Mixture periodic GARCH models: theory and applications
Fayçal Hamdi () and
Saïd Souam ()
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Fayçal Hamdi: USTHB
Empirical Economics, 2018, vol. 55, issue 4, 1925-1956
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.
Keywords: Mixture PGARCH models; Periodic stationarity; Higher-order moments; EM algorithm; Volatility forecasting; Exchange rates (search for similar items in EconPapers)
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