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tests/test-sst-example.R
In sstModel: Swiss Solvency Test (SST) Standard Models
# this is a complete example on how to simulate the target capital from the
# Swiss solvency test with the standalone sstModel package
# load package
library(sstModel)
# first step: define the market risks
## define the names of the base risk factors (Risiko Treiber).
name <- c("EURCHF", "USDCHF", # the fx rate risks
"equityCHF", "equityEUR", "equityUSD", # the equity risks
"kYCHF", "mYCHF", # the interest rate risks
"kYEUR", "mYEUR",
"PC1RateUSD", "PC2RateUSD", # here we use two PCA components
"AAACHF", "AAAEUR", "AAAUSD") # the spread risks
## then we need to define an appropriate correlation matrix
corr.mat <- diag(rep(1, 14))
colnames(corr.mat) <- name
rownames(corr.mat) <- name
## and the respective volatilities
volatility <- rep(0.05, 14)
# create cov mat
cov.mat <- diag(volatility, length(volatility), length(volatility)) %*%
corr.mat %*% diag(volatility, length(volatility), length(volatility))
colnames(cov.mat) <- rownames(cov.mat) <- colnames(corr.mat)
attr(cov.mat, "base.currency") <- "CHF"
## we should then build the mapping table of market risks
mapping.table <- mappingTable(currency(name = "EURCHF",
from = "EUR",
to = "CHF"),
currency(name = "USDCHF",
from = "USD",
to = "CHF"),
equity(name = "equityCHF",
type = "equity",
currency = "CHF"),
equity(name = "equityEUR",
type = "equity",
currency = "EUR"),
equity(name = "equityEUR",
type = "equity",
currency = "USD",
scale = 0.4694625),
pcRate(name = c("PC1RateUSD"),
currency = "USD"),
pcRate(name = c("PC2RateUSD"),
currency = "USD"),
pcRate(name = c("PC1RateUSD"),
currency = "EUR",
scale = 1),
pcRate(name = c("PC2RateUSD"),
currency = "EUR",
scale = 1),
rate(name = "kYCHF",
currency = "CHF",
horizon = "k"),
rate(name = c("PC1RateUSD",
"PC2RateUSD"),
currency = "EUR",
horizon = "k",
scale = c(0.1,
0.7)),
rate(name = c("PC1RateUSD",
"PC2RateUSD"),
currency = "USD",
horizon = "k",
scale = c(0.2,
0.5)),
rate(name = "mYCHF",
currency = "CHF",
horizon = "m"),
rate(name = c("PC1RateUSD",
"PC2RateUSD"),
currency = "EUR",
horizon = "m",
scale = c(0.05,
0.6)),
rate(name = c("PC1RateUSD",
"PC2RateUSD"),
currency = "USD",
horizon = "m",
scale = c(0.1,
0.9)),
spread(name = "AAACHF",
currency = "CHF",
rating = "AAA"),
spread(name = "AAAEUR",
currency = "EUR",
rating = "AAA"),
spread(name = "AAAUSD",
currency = "USD",
rating = "AAA"))
## and provide the initial values for the risks factors
initial.values <- list()
## initial fx
initial.values$initial.fx <- data.frame(from = c("EUR", "USD"),
to = c("CHF", "CHF"),
fx = c(1.05,1.02),
stringsAsFactors = F)
## initial rates
initial.values$initial.rate <- data.frame(time = c(2L, 2L, 2L, 10L, 10L, 10L),
currency = c("CHF", "EUR", "USD"),
rate = c(0.01, 0.01, 0.01, 0.03, 0.03, 0.03),
stringsAsFactors = F)
# define the mapped times for rates
mapping.time <- data.frame(time = c(2L, 10L), mapping = c("k","m"), stringsAsFactors = F)
## we are finally in shape to build the full market risk
mr <- marketRisk(cov.mat = cov.mat,
mapping.table = mapping.table,
base.currency = "CHF",
initial.values = initial.values,
mapping.time = mapping.time)
# second step: define the health and life risks
M <- matrix(c(1, 1, 1, 1), 2)
colnames(M) <- c("storno", "invalidity")
rownames(M) <- colnames(M)
lr <- lifeRisk(corr.mat = M,
quantile = c(0.995, 0.995))
hr <- healthRisk(corr.mat = M)
# third step: build the portfolio
list.assets <- list(asset(type = "equity", currency = "CHF", value = 30000000),
asset(type = "equity", currency = "EUR", value = 20000000),
