quarks: Simple Methods for Calculating and Backtesting Value at Risk and Expected Shortfall

Enables the user to calculate Value at Risk (VaR) and Expected Shortfall (ES) by means of various types of historical simulation. Currently plain-, age-, volatility-weighted- and filtered historical simulation are implemented in this package. Volatility weighting can be carried out via an exponentially weighted moving average model (EWMA) or other GARCH-type models. The performance can be assessed via Traffic Light Test, Coverage Tests and Loss Functions. The methods of the package are described in Gurrola-Perez, P. and Murphy, D. (2015) <https://EconPapers.repec.org/RePEc:boe:boeewp:0525> as well as McNeil, J., Frey, R., and Embrechts, P. (2015) <https://ideas.repec.org/b/pup/pbooks/10496.html>.

Version: 1.1.3
Depends: R (≥ 2.10)
Imports: dygraphs, ggplot2, graphics, progress, rugarch, shiny, shinyjs, smoots, stats, yfR, xts
Published: 2022-08-31
Author: Sebastian Letmathe [aut, cre] (Paderborn University, Germany)
Maintainer: Sebastian Letmathe <sebastian.letmathe at uni-paderborn.de>
License: GPL-3
NeedsCompilation: no
Materials: README NEWS
CRAN checks: quarks results

Documentation:

Reference manual: quarks.pdf

Downloads:

Package source: quarks_1.1.3.tar.gz
Windows binaries: r-devel: quarks_1.1.3.zip, r-release: quarks_1.1.3.zip, r-oldrel: quarks_1.1.3.zip
macOS binaries: r-release (arm64): quarks_1.1.3.tgz, r-oldrel (arm64): quarks_1.1.3.tgz, r-release (x86_64): quarks_1.1.3.tgz
Old sources: quarks archive

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