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Empirical Economics

Erschienen in:

27.12.2017

Mixture periodic GARCH models: theory and applications

verfasst von: Fayçal Hamdi, Saïd Souam

Erschienen in: Empirical Economics | Ausgabe 4/2018

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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.

Vorheriger Artikel Cointegration and price discovery in US corn cash and futures markets

Nächster Artikel Speculative price bubbles in urban housing markets

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The normality assumption is a natural starting point. A more flexible distribution could be considered. For instance, we can replace the normal conditional distribution in each component of the mixture model by the Student distribution.

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Titel: Mixture periodic GARCH models: theory and applications
verfasst von: Fayçal Hamdi
Saïd Souam
Publikationsdatum: 27.12.2017
Verlag: Springer Berlin Heidelberg
Erschienen in: Empirical Economics / Ausgabe 4/2018
Print ISSN: 0377-7332
Elektronische ISSN: 1435-8921
DOI: https://doi.org/10.1007/s00181-017-1348-9

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