asset(type = "equity", currency = "USD", value = 5000000))
list.liabilities <- list(liability(time = 2L, currency = "CHF", value = 400000),
liability(time = 2L, currency = "EUR", value = 700000),
liability(time = 2L, currency = "USD", value = 340000),
liability(time = 10L, currency = "CHF", value = 500000),
liability(time = 10L, currency = "EUR", value = 100000),
liability(time = 10L, currency = "USD", value = 240000))
list.asset.forward <- list(assetForward(type = "equity",
currency = "CHF",
time = 10L,
exposure = 10000,
price = 45000,
position = "long"))
list.marketItems <- append(append(append(append(list(), list.assets), list.liabilities),list.asset.forward),
list(delta(name = "EURCHF", currency = "CHF", sensitivity = 1000)))
valid.param <- list(mvm = list(mvm.life = 2, mvm.health = 4, mvm.nonlife = 3),
rtkr = 0,
rtkg = 0,
correction.term = 2,
credit.risk = 3,
expected.insurance.result = 10^6,
expected.financial.result = 10^5)
p <- portfolio(market.items = list.marketItems,
participation.item = participation(currency = "CHF", value = 3000),
life.item = life(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(100, 2000)),
health.item = health(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(230, 500)),
base.currency = "CHF",
portfolio.parameters = valid.param)
list.correlation.matrix <- list(base = matrix(c(1,0.15,0.075,0.15,
0.15,1,0.25,0.25,
0.075,0.25,1,0.15,
0.15,0.25,0.15,1), ncol=4, byrow = T),
scenario1 = matrix(c(1,1,1,0.35,
1,1,1,0.35,
1,1,1,0.35,
0.35,0.35,0.35,1), ncol=4, byrow = T),
scenario2 = matrix(c(1,0.6,0.5,0.25,
0.6,1,0.8,0.35,
0.5,0.8,1,0.35,
0.25,0.35,0.35,1), ncol=4, byrow = T),
scenario3 = matrix(c(1,0.25,0.25,0.5,
0.25,1,0.25,0.25,
0.25,0.25,1,0.25,
0.5,0.25,0.25,1), ncol=4, byrow = T))
list.correlation.matrix <- lapply(list.correlation.matrix, function(corr) {rownames(corr) <- colnames(corr) <- c("market", "life","health","nonlife"); corr})
# define the region boundaries (i.e. the thresholds t)
region.boundaries <- matrix(c(0.2,0.3,0.3,0.5,
0.5,0.2,0.2,0.8,
0.6,0.8,0.8,0.2), nrow=3, byrow = T)
colnames(region.boundaries) <- c("market", "life","health","nonlife")
rownames(region.boundaries) <- c("scenario1", "scenario2", "scenario3")
# scenario and region probabilities
scenario.probability = c(0.01, 0.01, 0.01)
region.probability = c(0.023, 0.034, 0.107)
## third step: define the sstModel
model <- sstModel(portfolio = p,
market.risk = mr,
life.risk = lr,
health.risk = hr,
nonlife.risk = nonLifeRisk(type = "simulations",
param = list(simulations = c(1, 2, 3, 4)),
currency = "CHF"),
nhmr = 0.06,
reordering.parameters = list(list.correlation.matrix = list(base=list.correlation.matrix[[1]])),
scenario.risk = scenarioRisk("tornado", 0.08, "CHF", -10000),
participation.risk = participationRisk(volatility = 0.5),
standalones = list(standalone(name = "std_equityCHF", equity(name = "equityCHF",
type = "equity",
currency = "CHF")),
standalone(name = "std_spreadAAACHF", spread(name = "AAACHF",
currency = "CHF",
rating = "AAA")),
standalone(name = "std_ratekCHF", rate(name = "kYCHF",
currency = "CHF",
horizon = "k"))
))
output <- compute(object = model, nsim = as.integer(100), nested.market.computations = T)
# life is null
p2 <- portfolio(market.items = list.marketItems,
participation.item = participation(currency = "CHF", value = 3000),
health.item = health(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(230, 500)),
base.currency = "CHF",
portfolio.parameters = valid.param)
model2 <- sstModel(portfolio = p2,
market.risk = mr,
health.risk = hr,
nonlife.risk = nonLifeRisk(type = "simulations",
param = list(simulations = c(1, 2, 3, 4)),
currency = "CHF"),
nhmr = 0.06,
