MS_Regress - A Package for Markov Regime Switching Models in Matlab 1.0

This submission provides functions (and examples scripts) for estimation, simulation and forecasting of a general Markov Regime Switching Regression. Features of the package:- Support for univariate and multivariate models.- Support of any number of states and any number of explanatory variables.- Estimation, by maximum likelihood, of any type of switching setup for the model. This means that you can choose which coefficients in the model, including distribution parameters, are switching states over time.- A wrapper function for the estimation of regime switching autoregressive models, including multivariate case (MS-VAR) is included in the package.- The values of standard error for the estimated coefficients can be calculated with 2 different methods.- Includes a C version of hamiltond-deOaos filter that may be used for speeding up the estimation function (see pdf for details).- Possibility of three distinct distribution assumptions for residual vector (Normal, t or GED).- Support for reduced/constrained estimation (see pdf document for details).- Loads of example scripts. Limitations of the Package (so far):- The EM algorithm is not implemented (all models are estimated by direct maximization of log likelihood function).- It doesnd-deOaot support state space models with markov switching effects.- It cannot estimate a model with time varying transition probabilities (TVPT).- It doesnd-deOaot support models with garch type of filters for conditional volatility. Here a few references in Markov Switching models: ALEXANDER, C. (2008) d-de?Market Risk Analysis: Practical Financial Econometricsd-deOao Wiley.BROOKS, C. (2002) d-de?Introduction to Econometricsd-deOao Cambridge University Press.HAMILTON, J., D. (2005) Regime Switching Models. Palgrave Dictionary of Economics, (available at http://dss.ucsd.edu/~jhamilto/palgrav1.pdf )HAMILTON, J., D. (1994) d-de?Time Series Analysisd-deOao Princeton University Press.KIM, C., J., NELSON, C., R. (1999) State Space Model with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications. The MIT press. Before using the package, make sure you read the pdf file (About the MS_Regress_Package.pdf) in the downloaded zip file. A copy of this paper can be found in http://ssrn.com/abstract=1714016. I also wrote a R/S+ version of the package (fMarkovSwitching). It is public available in the Rmetrics project: http://r-forge.r-project.org/projects/rmetrics/. Please be aware that the R version in no longer being maintained so it is actually an older version of the package with only the basic features. Fell free to send any comments/suggestions to my email.

Requirements:	No special requirements
Platforms:	Matlab
Keyword:	About The,  Actually An,  Algorithm,  Analysis Practical,  Analysis Princeton,  Choose,  Introduction,  Market,  Market Risk Analysis,  Models,  Older,  Read,  Regime,  Regime Switching,  State,  Time,  Time Series Analysis,  Time Varying,  Wrapper Function,  Wrote
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