Man pages for fGarch
Rmetrics - Autoregressive Conditional Heteroskedastic Modelling

00fGarch-packageModelling heterskedasticity in financial time series
class-fGARCHClass "fGARCH" - fitted ARMA-GARCH/APARCH models
class-fGARCHSPECClass "fGARCHSPEC"
class-fUGARCHSPECClass 'fUGARCHSPEC'
dist-absMomentsAbsolute moments of GARCH distributions
dist-gedStandardized generalized error distribution
dist-gedFitGeneralized error distribution parameter estimation
dist-sgedSkew generalized error distribution
dist-sgedFitSkew generalized error distribution parameter estimation
dist-SliderVisualise skew normal, (skew) Student-t and (skew) GED...
dist-snormSkew normal distribution
dist-snormFitSkew normal distribution parameter estimation
dist-sstdSkew Student-t distribution
dist-sstdFitSkew Student-t distribution parameter estimation
dist-stdStandardized Student-t distribution
dist-stdFitStudent-t distribution parameter estimation
fGarchDataTime series datasets
garchFitFit univariate and multivariate GARCH-type models
garchFitControlControl GARCH fitting algorithms
garchSimSimulate univariate GARCH/APARCH time series
garchSpecUnivariate GARCH/APARCH time series specification
methods-coefGARCH coefficients methods
methods-fittedExtract GARCH model fitted values
methods-formulaExtract GARCH model formula
methods-plotGARCH plot methods
methods-predictGARCH prediction function
methods-residualsExtract GARCH model residuals
methods-summaryfGARCH method for the summary function
methods-volatilityExtract GARCH model volatility
VaRCompute Value-at-Risk (VaR) and expected shortfall (ES)
fGarch documentation built on July 12, 2024, 3:01 p.m.