RobExtremes (version 1.3.0)

getCVaR: Risk Measures for Scale-Shape Families

Description

Functions to compute Value-at-Risk (VaR), Conditional Value-at-Risk (CVaR) and Expected Loss (EL) at data from scale-shape families.

Usage

getVaR(data, model, level, rob=TRUE)
getCVaR(data, model, level, rob=TRUE)
getEL(data, model, N0, rob=TRUE)
# S3 method for riskMeasure
print(x, level=NULL, ...)

Value

The risk measures getVaR, getCVaR, getEL return an (S3) object of class "riskMeasure", i.e., a numeric vector of length 2 with components "Risk" and "varofRisk"

containing the respective risk measure and a corresponding (asymptotic) standard error for the risk measure. To the return class "riskMeasure", there is a particular print-method; if the corresponding argument level is NULL (default) the corresponding standard error is printed together with the risk measure; otherwise a corresponding CLT-based confidence interval for the risk meausre is produced.

Arguments

data

data at which to compute the risk measure.

model

an object of class "L2ScaleShapeFamily". The parametric family at which to evaluate the risk measure.

level

real: probability needed for VaR and CVaR.

N0

real: expected frequency for expected loss.

rob

logical; if TRUE (default) the RMXE-parametric estimator is used; otherwise the MLE.

x

an object of (S3-)class "riskmeasure".

...

further arguments for print.

Author

Peter Ruckdeschel

References

P. Ruckdeschel, N. Horbenko (2013): Optimally-Robust Estimators in Generalized Pareto Models. Statistics 47(4), 762--791. tools:::Rd_expr_doi("10.1080/02331888.2011.628022").
N. Horbenko, P. Ruckdeschel, T. Bae (2011): Robust Estimation of Operational Risk. Journal of Operational Risk 6(2), 3--30.

See Also

GParetoFamily, GEVFamily, WeibullFamily, GammaFamily

Examples

   # to reduce checking time
  set.seed(123)
  GPD <- GParetoFamily(loc=20480, scale=7e4, shape=0.3)
  data <- r(GPD)(500)
  getCVaR(data,GPD,0.99)
  getVaR(data,GPD,0.99)
  getEL(data,GPD,5)
  getVaR(data,GPD,0.99, rob=FALSE)
  getEL(data,GPD,5, rob=FALSE)
  getCVaR(data,GPD,0.99, rob=FALSE)