varmonitor-package: Risk Management Tools: Value-at-Risk Monitor
In f-kailin/varmonitor: Risk Management Tools: Value-at-Risk Monitor

Description Details Author(s) References See Also Examples

Estimate the Value-at-Risk and Expected Shortfall according to the parametric and analytical approach under the following assumptions: no time-varying volatility and changes in market variables are following a normal distribution.

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Gatti Riccardo, Lin Francesco

Maintainer: Lin Francesco <fkl@francescolin.com>

Artzner P., Delbaen F., Eber J.M., Heath D. (1999): Coherent Measures of Risk in Mathematical Finance, 9th vol, Wiley.
Hull J.C. (2015): "Value-at-Risk and Expected Shortfall" in "Risk Management and Financial Institutions", Wiley.
Hull J.C. (2015): "Model-Building Approach" in "Risk Management and Financial Institutions", Wiley.
Jorion P. (2007): "Portfolio Risk: Analytical Methods" in "Value at Risk", McGraw-Hill.

parametricVaR parametricES analyticVaR analyticES

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parametricVaR(.99, -1000000, .01)
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parametricES(c(0.95, 0.975, 0.99), 1000000, 0.01, c(1, 5, 22))
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weights <- c(100000, -100000, 100000)
varcov <- matrix(c(0.05, 0.03, 0.01, 0.03, 0.04, 0.02, 0.01, 0.02, 0.03), nrow = 3)
analyticVaR(c(0.95, 0.99, 0.999), weights, varcov, 5)
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analyticES(.99, weights, varcov)