Danish reinsurance claim dataset

The univariate dataset was collected at Copenhagen Reinsurance and comprise 2167 fire losses over the period 1980 to 1990. They have been adjusted for inflation to reflect 1985 values and are expressed in millions of Danish Krone.

The multivariate dataset is the same data as above but the total claim has been divided into a building loss, a loss of contents and a loss of profits.

Usage

data(danishuni)
data(danishmulti)

Format

danishuni contains two columns:

Date

The day of claim occurence.

Loss

The total loss amount in millions of Danish Krone (DKK).

danishmulti contains five columns:

Date

The day of claim occurence.

Building

The loss amount (mDKK) of the building coverage.

Contents

The loss amount (mDKK) of the contents coverage.

Profits

The loss amount (mDKK) of the profit coverage.

Total

The total loss amount (mDKK).

All columns are numeric except Date columns of class Date.

Source

Embrechts, P., Kluppelberg, C. and Mikosch, T. (1997) Modelling Extremal Events for Insurance and Finance. Berlin: Springer.

References

McNeil, A. (1996), Estimating the Tails of Loss Severity Distributions using Extreme Value Theory, ASTIN Bull, doi:10.2143/AST.27.1.563210 .

Davison, A. C. (2003) Statistical Models. Cambridge University Press, doi:10.1017/CBO9780511815850 .

Examples

# (1) load of data
#
data(danishuni)

# (2) plot and description of data
#
plot(danishuni$Loss)


# (3) load of data
#
data(danishmulti)

# (4) plot and description of data
#
idx <- sample(1:NROW(danishmulti), 10)
barplot(danishmulti$Building[idx], col="grey25", 
    ylim=c(0, max(danishmulti$Total[idx])), main="Some claims of danish dataset")
barplot(danishmulti$Content[idx], add=TRUE, col="grey50", axes=FALSE)
barplot(danishmulti$Profits[idx], add=TRUE, col="grey75", axes=FALSE)
legend("topleft", legend=c("Building", "Content", "Profits"), fill=c("grey25", 
    "grey50", "grey75"))