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Estimation of multivariate asymmetric power GARCH models

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  • Boubacar Maïnassara, Y.
  • Kadmiri, O.
  • Saussereau, B.

Abstract

We suggest a new class of multivariate power transformed asymmetric models. It includes several functional forms of multivariate GARCH models which are of great interest in financial modeling and time series literature. We provide an explicit necessary and sufficient condition to establish the strict stationarity of the model. The asymptotic properties of the quasi-maximum likelihood estimator of the parameters are established. The asymptotic results are illustrated by Monte Carlo experiments and an application to real financial data is studied.

Suggested Citation

  • Boubacar Maïnassara, Y. & Kadmiri, O. & Saussereau, B., 2022. "Estimation of multivariate asymmetric power GARCH models," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    • Handle: RePEc:eee:jmvana:v:192:y:2022:i:c:s0047259x2200077x
    DOI: 10.1016/j.jmva.2022.105073
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    Cited by:

    1. Yacouba Boubacar Maïnassara & Othman Kadmiri & Bruno Saussereau, 2022. "Portmanteau test for a class of multivariate asymmetric power GARCH model," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(6), pages 964-1002, November.
    2. Baye Matar Kandji, 2023. "On the growth rate of superadditive processes and the stability of functional GARCH models," Working Papers 2023-07, Center for Research in Economics and Statistics.

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