A Hidden Markov Regime-Switching Smooth Transition Model

  • Robert J. Elliott (Creator)
  • Tak Kuen Siu (Creator)
  • John Lau (Contributor)



This archive contains the data and the R code used for the simulation and the empirical application in "A Hidden Markov Regime-Switching Smooth Transition Model" by Robert J. Elliott, Tak Kuen Siu, and John W. Lau.

We have developed 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 filterbased expectation-maximization (EM) algorithm. Applications of the model are illustrated using simulated data and real financial data.
Date made available10 Feb 2018
PublisherCode Ocean

Cite this

Elliott, R. J. (Creator), Siu, T. K. (Creator) (10 Feb 2018). A Hidden Markov Regime-Switching Smooth Transition Model. Code Ocean. 10.24433/co.dd77cb0f-e54e-4693-905b-493a86cfd345