ExcessEPD {ReIns}

Estimates for excess-loss premiums using EPD estimates

Description

Estimate premiums of excess-loss reinsurance with retention R and limit L using EPD estimates.

Usage

ExcessEPD(data, gamma, kappa, tau, R, L = Inf, warnings = TRUE, plot = TRUE, add = FALSE, 
          main = "Estimates for premium of excess-loss insurance", ...)

Arguments

data

Vector of n observations.

gamma

Vector of n-1 estimates for the EVI, obtained from EPD.

kappa

Vector of n-1 estimates for \kappa, obtained from EPD.

tau

Vector of n-1 estimates for \tau, obtained from EPD.

R

The retention level of the (re-)insurance.

L

The limit of the (re-)insurance, default is Inf.

warnings

Logical indicating if warnings are displayed, default is TRUE.

plot

Logical indicating if the estimates should be plotted as a function of k, default is FALSE.

add

Logical indicating if the estimates should be added to an existing plot, default is FALSE.

main

Title for the plot, default is "Estimates for premium of excess-loss insurance".

...

Additional arguments for the plot function, see plot for more details.

Details

We need that u \ge X_{n-k,n}, the (k+1)-th largest observation. If this is not the case, we return NA for the premium. A warning will be issued in that case if warnings=TRUE.

The premium for the excess-loss insurance with retention R and limit L is given by

E(\min{(X-R)_+, L}) = \Pi(R) - \Pi(R+L)

where \Pi(u)=E((X-u)_+)=\int_u^{\infty} (1-F(z)) dz is the premium of the excess-loss insurance with retention u. When L=\infty, the premium is equal to \Pi(R).

We estimate \Pi by

\hat{\Pi}(u) = (k+1)/(n+1) \times (X_{n-k,n})^{1/\hat{\gamma}} \times ((1-\hat{\kappa}/\hat{\gamma})(1/\hat{\gamma}-1)^{-1}u^{1-1/\hat{\gamma}} + \hat{\kappa}/(\hat{\gamma}X_{n-k,n}^{\hat{\tau}})(1/\hat{\gamma}-\hat{\tau}-1)^{-1}u^{1+\hat{\tau}-1/\hat{\gamma}})

with \hat{\gamma}, \hat{\kappa} and \hat{\tau} the estimates for the parameters of the EPD.

See Section 4.6 of Albrecher et al. (2017) for more details.

Value

A list with following components:

k

Vector of the values of the tail parameter k.

premium

The corresponding estimates for the premium.

R

The retention level of the (re-)insurance.

L

The limit of the (re-)insurance.

Author(s)

Tom Reynkens

References

Albrecher, H., Beirlant, J. and Teugels, J. (2017). Reinsurance: Actuarial and Statistical Aspects, Wiley, Chichester.

See Also

EPD, ExcessHill, ExcessGPD

Examples

data(secura)

# EPD estimator
epd <- EPD(secura$size)

# Premium of excess-loss insurance with retention R
R <- 10^7
ExcessEPD(secura$size, gamma=epd$gamma, kappa=epd$kappa, tau=epd$tau, R=R, ylim=c(0,2*10^4))