Rmetrics - Autoregressive Conditional Heteroskedastic Modelling

Analyze and model heteroskedastic behavior in financial time series.

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 (rendered with pkgdown) 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(This is an unpublished manuscript.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.)