Man pages for fGarch
Rmetrics - Autoregressive Conditional Heteroskedastic Modelling

00fGarch-packageModelling heterskedasticity in financial time series
class-fGARCHClass "fGARCH"
class-fGARCHSPECClass "fGARCHSPEC"
class-fUGARCHSPECClass 'fUGARCHSPEC'
dist-absMomentsAbsolute moments of GARCH distributions
dist-gedStandardized generalized error distribution
dist-gedFitGeneralized error distribution parameter estimation
dist-gedSliderGeneralized error distribution slider
dist-sgedSkew generalized error distribution
dist-sgedFitSkew generalized error distribution parameter estimation
dist-sgedSliderSkew GED distribution slider
dist-snormSkew normal distribution
dist-snormFitSkew normal distribution parameter estimation
dist-snormSliderSkew normal distribution slider
dist-sstdSkew Student-t distribution
dist-sstdFitSkew Student-t distribution parameter estimation
dist-sstdSliderSkew Student-t distribution slider
dist-stdStandardized Student-t distribution
dist-stdFitStudent-t distribution parameter estimation
dist-stdSliderStudent-t distribution slider
fGarchDataTime series datasets
garchFitUnivariate or multivariate GARCH time series fitting
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-summaryGARCH summary methods
methods-volatilityExtract GARCH model volatility
VaRCompute Value-at-Risk (VaR) and expected shortfall (ES)
fGarch documentation built on May 29, 2024, 8:30 a.m.