reordering.parameters = list(list.correlation.matrix = list(base=list.correlation.matrix[[1]])),
scenario.risk = scenarioRisk("tornado", 0.08, "CHF", -10000),
participation.risk = participationRisk(volatility = 0.5),
standalones = list(standalone(name = "std_equityCHF", equity(name = "equityCHF",
type = "equity",
currency = "CHF")),
standalone(name = "std_spreadAAACHF", spread(name = "AAACHF",
currency = "CHF",
rating = "AAA")),
standalone(name = "std_ratekCHF", rate(name = "kYCHF",
currency = "CHF",
horizon = "k"))
))
output2 <- compute(object = model2, nsim = as.integer(100))
# health is null
p3 <- portfolio(market.items = list.marketItems,
participation.item = participation(currency = "CHF", value = 3000),
life.item = life(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(100, 2000)),
base.currency = "CHF",
portfolio.parameters = valid.param)
model3 <- sstModel(portfolio = p3,
market.risk = mr,
life.risk = lr,
nonlife.risk = nonLifeRisk(type = "simulations",
param = list(simulations = c(1, 2, 3, 4)),
currency = "CHF"),
nhmr = 0.06,
reordering.parameters = list(list.correlation.matrix = list(base=list.correlation.matrix[[1]])),
scenario.risk = scenarioRisk("tornado", 0.08, "CHF", -10000),
participation.risk = participationRisk(volatility = 0.5),
standalones = list(standalone(name = "std_equityCHF", equity(name = "equityCHF",
type = "equity",
currency = "CHF")),
standalone(name = "std_spreadAAACHF", spread(name = "AAACHF",
currency = "CHF",
rating = "AAA")),
standalone(name = "std_ratekCHF", rate(name = "kYCHF",
currency = "CHF",
horizon = "k"))
))
output3 <- compute(object = model3, nsim = as.integer(100))
# participation is null
p4 <- portfolio(market.items = list.marketItems,
life.item = life(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(100, 2000)),
health.item = health(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(230, 500)),
base.currency = "CHF",
portfolio.parameters = valid.param)
model4 <- sstModel(portfolio = p4,
market.risk = mr,
life.risk = lr,
health.risk = hr,
nonlife.risk = nonLifeRisk(type = "simulations",
param = list(simulations = c(1, 2, 3, 4)),
currency = "CHF"),
nhmr = 0.06,
reordering.parameters = list(list.correlation.matrix = list(base=list.correlation.matrix[[1]])),
scenario.risk = scenarioRisk("tornado", 0.08, "CHF", -10000),
standalones = list(standalone(name = "std_equityCHF", equity(name = "equityCHF",
type = "equity",
currency = "CHF")),
standalone(name = "std_spreadAAACHF", spread(name = "AAACHF",
currency = "CHF",
rating = "AAA")),
standalone(name = "std_ratekCHF", rate(name = "kYCHF",
currency = "CHF",
horizon = "k"))
))
output4 <- compute(object = model4, nsim = as.integer(100))
# only one market item with participation
p5 <- portfolio(market.items = list(list.marketItems[[1]]),
participation.item = participation(currency = "CHF", value = 3000),
life.item = life(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(100, 2000)),
health.item = health(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(230, 500)),
base.currency = "CHF",
portfolio.parameters = valid.param)
model5 <- sstModel(portfolio = p5,
market.risk = mr,
life.risk = lr,
health.risk = hr,
participation.risk = participationRisk(volatility = 0.5),
nonlife.risk = nonLifeRisk(type = "simulations",
param = list(simulations = c(1, 2, 3, 4)),
currency = "CHF"),
nhmr = 0.06,
reordering.parameters = list(list.correlation.matrix = list(base=list.correlation.matrix[[1]])),
scenario.risk = scenarioRisk("tornado", 0.08, "CHF", -10000),
standalones = list(standalone(name = "std_equityCHF", equity(name = "equityCHF",
type = "equity",
currency = "CHF")),
