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Whittle estimation in multivariate CCC-GARCH processes

Author

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  • Abdelouahab Bibi
  • Karima Kimouche

Abstract

In this paper, we explore some probabilistic properties and statistical analysis of multivariate constant conditional correlation GARCH (CCC-GARCH for short) model. So, in the first part we give the conditions for the model stationarity and its finite moments up to some orders. In the second part, the Whittle estimator is proposed for the parameters CCC-GARCH model based on a transformation. This Whittle estimator is shown to be consistent when the data have finite 4th moment, and its asymptotic normality is established when the data have finite 8th moment. Finite sample properties of this Whittle estimator are further examined through Monte-Carlo experiments.

Suggested Citation

  • Abdelouahab Bibi & Karima Kimouche, 2019. "Whittle estimation in multivariate CCC-GARCH processes," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(15), pages 3921-3940, August.
    • Handle: RePEc:taf:lstaxx:v:48:y:2019:i:15:p:3921-3940
    DOI: 10.1080/03610926.2018.1484140
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