Learn R Programming

actuar (version 0.9-4)

CTE: Conditional Tail Expectation

Description

Conditional Tail Expectation.

Usage

CTE(x, ...)

## S3 method for class 'aggregateDist': CTE(x, conf.level = c(0.9, 0.95, 0.99), names = TRUE, ...)

Arguments

x
an Robject.
conf.level
numeric vector of probabilities with values in $[0, 1)$
names
logical; if true, the result has a names attribute. Set to FALSE for speedup with many probs.
...
further arguments passed to or from other methods.

Value

  • A numeric vector, named if names is TRUE.

Details

The Conditional Tail Expectation measures the average of losses above the Value at Risk for some given confidence level, that is $E[X|X > VaR(X)]$ where $X$ is the loss random variable.

CTE is a generic function with, currently, only a method for objects of class "aggregateDist".

For the recursive, convolution and simulation methods of aggregateDist, the CTE is computed from the definition using the empirical cdf.

For the normal approximation method, an explicit formula exists: $$\mu + \frac{\sigma}{(1 - \alpha)} \sqrt{2 \pi} e^{-\mathrm{VaR(X)}^2/2},$$ where $\mu$ is the mean, $\sigma$ the standard deviation and $\alpha$ the confidence level.

For the Normal Power approximation, the CTE is computed from the definition using integrate.

See Also

aggregateDist; VaR

Examples

Run this code
model.freq <- expression(data = rpois(7))
model.sev <- expression(data = rnorm(9, 2))
Fs <- aggregateDist("simulation", model.freq, model.sev, nb.simul = 1000)
CTE(Fs)

Run the code above in your browser using DataLab