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.