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Commit 1bccc58d authored by Reinhold Kainhofer's avatar Reinhold Kainhofer
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Implement premium calculation (grosss, net, Zillmer, written, tax)

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Formulas_Reference/.gitignore
+ 1
− 0
View file @ 1bccc58d
......@@ -4,3 +4,4 @@
*.synctex.gz
*.backup
*.kilepr
Bernkopf Max
R/HelperFunctions.R
+ 12
− 3
View file @ 1bccc58d
......@@ -56,11 +56,13 @@ calculatePVDeath = function(q, benefits, ..., v=1) {
}
correctionPaymentsPerYear = function(m = 1, i = self$i, order = 0) {
correctionPaymentFrequency = function(m = 1, i = self$i, order = 0) {
# 0th-order approximation
alpha=1;
beta=(m-1)/(2*m);
beta=0;
# negative orders mean that NO correction is done, e.g. because other means of
# correction are used like an explicit premium frequency loading on the premium.
if (order >=0 ) beta = beta + (m-1)/(2*m);
# For higher orders, simply add one term after the other!
if (order >= 1) beta = beta + (m^2-1)/(6*m^2)*i;
# order 1.5 has a special term that should NOT be used for higher-order approximations!
......@@ -90,3 +92,10 @@ pad0 = function(v, l, value=0) {
}
}
valueOrFunction = function(val, ...) {
if (is.function(val)) {
val(...)
} else {
val
}
}
R/InsuranceTarif.R
+ 125
− 196
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This diff is collapsed.
R/ValuationTables.R
+ 28
− 21
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......@@ -3,26 +3,26 @@ library(ggplot2);
# (virtual) base class for valuation tables, contains only the name / ID
valuationTable=setClass(
"valuationTable",
slots=list(name="character", baseYear="numeric"),
prototype=list(name="Actuarial Valuation Table", baseYear=2000),
"valuationTable",
slots=list(name="character", baseYear="numeric"),
prototype=list(name="Actuarial Valuation Table", baseYear=2000),
contains="VIRTUAL"
);
# A period life table, giving death probabilities for each age, up to
# A period life table, giving death probabilities for each age, up to
# maximum age omega. Optionally apply selection factors to the probabilities
valuationTable.period=setClass(
"valuationTable.period",
"valuationTable.period",
slots=list(ages="numeric", deathProbs="numeric"),
prototype=list(ages=eval(0:120), deathProbs=rep(1,120)),
contains="valuationTable"
);
# A cohort life table, obtained by age-shifting from a given base table (PODs
# A cohort life table, obtained by age-shifting from a given base table (PODs
# for a base YOB)
valuationTable.ageShift=setClass(
"valuationTable.ageShift",
"valuationTable.ageShift",
slots=list(ageShifts="data.frame"),
prototype=list(ageShifts=data.frame(YOB=c(), shifts=c())),
contains="valuationTable.period"
......@@ -34,25 +34,25 @@ valuationTable.ageShift=setClass(
# The dampingFunction can be used to modify the cumulative years (e.g. G(tau+x) instead of tau+x)
# If trend2 is given, the G(tau+x) gives the weight of the first trend, 1-G(tau+x) the weight of the second trend
valuationTable.trendProjection=setClass(
"valuationTable.trendProjection",
"valuationTable.trendProjection",
slots=list(baseYear="numeric", trend="numeric", dampingFunction="function", trend2="numeric"),
prototype=list(baseYear=1980, trend=rep(0,120), dampingFunction=identity, trend2=0),
contains="valuationTable.period"
);
