fExtremes: Rmetrics - Modelling Extreme Events in Finance

Provides functions for analysing and modelling extreme events in financial time Series. The topics include: (i) data pre-processing, (ii) explorative data analysis, (iii) peak over threshold modelling, (iv) block maxima modelling, (v) estimation of VaR and CVaR, and (vi) the computation of the extreme index.

Version: 4032.84
Depends: R (≥ 2.15.1)
Imports: fBasics, fGarch, graphics, methods, stats, timeDate, timeSeries
Suggests: RUnit, tcltk
Published: 2023-12-21
Author: Diethelm Wuertz [aut], Tobias Setz [aut], Yohan Chalabi [aut], Paul J. Northrop [cre, ctb]
Maintainer: Paul J. Northrop <p.northrop at ucl.ac.uk>
BugReports: https://r-forge.r-project.org/projects/rmetrics
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://www.rmetrics.org
NeedsCompilation: no
Materials: README NEWS ChangeLog
In views: Distributions, ExtremeValue, Finance
CRAN checks: fExtremes results

Documentation:

Reference manual: fExtremes.pdf

Downloads:

Package source: fExtremes_4032.84.tar.gz
Windows binaries: r-devel: fExtremes_4032.84.zip, r-release: fExtremes_4032.84.zip, r-oldrel: fExtremes_4032.84.zip
macOS binaries: r-release (arm64): fExtremes_4032.84.tgz, r-oldrel (arm64): fExtremes_4032.84.tgz, r-release (x86_64): fExtremes_4032.84.tgz
Old sources: fExtremes archive

Reverse dependencies:

Reverse depends: AssocTests
Reverse imports: CompDist, extremeStat
Reverse suggests: fitteR, lax

Linking:

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