MARKOV REGIME-SWITCHING MODELS
Abstract
A regime-switching model is a time-series model in which parameters change values
according to the regime at present time. While regime-switching models have been very
popular in applied work, there is a lack of literature for simulation studies. New methods
based on regime-switching models are often proposed with neither a proof of convergence
nor simulations to demonstrate their basic properties. In this thesis, a detailed simulation
study of regime-switching models is conducted. A strategy to generate initial search values
in the parameter estimation of regime-switching models is proposed. It is shown that this
method can dramatically reduce the number of restarts of the optimizer. Even in 3-regime
models (with 15 unknown parameters), parameters can be estimated reasonably well with
only 5 restarts.