standalone(name = "std_spreadAAACHF", spread(name = "AAACHF",
currency = "CHF",
rating = "AAA")),
standalone(name = "std_ratekCHF", rate(name = "kYCHF",
currency = "CHF",
horizon = "k"))
))
output5 <- compute(object = model5, nsim = as.integer(100))
# only one market item without participation
p6 <- portfolio(market.items = list(list.marketItems[[1]]),
life.item = life(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(100, 2000)),
health.item = health(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(230, 500)),
base.currency = "CHF",
portfolio.parameters = valid.param)
model6 <- sstModel(portfolio = p6,
market.risk = mr,
life.risk = lr,
health.risk = hr,
nonlife.risk = nonLifeRisk(type = "simulations",
param = list(simulations = c(1, 2, 3, 4)),
currency = "CHF"),
nhmr = 0.06,
reordering.parameters = list(list.correlation.matrix = list(base=list.correlation.matrix[[1]])),
scenario.risk = scenarioRisk("tornado", 0.08, "CHF", -10000),
standalones = list(standalone(name = "std_equityCHF", equity(name = "equityCHF",
type = "equity",
currency = "CHF")),
standalone(name = "std_spreadAAACHF", spread(name = "AAACHF",
currency = "CHF",
rating = "AAA")),
standalone(name = "std_ratekCHF", rate(name = "kYCHF",
currency = "CHF",
horizon = "k"))
))
output6 <- compute(object = model6, nsim = as.integer(100))
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# this is a complete example on how to simulate the target capital from the
# Swiss solvency test with the standalone sstModel package
# load package
library(sstModel)
# first step: define the market risks
## define the names of the base risk factors (Risiko Treiber).
name <- c("EURCHF", "USDCHF", # the fx rate risks
"equityCHF", "equityEUR", "equityUSD", # the equity risks
"kYCHF", "mYCHF", # the interest rate risks
"kYEUR", "mYEUR",
"PC1RateUSD", "PC2RateUSD", # here we use two PCA components
"AAACHF", "AAAEUR", "AAAUSD") # the spread risks
## then we need to define an appropriate correlation matrix
corr.mat <- diag(rep(1, 14))
colnames(corr.mat) <- name
rownames(corr.mat) <- name
## and the respective volatilities
volatility <- rep(0.05, 14)
# create cov mat
cov.mat <- diag(volatility, length(volatility), length(volatility)) %*%
corr.mat %*% diag(volatility, length(volatility), length(volatility))
colnames(cov.mat) <- rownames(cov.mat) <- colnames(corr.mat)
attr(cov.mat, "base.currency") <- "CHF"
## we should then build the mapping table of market risks
mapping.table <- mappingTable(currency(name = "EURCHF",
from = "EUR",
to = "CHF"),
currency(name = "USDCHF",
from = "USD",
to = "CHF"),
equity(name = "equityCHF",
type = "equity",
currency = "CHF"),
equity(name = "equityEUR",
type = "equity",
currency = "EUR"),
equity(name = "equityEUR",
type = "equity",
currency = "USD",
scale = 0.4694625),
pcRate(name = c("PC1RateUSD"),
currency = "USD"),
pcRate(name = c("PC2RateUSD"),
currency = "USD"),
pcRate(name = c("PC1RateUSD"),
currency = "EUR",
scale = 1),
pcRate(name = c("PC2RateUSD"),
currency = "EUR",
scale = 1),
rate(name = "kYCHF",
currency = "CHF",
horizon = "k"),
rate(name = c("PC1RateUSD",
"PC2RateUSD"),
currency = "EUR",
horizon = "k",
scale = c(0.1,
0.7)),
rate(name = c("PC1RateUSD",
"PC2RateUSD"),
currency = "USD",
horizon = "k",
scale = c(0.2,
0.5)),
rate(name = "mYCHF",
currency = "CHF",
horizon = "m"),
rate(name = c("PC1RateUSD",
"PC2RateUSD"),
currency = "EUR",
horizon = "m",
scale = c(0.05,
0.6)),
rate(name = c("PC1RateUSD",
"PC2RateUSD"),
currency = "USD",
horizon = "m",
scale = c(0.1,
0.9)),
spread(name = "AAACHF",
currency = "CHF",
rating = "AAA"),
spread(name = "AAAEUR",
currency = "EUR",
rating = "AAA"),
