Multivariate Variance Targeting in the BEKK-GARCH Model
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Multivariate Variance Targeting in the BEKK-GARCH Model. / Pedersen, Rasmus Søndergaard; Rahbek, Anders.
In: Econometrics Journal, Vol. 17, No. 1, 2014, p. 24-55.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Multivariate Variance Targeting in the BEKK-GARCH Model
AU - Pedersen, Rasmus Søndergaard
AU - Rahbek, Anders
PY - 2014
Y1 - 2014
N2 - This paper considers 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 consis-tency is established under weak moment conditions, while sixth-order moment restrictions are imposed to establish asymptotic normality. Included simulations indicate that the multivariately induced higher-order moment constraints are necessary
AB - This paper considers 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 consis-tency is established under weak moment conditions, while sixth-order moment restrictions are imposed to establish asymptotic normality. Included simulations indicate that the multivariately induced higher-order moment constraints are necessary
KW - Faculty of Social Sciences
KW - Covariance targeting
KW - Variance targeting
KW - Multivariate GARCH
KW - BEKK
KW - Asymptotic theory
KW - Time series
U2 - 10.1111/ectj.12019
DO - 10.1111/ectj.12019
M3 - Journal article
VL - 17
SP - 24
EP - 55
JO - Econometrics Journal
JF - Econometrics Journal
SN - 1368-4221
IS - 1
ER -
ID: 49889943