Moving Average Model with an Alternative GARCH-Type Error

Zhu Huafeng (), Zhang Xingfa (), Liang Xin () and Li Yuan ()
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Zhu Huafeng: School of Economics and Statistics, Guangzhou University, Guangzhou510006, China
Zhang Xingfa: School of Economics and Statistics, Guangzhou University, Guangzhou510006, China
Liang Xin: School of Economics and Statistics, Guangzhou University, Guangzhou510006, China
Li Yuan: School of Economics and Statistics, Guangzhou University, Guangzhou510006, China

Journal of Systems Science and Information, 2018, vol. 6, issue 2, 165-177

Abstract: Motivated by the double autoregressive model with order p (DAR(p) model), in this paper, we study the moving average model with an alternative GARCH error. The model is an extension from DAR(p) model by letting the order p goes to infinity. The quasi maximum likelihood estimator of the parameters in the model is shown to be asymptotically normal, without any strong moment conditions. Simulation results confirm that our estimators perform well. We also apply our model to study a real data set and it has better fitting performance compared to DAR model for the considered data.

Keywords: moving average model; double autoregressive model; quasi maximum likelihood estimator (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:jossai:v:6:y:2018:i:2:p:165-177:n:5

DOI: 10.21078/JSSI-2018-165-13

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