Rmetrics - Autoregressive Conditional Heteroskedastic Modelling
Modelling heterskedasticity in financial time series
Class "fGARCH"
Class "fGARCHSPEC"
Class 'fUGARCHSPEC'
Absolute moments of GARCH distributions
Standardized generalized error distribution
Generalized error distribution parameter estimation
Generalized error distribution slider
Skew generalized error distribution
Skew generalized error distribution parameter estimation
Skew GED distribution slider
Skew normal distribution
Skew normal distribution parameter estimation
Skew normal distribution slider
Skew Student-t distribution
Skew Student-t distribution parameter estimation
Skew Student-t distribution slider
Standardized Student-t distribution
Student-t distribution parameter estimation
Student-t distribution slider
Time series datasets
Univariate or multivariate GARCH time series fitting
Control GARCH fitting algorithms
Simulate univariate GARCH/APARCH time series
Univariate GARCH/APARCH time series specification
GARCH coefficients methods
Extract GARCH model fitted values
Extract GARCH model formula
GARCH plot methods
GARCH prediction function
Extract GARCH model residuals
GARCH summary methods
Extract GARCH model volatility
Diagnostic plots and statistics for fitted GARCH models
Compute Value-at-Risk (VaR) and expected shortfall (ES)
Analyze and model heteroskedastic behavior in financial time series.
Useful links