QuantileIFRS17: Quantile estimation for the IFRS 17 Risk Adjustment

In edalmoro/ChainLadderEDM: Statistical Methods and Models for Claims Reserving in General Insurance

Description

The Quantile IFRS 17 function provides an estimate of the quantile attained on the reserve risk distribution that corresponds to the booked Risk Adjustment amount on top of the Best Estimate.

Usage

QuantileIFRS17(Triangles, Correlations, RiskMargin)

Arguments

Triangles	Import triangles of the same size (number of columns and lines) one below the other. Several triangles should be imported.
Correlations	Correlation matrix depicting the correlations between each triangle imported
RiskMargin	Input the risk margin as a single number

Value

QuantileIFRS17 returns a list with the following elements

QuantileIFRS_17	Quantile attained on the reserve risk distribution with the booked Risk Adjustment
Skewness	Skewness of the overall aggregated risk distribution across all triangles input
CoV	Coefficient of Variation of the overall aggregated risk distribution across all triangles input
Res	Best Estimate reserve using a chain-ladder model applied on all input triangles
Totals	A summary of the above elements: Quantile attained on the reserve risk distribution with the booked Risk Adjustment, Skewness, Coefficient of Variation and Total Reserves

References

Thomas Mack. Distribution-free calculation of the standard error of chain ladder reserve estimates. Astin Bulletin. Vol. 23. No 2. 1993. pp.213:225

Thomas Mack. The standard error of chain ladder reserve estimates: Recursive calculation and inclusion of a tail factor. Astin Bulletin. Vol. 29. No 2. 1999. pp.361:366

Dal Moro, Krvavych. Probability of sufficiency of Solvency II Reserve risk margins: Practical approximations. ASTIN Bulletin, 47(3), 737-785

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

library(ChainLadder)
MyData <- read.csv(file="threeTriangles.csv", header=FALSE,  sep=";")
Mycorrel <- read.csv(file="correl1.csv", header=FALSE, sep=";")
RiskMargin=1000000

QuantileIF<-QuantileIFRS17(MyData, Mycorrel, 10000000)
QuantileIF$Totals

edalmoro/ChainLadderEDM documentation built on May 15, 2019, 1:14 p.m.