DocumentCode :
614745
Title :
Mixture periodic GARCH models: Applications to exchange rate modeling
Author :
Hamdi, Faycal ; Souam, Said
fYear :
2013
fDate :
28-30 April 2013
Firstpage :
1
Lastpage :
6
Abstract :
In this paper, we propose an extension of a mixture periodic ARCH model (MPARCH) to a mixture periodic GARCH model (MPGARCH), and provide some probabilistic properties of this class of models. An estimation method based on the Expectation-Maximization (EM) algorithm is proposed. Finally, it is applied to model the spot rates of the Algerian Dinar against the U.S.-Dollar and Euro. The empirical analysis demonstrates that the proposed mixture model yields the best performance among the competing models.
Keywords :
autoregressive processes; exchange rates; expectation-maximisation algorithm; financial management; probability; Algerian Dinar; Euro; MPGARCH; US Dollar; estimation method; exchange rate modeling; expectation-maximization algorithm; generalized autoregressive conditionally heteroscedastic model; mixture periodic GARCH model; probabilistic properties; spot rate modelling; Biological system modeling; Computational modeling; Data models; Estimation; Exchange rates; Time series analysis; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Modeling, Simulation and Applied Optimization (ICMSAO), 2013 5th International Conference on
Conference_Location :
Hammamet
Print_ISBN :
978-1-4673-5812-5
Type :
conf
DOI :
10.1109/ICMSAO.2013.6552570
Filename :
6552570
Link To Document :
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