We extend the basic random walk Markov-Switching model in two ways and evaluate the out-of-sample forecasting performance on the Japanese yen during 1995-2004. First, we estimate both a twoand also a three-regime Markov switching models. Second, we add four exogenous variables as suggested in the monetary theory. According to the modified DieboldMariano forecast equivalence test, the result sho...

In this study, a two-state Markov switching count-data model is proposed as an alternative to zero-inflated models to account for the preponderance of zeros sometimes observed in transportation count data, such as the number of accidents occurring on a roadway segment over some period of time. For this accident-frequency case, zero-inflated models assume the existence of two states: one of the ...

In the dynamic factor model, a single unobserved factor common to some macroeconomic variables is defined as a composite index to measure business cycles. This model has recently been developed by combining with the regime-switching model so that the mean growth of the index may shift depending on whether the economy is in the boom regime or in the recession regime. An advantage of this dynamic...

An iterative stochastic algorithm to perform maximum a posteriori parameter estimation of hidden Markov models is proposed. It makes the most of the statistical model by introducing an artiicial probability model based on an increasing number of the unobserved Markov chain at each iteration. Under minor regularity assumptions, we provide suucient conditions to ensure global convergence of this ...

We develop a multivariate generalization of the Markov–switching GARCH model introduced by Haas, Mittnik, and Paolella (2004b) and derive its fourth– moment structure. An application to international stock markets illustrates the relevance of accounting for volatility regimes from both a statistical and economic perspective, including out–of–sample portfolio selection and computation of Value– ...

Nonlinear autoregressive Markov regime-switching models are intuitive and frequently proposed time series approaches for the modelling of electricity spot prices. In this paper such models are compared to an ordinary linear autoregressive model with regard to their forecast performance. The study is carried out using German daily spot prices from the European Energy Exchange in Leipzig. Four no...

In this paper we suggest ways to characterize the transmission mechanisms of volatility between markets by making use of a new Markov Switching bivariate model where the state of one variable feeds into the transition probability of the state of the other. The comparison between this model and other Markov Switching models allows us to derive statistical tests stressing the role of one market r...