… of second and fourth moments of Markov switching multivariate generalized autoregressive
… for such moments, which are obtained by using a Markov switching vector autoregressive …

… moment conditions for a unified class of Markov switching positive conditional mean models
… on the state of a finite unobserved Markov chain. The corresponding mixing distributions are …

We describe the package MSGARCH, which implements Markov-switching GARCH models
in R with efficient C++ object-oriented programming. Markov-switching GARCH models …

… Markov switching (MS-)GARCH(1,1) models allow for … ), that is currently limited to hidden
Markov models with a one-… MS-GARCH(1,1) models, a model which requires two dimensions, …

… Markov switching AR models, where analytic tractability and flexibility are quite simply a
competitive advantage, which becomes an attractive tool for modeling … existence of moments for …

… the best model or set of models for modelling volatility of the … More than 1000 GARCH models
are fitted to the log returns of … The best model or superior set of models is then chosen by …

… As such, efforts into modelling the conditional moments of the flagship cryptocurrency
Bitcoin have been extensive. There have been numerous studies published into finding the …

… switching between … Markov regime switching models, which are examples of HMM. Since
financial data is observed at discrete time points in practice, we consider a discrete time model …

… or shrink the shot efficiencies: a moment when the player's shots tend to be highly efficient
results in a better performance if the shooting intensity is high at that moment. For example, a …

… models that allow this to occur have been used so far in the literature – the ‘time-varying
coefficient model’ and the ‘Markov switching model’. … the first and second moments of the system …