cvar: Compute Expected Shortfall and Value at Risk for Continuous Distributions

Compute expected shortfall (ES) and Value at Risk (VaR) from a quantile function, distribution function, random number generator or probability density function. ES is also known as Conditional Value at Risk (CVaR). Virtually any continuous distribution can be specified. The functions are vectorized over the arguments. The computations are done directly from the definitions, see e.g. Acerbi and Tasche (2002) <doi:10.1111/1468-0300.00091>.

Version: 0.2-0
Imports: gbutils, Rdpack (≥ 0.8)
Suggests: testthat, PerformanceAnalytics, covr
Published: 2018-08-19
Author: Georgi N. Boshnakov [aut, cre]
Maintainer: Georgi N. Boshnakov <georgi.boshnakov at manchester.ac.uk>
BugReports: https://github.com/GeoBosh/cvar/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/GeoBosh/cvar
NeedsCompilation: no
Materials: README NEWS
In views: Finance
CRAN checks: cvar results

Downloads:

Reference manual: cvar.pdf
Vignettes: Brief guide to R package \pkg{cvar}
Package source: cvar_0.2-0.tar.gz
Windows binaries: r-devel: cvar_0.2-0.zip, r-release: cvar_0.2-0.zip, r-oldrel: cvar_0.1-1.zip
OS X binaries: r-release: cvar_0.1-1.tgz, r-oldrel: cvar_0.1-1.tgz
Old sources: cvar archive

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