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2014 Stationarity and ergodicity of univariate generalized autoregressive score processes
Francisco Blasques, Siem Jan Koopman, André Lucas
Electron. J. Statist. 8(1): 1088-1112 (2014). DOI: 10.1214/14-EJS924

Abstract

We characterize the dynamic properties of generalized autoregressive score models by identifying the regions of the parameter space that imply stationarity and ergodicity of the corresponding nonlinear time series process. We show how these regions are affected by the choice of parameterization and scaling, which are key features for the class of generalized autoregressive score models compared to other observation driven models. All results are illustrated for the case of time-varying means, variances, or higher-order moments.

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Francisco Blasques. Siem Jan Koopman. André Lucas. "Stationarity and ergodicity of univariate generalized autoregressive score processes." Electron. J. Statist. 8 (1) 1088 - 1112, 2014. https://doi.org/10.1214/14-EJS924

Information

Published: 2014
First available in Project Euclid: 5 August 2014

zbMATH: 1309.60034
MathSciNet: MR3263114
Digital Object Identifier: 10.1214/14-EJS924

Subjects:
Primary: 60G10, 62M10
Secondary: 91B84

Rights: Copyright © 2014 The Institute of Mathematical Statistics and the Bernoulli Society

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Vol.8 • No. 1 • 2014
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