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Communications in Statistics - Simulation and Computation Volume 49, 2020 - Issue 6
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Original Articles

BINMA(1) model with COM-Poisson innovations: Estimation and application

Yuvraj SunecherDepartment of Accounting and Finance, University of Technology Mauritius, Latour Koenig, Mauritius;
,
Naushad Mamode KhanDepartment of Economics and Statistics, University of Mauritius, Reduit, Mauritius; Correspondence[email protected]
&
Vandna JowaheerDepartment of Mathematics, University of Mauritius, Reduit, Mauritius
Pages 1631-1652 | Received 10 Mar 2017, Accepted 13 Jul 2018, Published online: 17 Oct 2018
 
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Abstract

The article introduces a first-order bivariate integer-valued moving average process (BINMA(1)) where the respective innovation series are marginally COM-Poisson distributed under nonstationary moments. The purpose of this process is to model inter-related INMA(1) time series that are known to exhibit different levels and types of dispersion. The unknown parameters of the model are estimated by the Generalized Quasi-likelihood (GQL) approach. Simulation experiments and a real-life data application to intra-day stock series of two banking companies is presented.

Mathematical Subject Classification:

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