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MS_Regress - A Package for Markov Regime Switching Models in Matlab

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Description:
This submission provides functions (and examples scripts) for estimation, simulation and forecasting of a general Markov Regime Switching Regression.
Before using the package, make sure you read the pdf file (About the MS_Regress_Package.pdf) in the downloaded zip file (or link below). A copy of this paper can also be found in http://ssrn.com/abstract=1714016.

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 parameter's standard errors can be calculated with 2 different methods;
Includes a C version of hamilton’s 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);
The user can choose the optimizing function to be used in the estimation of the model (fminsearch, fmincon or fminunc);
Support for reduced/constrained estimation (see pdf document for details);
Several example scripts that show how to use the code;

Limitations of the package (so far):

The EM algorithm is not implemented (all models are estimated by direct maximization of log likelihood function);
It does not support state space models with markov switching effects;
It cannot estimate a model with time varying transition probabilities (TVPT). But, Zhuanxin Ding has developed a matlab package for TVTP models based on MS_Regress. You can access it here;
It does not support models with garch type of filters for conditional volatility;

I also wrote a R/S+ version of the package (fMarkovSwitching). It is public available in the R Metrics project and in R Code section of this website. Please be aware that the R version in no longer being maintained so it is actually an older version of the matlab package with only the basic features.
Required Products:
Optimization, Statistics
References:

Alexander, C. (2008) ‘Market Risk Analysis: Practical Financial Econometrics’ Wiley. Brooks, C. (2002) ‘Introduction to Econometrics’ 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) ‘Time Series Analysis’ 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.

About the MS_Regress_Package.pdf (530k)
Marcelo Perlin, Oct 30, 2014, 9:05 AM

v.7

MS_Regress_FEX_1.07.zip (248k)
Marcelo Perlin, Feb 24, 2014, 6:54 AM

v.1

MS_Regress_FEX_1.08.zip (507k)
Marcelo Perlin, Oct 30, 2014, 9:04 AM

v.1

Version_Log.txt (1k)
Marcelo Perlin, Oct 30, 2014, 9:05 AM

v.4

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MS_Regress - A Package for Markov Regime Switching Models in Matlab-经管之家官网！

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