Package: cvar 0.5.9000
Georgi N. Boshnakov
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>. Some support for GARCH models is provided, as well.
Authors:
cvar_0.5.9000.tar.gz
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cvar.pdf |cvar.html✨
cvar/json (API)
NEWS
| # Install 'cvar' in R: |
| install.packages('cvar', repos = c('https://geobosh.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/geobosh/cvar/issues
Pkgdown site:https://geobosh.github.io
expected-shortfalllocations-scale-transformationsquantilequantile-functionsriskvalue-at-risk
Last updated 2 years agofrom:207fd77ccc. Checks:7 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Jan 08 2025 |
| R-4.5-win | OK | Jan 08 2025 |
| R-4.5-linux | OK | Jan 08 2025 |
| R-4.4-win | OK | Jan 08 2025 |
| R-4.4-mac | OK | Jan 08 2025 |
| R-4.3-win | OK | Jan 08 2025 |
| R-4.3-mac | OK | Jan 08 2025 |
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Compute Conditional Value-at-Risk and Value-at-Risk | cvar-package cvar |
| Compute expected shortfall (ES) of distributions | ES ES.default ES.numeric |
| Specify a GARCH model | GarchModel |
| Prediction for GARCH(1,1) time series | predict.garch1c1 |
| Simulate GARCH(1,1) time series | sim_garch1c1 |
| Compute Value-at-Risk (VaR) | VaR VaR.default VaR.numeric VaR_cdf VaR_qf |