ARMAX-GARCH Toolbox 1.0

The ARMAX-GARCH Toolbox estimates, forecasts and simulates a large variety of ARMA and GARCH models with different distributions and for any order of AR(n), MA(m), ARCH (p) and GARCH (q) effects as well as it allows any number of factors in the mean and volatility process.The supported models are:GARCH, GJR-GARCH, EGARCH, NARCH (Nonlinear ARCH), NGARCH (Nonlinear GARCH), AGARCH (Asymmetric GARCH), APGARCH (Asymmetric Power GARCH), and NAGARCH (Nonlinear Asymmetric GARCH).The supported distributions are:Gaussian Normal, Student t, Generalized Error, Cauchy, Hansend-deOaos Skew-t, and Gram-Charlier Expansion Series with constant higher-moments.The main functions are:1. garch.m, which estimates the ARMAX-GARCH family of models. The functiond-deOaos inputs are a data vector, the GARCH model to be estimated, the distribution of the innovation terms, the order of AR, MA, ARCH and GARCH effects as well as a vector of factors for the mean and volatility process. The functiond-deOaos outputs are a vector of estimated parameters, standard errors estimated by the inverse Hessian, the Log-Likelihood value, a vector of conditional variances, the residuals, and a summary of results which includes: model statistics, t-statistics, robust standard errors, scores among others.2. garchfor.m, which estimates mean and volatility forecasts given the model, distribution, and number of forecasts.3.garchsim.m, which simulates GARCH responses given the model, distribution, number of samples and number of paths. Additionally, a vector of time series of positive pre-sample conditional standard deviations may be provided, which the variance model will initialize.For further information regarding the full functionality and a set of examples of the ARMAX-GARCH Toolbox please refer to the readme files.I would like to thank you for your comments and your suggestions regarding additional features that should be included.Please feel free to contact me with comments, suggestions, or bugfixes.

Requirements:	No special requirements
Platforms:	Matlab
Keyword:	Additionally,  Garchform,  Paths,  Robust,  Samples,  Scores,  Tstatistics
Users rating:	0/10