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Structure of a double autoregressive process driven by a hidden Markov chain

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  • Liu, Ji-Chun

Abstract

This paper considers a new so-called autoregressive process with ARCH(1) errors driven by a hidden Markov chain, Xt+1=α(Δt+1)Xt+ηt+1β(Δt+1)+λ(Δt+1)Xt2,t∈N, where (ηt) is a sequence of independent and identically distributed standard normal random variables, and (Δt) is a Markov chain with finite state space. Some structural properties of this new autoregressive process are considered. A sufficient condition for the existence of the strictly stationary and geometrically ergodic solution of the process is presented. The condition for this is only E[ln|α(Δt)+ηtλ(Δt)|]<0. Moreover, some simple conditions for the existence of the moments of the process are also derived.

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  • Liu, Ji-Chun, 2012. "Structure of a double autoregressive process driven by a hidden Markov chain," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1468-1473.
  • Handle: RePEc:eee:stapro:v:82:y:2012:i:7:p:1468-1473
    DOI: 10.1016/j.spl.2012.04.001
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    Cited by:

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    2. Zhu, Huafeng & Zhang, Xingfa & Liang, Xin & Li, Yuan, 2017. "On a vector double autoregressive model," Statistics & Probability Letters, Elsevier, vol. 129(C), pages 86-95.

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