# A cohort life table, obtained by an improvment factor projection
# A cohort life table, obtained by an improvment factor projection
# from a given base table (PODs for a given observation year).
valuationTable.improvementFactors=setClass(
"valuationTable.improvementFactors",
"valuationTable.improvementFactors",
slots=list(baseYear="numeric", improvement="numeric"),
prototype=list(baseYear=2012, improvement=rep(0,120)),
contains="valuationTable.period"
);
# A cohort life table described by actual observations (data frame of PODs
# A cohort life table described by actual observations (data frame of PODs
# per year and age)
valuationTable.observed=setClass(
"valuationTable.observed",
"valuationTable.observed",
slots=list(data="data.frame"),
prototype=list(data=data.frame()),
contains="valuationTable"
......@@ -62,15 +62,15 @@ valuationTable.observed=setClass(
# applies only to certain observation years (e.g. for the past use the observed
# PODs, and project them to the future with the trend projection)
valuationTable.joined=setClass(
"valuationTable.joined",
"valuationTable.joined",
slots=list(
table1="valuationTable", yearRange1="numeric",
table1="valuationTable", yearRange1="numeric",
table2="valuationTable", yearRange2="numeric"),
contains="valuationTable"
);
# A cohort life table obtained by mixing two life tables with the given weights
valuationTable.mixed=setClass(
"valuationTable.mixed",
"valuationTable.mixed",
slots=c(table1="valuationTable", table2="valuationTable", weight1="numeric", weight2="numeric"),
prototype=list(weight1=1/2, weight2=1/2),
contains="valuationTable"
......@@ -212,9 +212,9 @@ setGeneric("getPeriodTable", function(object, Period, ...) standardGeneric("getP
setMethod("getPeriodTable","valuationTable",
function (object, Period, ...) {
valuationTable.period(
name = paste(object@name, ", Period ", Period),
name = paste(object@name, ", Period ", Period),
baseYear = Period,
ages = ages(object),
ages = ages(object),
deathProbs = periodDeathProbabilities(object, Period=Period)
)
})
......@@ -225,12 +225,19 @@ setMethod("getCohortTable","valuationTable",
valuationTable.period(
name = paste(object@name, ", YOB ", YOB),
baseYear = YOB,
ages=ages(object),
ages=ages(object),
deathProbs=deathProbabilities(object, YOB=YOB)
);
})
setGeneric("undampenTrend", function (object) standardGeneric("undampenTrend"));
setMethod("undampenTrend", "valuationTable.trendProjection",
function (object) {
object@dampingFunction=identity;
object
});
makeQxDataFrame = function(..., YOB=1972, Period=NA) {
data=list(...);
......@@ -242,7 +249,7 @@ makeQxDataFrame = function(..., YOB=1972, Period=NA) {
cat("Period: ", Period,"\n");
data = lapply(data, function(t) cbind(x=t@ages, y=periodDeathProbabilities(t, Period=Period)))
}
list.names = names(data)
lns <- sapply(data, nrow)
data <- as.data.frame(do.call("rbind", data))
......@@ -254,7 +261,7 @@ plotValuationTables = function(data, ..., title = "", legend.position=c(0.9,0.1)
if (!is.data.frame(data)) {
data = makeQxDataFrame(data, ...);
}
pl = ggplot(data, aes(x = x, y = y, colour = data$group)) +
theme_bw() +
theme(
......@@ -280,7 +287,7 @@ plotValuationTables = function(data, ..., title = "", legend.position=c(0.9,0.1)
breaks = function (limits) seq(max(min(limits),0),max(limits),5),
minor_breaks = function (limits) seq(max(round(min(limits)),0),round(max(limits)),1),
#labels = scales::trans_format('log10', scales::math_format(10^.x))
) +
annotation_logticks(sides="lr") +
xlab("Alter") + labs(colour="Sterbetafel");
......
R/ValuationTables_Austria_Annuities.R
+ 33
− 23
View file @ 1bccc58d
......@@ -4,6 +4,7 @@
# rm(frame_files)
# setwd(dirname(PATH))
setwd("R")
library("gdata")
......@@ -13,8 +14,8 @@ library("gdata")
###############################################################################
rr67.data=read.xls(
"Tafeln/AVOe_R.xls",
sheet="OeVM59-61 RR67", skip=1, #row.names=1,
"Tables/AVOe_R.xls",
sheet="OeVM59-61 RR67", skip=1, #row.names=1,
col.names=c("age","qx"));
rr67=valuationTable.period(
......@@ -28,8 +29,8 @@ rr67=valuationTable.period(
###############################################################################
eromf.data=read.xls(
"Tafeln/AVOe_R.xls",
sheet="EROM-F Basistafeln", skip=2, #row.names=1,
"Tables/AVOe_R.xls",
sheet="EROM-F Basistafeln", skip=2, #row.names=1,
col.names=c("age", "EROM85", "EROF85", "EROMG1950", "EROFG1950","","","")
);
......@@ -55,8 +56,8 @@ EROF.G1950.female=valuationTable.period(
);
eromf.data.av=read.xls(
"Tafeln/AVOe_R.xls",
sheet="EROM-F G AV", skip=1, row.names=1,
"Tables/AVOe_R.xls",
sheet="EROM-F G AV", skip=1, row.names=1,
