Multivariate variance targeting in the BEKK-GARCH model

TY - JOUR

T1 - Multivariate variance targeting in the BEKK-GARCH model

AU - Pedersen, Rasmus S.

AU - Rahbæk, Anders

PY - 2014/2/1

Y1 - 2014/2/1

N2 - In this paper, we consider asymptotic inference in the multivariate BEKK model based on (co)variance targeting (VT). By definition the VT estimator is a two-step estimator and the theory presented is based on expansions of the modified likelihood function, or estimating function, corresponding to these two steps. Strong consistency is established under weak moment conditions, while sixth-order moment restrictions are imposed to establish asymptotic normality. The simulations included indicate that the multivariately induced higher-order moment constraints are necessary.

AB - In this paper, we consider asymptotic inference in the multivariate BEKK model based on (co)variance targeting (VT). By definition the VT estimator is a two-step estimator and the theory presented is based on expansions of the modified likelihood function, or estimating function, corresponding to these two steps. Strong consistency is established under weak moment conditions, while sixth-order moment restrictions are imposed to establish asymptotic normality. The simulations included indicate that the multivariately induced higher-order moment constraints are necessary.

KW - Asymptotic theory

KW - BEKK

KW - Covariance targeting

KW - Multivariate GARCH

KW - Time series

KW - Variance targeting

U2 - 10.1111/ectj.12019

DO - 10.1111/ectj.12019

M3 - Journal article

AN - SCOPUS:84894225642

SN - 1368-4221

VL - 17

SP - 24

EP - 55

JO - Econometrics Journal

JF - Econometrics Journal

IS - 1

ER -