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The rgarch project aims to provide a flexible and rich GARCH modelling and testing environment in R.
The project currently hosts a univariate (rugarch) and multivariate (rmgarch) GARCH package. The old rgarch "package" is no longer being developed, but can still be used while the re-write of rmgarch takes place.
Univariate Functionality (rugarch)
Mean Equation: ARFIMAX, ARCH-in-Mean
Variance Equation: GARCH, IGARCH, GJR, TGARCH, EGARCH, APARCH, NAGARCH, NGARCH, AVGARCH, FGARCH (Hentschel) and Exogenous Regressors
Conditional Distributions: [Skew] Normal, [Skew] Student, [Skew] GED, GH & NIG, JSU
Methods: Model Specification, Fit, Filter, Forecast (from spec or fit), Simulation (from fit or spec), Rolling Backtest, Forecast by Bootstrap, Parameter Distribution by Simulation, Summary, Plots, Inference Tests, Forecast Performance Measures...
Multivariate Functionality (rmgarch)
Mean Equation: VARX or univariate ARFIMAX
CoVariance Models: GO-GARCH (Independent Components Analysis based) with mvnorm, maNIG and maGH distrbutions, DCC-GARCH with mvnorm, mvt and mvlaplace distributions and Copula-GARCH (Static or Dynamic Correlation) with mvnorm and mvt.
Please read the disclaimer before downloading and using.
rugarch current version: 1.0-4
rmgarch current version: 0.91
The rgarch project aims to provide a flexible and rich GARCH modelling and testing environment in R.
The project currently hosts a univariate (rugarch) and multivariate (rmgarch) GARCH package. The old rgarch "package" is no longer being developed, but can still be used while the re-write of rmgarch takes place.
Univariate Functionality (rugarch)
Mean Equation: ARFIMAX, ARCH-in-Mean
Variance Equation: GARCH, IGARCH, GJR, TGARCH, EGARCH, APARCH, NAGARCH, NGARCH, AVGARCH, FGARCH (Hentschel) and Exogenous Regressors
Conditional Distributions: [Skew] Normal, [Skew] Student, [Skew] GED, GH & NIG, JSU
Methods: Model Specification, Fit, Filter, Forecast (from spec or fit), Simulation (from fit or spec), Rolling Backtest, Forecast by Bootstrap, Parameter Distribution by Simulation, Summary, Plots, Inference Tests, Forecast Performance Measures...
Multivariate Functionality (rmgarch)
Mean Equation: VARX or univariate ARFIMAX
CoVariance Models: GO-GARCH (Independent Components Analysis based) with mvnorm, maNIG and maGH distrbutions, DCC-GARCH with mvnorm, mvt and mvlaplace distributions and Copula-GARCH (Static or Dynamic Correlation) with mvnorm and mvt.
Please read the disclaimer before downloading and using.
rugarch current version: 1.0-4
rmgarch current version: 0.91
rgarch
Copyright © 2009, 2010, 2011 by Alexios Ghalanos · All Rights reserved · E-Mail: alexios_at_4dscape_dot_com