A hidden Markov regime-switching smooth transition model

Robert J. Elliott, Tak Kuen Siu*, John W. Lau

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    Abstract

    In this paper, we develop a new class of parametric nonlinear time series models by combining two important classes of models, namely smooth transition models and hidden Markov regime-switching models. The class of models is general and flexible enough to incorporate two types of switching behavior: smooth state transitions and abrupt changes in hidden states. The estimation of the hidden states and model parameters is performed by applying filtering theory and a filter-based expectation-maximization (EM) algorithm. Applications of the model are illustrated using simulated data and real financial data. Other potential applications are mentioned.

    Original languageEnglish
    Article number20160061
    Pages (from-to)1-21
    Number of pages21
    JournalStudies in Nonlinear Dynamics and Econometrics
    Volume22
    Issue number4
    Early online date29 Jun 2018
    DOIs
    Publication statusPublished - Sep 2018

    Keywords

    • filtering
    • Laplace series expansion
    • nonlinear time series
    • regime switching model
    • smooth transition model

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