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cvar  

Compute Expected Shortfall and Value at Risk for Continuous Distributions
View on CRAN: Click here


Download and install cvar package within the R console
Install from CRAN:
install.packages("cvar")

Install from Github:
library("remotes")
install_github("cran/cvar")

Install by package version:
library("remotes")
install_version("cvar", "0.6")



Attach the package and use:
library("cvar")
Maintained by
Georgi N. Boshnakov
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-04-09
Latest Update: 2022-11-03
Description:
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) . Some support for GARCH models is provided, as well.
How to cite:
Georgi N. Boshnakov (2018). cvar: Compute Expected Shortfall and Value at Risk for Continuous Distributions. R package version 0.6, https://cran.r-project.org/web/packages/cvar. Accessed 15 Jul. 2026.
Previous versions and publish date:
(2026-07-09 07:29), 0.1-1 (2018-04-09 18:01), 0.2-0 (2018-08-19 18:50), 0.3-0 (2018-10-06 09:10), 0.4-0 (2019-03-15 18:53), 0.4.1 (2022-09-19 19:06), 0.5 (2022-11-03 11:00)
Other packages that cited cvar R package
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Complete documentation for cvar
Functions, R codes and Examples using the cvar R package
Some associated functions: ES . GarchModel . VaR . cvar-package . predict.garch1c1 . sim_garch1c1 . 
Some associated R codes: VaR.R . cvar-package.R . garch.R .  Full cvar package functions and examples
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