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Mixture periodic GARCH models: theory and applications

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  • Fayçal Hamdi

    (USTHB)

  • Saïd Souam

    (EconomiX, Université Paris Nanterre
    CREST)

Abstract

This paper discusses mixture periodic GARCH (M-PGARCH) models that constitute very flexible class of nonlinear time series models of the conditional variance. It turns out that they are more parsimonious comparatively to MPARCH models. We first provide some probabilistic properties of this class of models. We thus propose an estimation method based on the expectation-maximization algorithm. Finally, we apply this methodology to model the spot rates of the Algerian dinar against euro and US dollar. This empirical analysis shows that M-PGARCH models yield the best performance among the competing models.

Suggested Citation

  • Fayçal Hamdi & Saïd Souam, 2018. "Mixture periodic GARCH models: theory and applications," Empirical Economics, Springer, vol. 55(4), pages 1925-1956, December.
    • Handle: RePEc:spr:empeco:v:55:y:2018:i:4:d:10.1007_s00181-017-1348-9
    DOI: 10.1007/s00181-017-1348-9
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    Cited by:

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    2. Bibi, Abdelouahab & Ghezal, Ahmed, 2017. "Asymptotic properties of QMLE for periodic asymmetric strong and semi-strong GARCH models," MPRA Paper 81126, University Library of Munich, Germany.

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