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Empirical Economics

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27-12-2017

Mixture periodic GARCH models: theory and applications

Authors: Fayçal Hamdi, Saïd Souam

Published in: Empirical Economics | Issue 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.

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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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Title: Mixture periodic GARCH models: theory and applications
Authors: Fayçal Hamdi
Saïd Souam
Publication date: 27-12-2017
Publisher: Springer Berlin Heidelberg
Published in: Empirical Economics / Issue 4/2018
Print ISSN: 0377-7332
Electronic ISSN: 1435-8921
DOI: https://doi.org/10.1007/s00181-017-1348-9

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