Learn R Programming

Analyze and model heteroskedastic behavior in financial time series with GARCH, APARCH and related models.

Package fGarch is part of the Rmetrics suite of R packages and is developed on R-forge at fGarch devel. The root of Rmetrics is at R-forge.

Installing fGarch

Install the latest stable version of fGarch from CRAN:

install.packages("fGarch")

You can install the development version of fGarch from R-forge:

install.packages("fGarch", repos = "http://R-Forge.R-project.org")

To report bugs visit Rmetrics.

Documentation

You can view the documentation of fGarch at fGarchDoc or download the reference manual of the latest release from CRAN.

A comprehensive overview of the models and conditional distributions employed in package fGarch, along with worked examples, is available in the following paper by the original authors of the package:

WurtzEtAlGarch.pdf.

(This is an unpublished manuscript. Some online sources, confusingly, attribute it to JSS, vol 55, issue 2, but this seems to have taken the placeholders VV and II in the heading on the first page as being the Roman numbers 55 and 2.)

Copy Link

Version

Install

install.packages('fGarch')

Monthly Downloads

14,321

Version

4033.92

License

GPL (>= 2)

Maintainer

Georgi Boshnakov

Last Published

March 26th, 2024

Functions in fGarch (4033.92)

sstd

Skew Student-t distribution
snormFit

Skew normal distribution parameter estimation
sstdSlider

Skew Student-t distribution slider
garchFit

Univariate or multivariate GARCH time series fitting
garchFitControl

Control GARCH fitting algorithms
coef-methods

GARCH coefficients methods
formula-methods

Extract GARCH model formula
fitted-methods

Extract GARCH model fitted values
garchSpec

Univariate GARCH/APARCH time series specification
garchSim

Simulate univariate GARCH/APARCH time series
fGarchData

Time series datasets
summary-methods

GARCH summary methods
stdSlider

Student-t distribution slider
plot-methods

GARCH plot methods
residuals-methods

Extract GARCH model residuals
volatility-methods

Extract GARCH model volatility
stats-tsdiag

Diagnostic plots and statistics for fitted GARCH models
predict-methods

GARCH prediction function
VaR

Compute Value-at-Risk (VaR) and expected shortfall (ES)
absMoments

Absolute moments of GARCH distributions
sstdFit

Skew Student-t distribution parameter estimation
sged

Skew generalized error distribution
sgedFit

Skew generalized error distribution parameter estimation
stdFit

Student-t distribution parameter estimation
fUGARCHSPEC-class

Class 'fUGARCHSPEC'
ged

Standardized generalized error distribution
gedFit

Generalized error distribution parameter estimation
fGARCH-class

Class "fGARCH"
gedSlider

Generalized error distribution slider
fGarch-package

Modelling heterskedasticity in financial time series
sgedSlider

Skew GED distribution slider
snormSlider

Skew normal distribution slider
std

Standardized Student-t distribution
snorm

Skew normal distribution
fGARCHSPEC-class

Class "fGARCHSPEC"