Stationarity and ergodicity of Markov switching positive conditional mean models

DOI10.1111/jtsa.12621OpenAlexW3197848495MaRDI QIDQ5095291

Abdelhakim Aknouche, Christian Francq

Publication date: 8 August 2022

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

Full work available at URL: https://mpra.ub.uni-muenchen.de/102503/1/MPRA_paper_102503.pdf

zbMATH Keywords

ergodicityfinite mixture modelsautoregressive conditional durationMarkov mixture modelsinteger-valued GARCHcount time series models

Mathematics Subject Classification ID

Stationary stochastic processes (60G10) Time series analysis of dynamical systems (37M10) Inference from stochastic processes (62Mxx)

Related Items

A NEGATIVE BINOMIAL AUTOREGRESSION WITH A LINEAR CONDITIONAL VARIANCE-TO-MEAN FUNCTION ⋮ Asymptotic negative binomial quasi-likelihood inference for periodic integer-valued time series models ⋮ Autoregressive conditional proportion: A multiplicative‐error model for (0,1)‐valued time series ⋮ A multiplicative thinning‐based integer‐valued GARCH model ⋮ On an independent-switching periodic autoregressive conditional duration

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