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Feasible generalized least squares estimation of multivariate GARCH(1, 1) models

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  • Poloni, Federico
  • Sbrana, Giacomo

Abstract

We provide a feasible generalized least squares estimator for (unrestricted) multivariate GARCH(1, 1) models. We show that the estimator is consistent and asymptotically normally distributed under mild assumptions. Unlike the (quasi) maximum likelihood method, the feasible GLS is considerably fast to implement and does not require any complex optimization routine.

Suggested Citation

  • Poloni, Federico & Sbrana, Giacomo, 2014. "Feasible generalized least squares estimation of multivariate GARCH(1, 1) models," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 151-159.
  • Handle: RePEc:eee:jmvana:v:129:y:2014:i:c:p:151-159
    DOI: 10.1016/j.jmva.2014.04.015
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    10. repec:cup:cbooks:9780521822893 is not listed on IDEAS
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    Cited by:

    1. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.

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