimator are established under non-normality of the standardized shocks. 2009 Journal Article http://hdl.handle.net/20.500.11937/16633 10.1080/07474930802467217 Taylor and Francis restricted
spellingShingle Asymmetric effects
C52
Multivariate structure
Regularity conditions
C51
C32
Conditional volatility
Asymptotic theory
Mcaleer, M.
Hoti, S.
Chan, Felix
Structure and asymptotic theory for multivariate asymmetric conditional volatility
title Structure and asymptotic theory for multivariate asymmetric conditional volatility
title_full Structure and asymptotic theory for multivariate asymmetric conditional volatility
title_fullStr Structure and asymptotic theory for multivariate asymmetric conditional volatility
title_full_unstemmed Structure and asymptotic theory for multivariate asymmetric conditional volatility
title_short Structure and asymptotic theory for multivariate asymmetric conditional volatility
title_sort structure and asymptotic theory for multivariate asymmetric conditional volatility
topic Asymmetric effects
C52
Multivariate structure
Regularity conditions
C51
C32
Conditional volatility
Asymptotic theory
url http://hdl.handle.net/20.500.11937/16633