col.names=c("YOB", "shiftM", "shiftF")
);
......@@ -81,8 +82,8 @@ EROF.G1950.female.av=valuationTable.ageShift(
###############################################################################
AVOe1996R.exakt.data=read.xls(
"Tafeln/AVOe_R.xls",
sheet="AVOe 1996R exakt", skip=2, #row.names=1,
"Tables/AVOe_R.xls",
sheet="AVOe 1996R exakt", skip=2, #row.names=1,
col.names=c("age",
"q1991M", "trendM.long", "trendM.short", "factorMG", "factorM",
"",
......@@ -106,7 +107,7 @@ AVOe1996R.trend.switching=function(year) {
AVÖ1996R.male=valuationTable.trendProjection(
name="AVÖ 1996R male",
ages=AVOe1996R.exakt.data$age, baseYear=1991,
deathProbs=AVOe1996R.exakt.data$q1991M*AVOe1996R.exakt.data$factorM,
deathProbs=AVOe1996R.exakt.data$q1991M*AVOe1996R.exakt.data$factorM,
trend=AVOe1996R.exakt.data$trendM.long,
trend2=AVOe1996R.exakt.data$trendM.short,
dampingFunction=AVOe1996R.trend.switching
......@@ -114,7 +115,7 @@ AVÖ1996R.male=valuationTable.trendProjection(
AVÖ1996R.female=valuationTable.trendProjection(
name="AVÖ 1996R female",
ages=AVOe1996R.exakt.data$age, baseYear=1991,
deathProbs=AVOe1996R.exakt.data$q1991F*AVOe1996R.exakt.data$factorF,
deathProbs=AVOe1996R.exakt.data$q1991F*AVOe1996R.exakt.data$factorF,
trend=AVOe1996R.exakt.data$trendF.long,
trend2=AVOe1996R.exakt.data$trendF.short,
dampingFunction=AVOe1996R.trend.switching
......@@ -122,7 +123,7 @@ AVÖ1996R.female=valuationTable.trendProjection(
AVÖ1996R.male.group=valuationTable.trendProjection(
name="AVÖ 1996R male, group",
ages=AVOe1996R.exakt.data$age, baseYear=1991,
deathProbs=AVOe1996R.exakt.data$q1991M*AVOe1996R.exakt.data$factorMG,
deathProbs=AVOe1996R.exakt.data$q1991M*AVOe1996R.exakt.data$factorMG,
trend=AVOe1996R.exakt.data$trendM.long,
trend2=AVOe1996R.exakt.data$trendM.short,
dampingFunction=AVOe1996R.trend.switching
......@@ -130,7 +131,7 @@ AVÖ1996R.male.group=valuationTable.trendProjection(
AVÖ1996R.female.group=valuationTable.trendProjection(
name="AVÖ 1996R female, group",
ages=AVOe1996R.exakt.data$age, baseYear=1991,
deathProbs=AVOe1996R.exakt.data$q1991F*AVOe1996R.exakt.data$factorFG,
deathProbs=AVOe1996R.exakt.data$q1991F*AVOe1996R.exakt.data$factorFG,
trend=AVOe1996R.exakt.data$trendF.long,
trend2=AVOe1996R.exakt.data$trendF.short,
dampingFunction=AVOe1996R.trend.switching
......@@ -144,16 +145,16 @@ AVÖ1996R.female.group=valuationTable.trendProjection(
###############################################################################
AVOe2005R.exakt.data=read.xls(
"Tafeln/AVOe_R.xls",
sheet="AVOe 2005R", skip=3, #row.names=1,
"Tables/AVOe_R.xls",
sheet="AVOe 2005R", skip=3, #row.names=1,
header=FALSE,
col.names=c("age",
"q2001M","q2001MG", "trendM",
"q2001F", "q2001FG", "trendF",
"",
"q2001M.2Ord", "2001MG.2Ord", "trendM.2Ord",
"q2001F.2Ord", "q2001FG.2Ord", "trendF.2Ord",
"",
col.names=c("age",
"q2001M","q2001MG", "trendM",
"q2001F", "q2001FG", "trendF",
"",
"q2001M.2Ord", "2001MG.2Ord", "trendM.2Ord",
"q2001F.2Ord", "q2001FG.2Ord", "trendF.2Ord",
"",
"q2001U", "q2001UG", "trendU",
rep("", 10))
);
......@@ -182,19 +183,28 @@ AVOe2005R.male.group =AVOe2005R_gen("AVÖ 2005R male group (exact), loaded",
AVOe2005R.female.group=AVOe2005R_gen("AVÖ 2005R female group (exact), loaded", "q2001FG", "trendF");
AVOe2005R.unisex.group=AVOe2005R_gen("AVÖ 2005R unisex group (exact), loaded", "q2001UG", "trendU");
AVOe2005R.male.nodamping = undampenTrend(AVOe2005R.male);
AVOe2005R.female.nodamping = undampenTrend(AVOe2005R.female);
AVOe2005R.unisex.nodamping = undampenTrend(AVOe2005R.unisex);
AVOe2005R.male.nodamping.unloaded = undampenTrend(AVOe2005R.male.unloaded);
AVOe2005R.female.nodamping.unloaded = undampenTrend(AVOe2005R.female.unloaded);
AVOe2005R.male.nodamping.group = undampenTrend(AVOe2005R.male.group);
AVOe2005R.female.nodamping.group = undampenTrend(AVOe2005R.female.group);
AVOe2005R.unisex.nodamping.group = undampenTrend(AVOe2005R.unisex.group);
###############################################################################
#AVÖ 2005R with age-shifting (Male, Female, unisex), 1st-order only
###############################################################################
AVOe2005R.av.base=read.xls(
"Tafeln/AVOe_R.xls",
"Tables/AVOe_R.xls",
sheet="AVOe 2005R AV Basistafel", skip=1, # row.names=1,
col.names=c("age", "q1965M", "q1965MG", "q1965F", "q1965FG", "q1972U", "q1972UG")
);
AVOe2005R.av.verschiebung=read.xls(
"Tafeln/AVOe_R.xls",
"Tables/AVOe_R.xls",
sheet="AVOe 2005R AV Verschiebung",skip=2,row.names=1,
col.names=c("YOB", "shiftM", "shiftMG", "shiftF", "shiftFG", "shiftU", "shiftUG")
)
......
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