spread(name = "AAAUSD",
currency = "USD",
rating = "AAA"))
## and provide the initial values for the risks factors
initial.values <- list()
## initial fx
initial.values$initial.fx <- data.frame(from = c("EUR", "USD"),
to = c("CHF", "CHF"),
fx = c(1.05,1.02),
stringsAsFactors = F)
## initial rates
initial.values$initial.rate <- data.frame(time = c(2L, 2L, 2L, 10L, 10L, 10L),
currency = c("CHF", "EUR", "USD"),
rate = c(0.01, 0.01, 0.01, 0.03, 0.03, 0.03),
stringsAsFactors = F)
# define the mapped times for rates
mapping.time <- data.frame(time = c(2L, 10L), mapping = c("k","m"), stringsAsFactors = F)
## we are finally in shape to build the full market risk
mr <- marketRisk(cov.mat = cov.mat,
mapping.table = mapping.table,
base.currency = "CHF",
initial.values = initial.values,
mapping.time = mapping.time)
# second step: define the health and life risks
M <- matrix(c(1, 1, 1, 1), 2)
colnames(M) <- c("storno", "invalidity")
rownames(M) <- colnames(M)
lr <- lifeRisk(corr.mat = M,
quantile = c(0.995, 0.995))
hr <- healthRisk(corr.mat = M)
# third step: build the portfolio
list.assets <- list(asset(type = "equity", currency = "CHF", value = 30000000),
asset(type = "equity", currency = "EUR", value = 20000000),
asset(type = "equity", currency = "USD", value = 5000000))
list.liabilities <- list(liability(time = 2L, currency = "CHF", value = 400000),
liability(time = 2L, currency = "EUR", value = 700000),
liability(time = 2L, currency = "USD", value = 340000),
liability(time = 10L, currency = "CHF", value = 500000),
liability(time = 10L, currency = "EUR", value = 100000),
liability(time = 10L, currency = "USD", value = 240000))
list.asset.forward <- list(assetForward(type = "equity",
currency = "CHF",
time = 10L,
exposure = 10000,
price = 45000,
position = "long"))
list.marketItems <- append(append(append(append(list(), list.assets), list.liabilities),list.asset.forward),
list(delta(name = "EURCHF", currency = "CHF", sensitivity = 1000)))
valid.param <- list(mvm = list(mvm.life = 2, mvm.health = 4, mvm.nonlife = 3),
rtkr = 0,
rtkg = 0,
correction.term = 2,
credit.risk = 3,
expected.insurance.result = 10^6,
expected.financial.result = 10^5)
p <- portfolio(market.items = list.marketItems,
participation.item = participation(currency = "CHF", value = 3000),
life.item = life(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(100, 2000)),
health.item = health(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(230, 500)),
base.currency = "CHF",
portfolio.parameters = valid.param)
list.correlation.matrix <- list(base = matrix(c(1,0.15,0.075,0.15,
0.15,1,0.25,0.25,
0.075,0.25,1,0.15,
0.15,0.25,0.15,1), ncol=4, byrow = T),
scenario1 = matrix(c(1,1,1,0.35,
1,1,1,0.35,
1,1,1,0.35,
0.35,0.35,0.35,1), ncol=4, byrow = T),
scenario2 = matrix(c(1,0.6,0.5,0.25,
0.6,1,0.8,0.35,
0.5,0.8,1,0.35,
0.25,0.35,0.35,1), ncol=4, byrow = T),
scenario3 = matrix(c(1,0.25,0.25,0.5,
0.25,1,0.25,0.25,
0.25,0.25,1,0.25,
0.5,0.25,0.25,1), ncol=4, byrow = T))
list.correlation.matrix <- lapply(list.correlation.matrix, function(corr) {rownames(corr) <- colnames(corr) <- c("market", "life","health","nonlife"); corr})
# define the region boundaries (i.e. the thresholds t)
region.boundaries <- matrix(c(0.2,0.3,0.3,0.5,
0.5,0.2,0.2,0.8,
0.6,0.8,0.8,0.2), nrow=3, byrow = T)
colnames(region.boundaries) <- c("market", "life","health","nonlife")
rownames(region.boundaries) <- c("scenario1", "scenario2", "scenario3")
# scenario and region probabilities
scenario.probability = c(0.01, 0.01, 0.01)
region.probability = c(0.023, 0.034, 0.107)
## third step: define the sstModel
model <- sstModel(portfolio = p,
market.risk = mr,
life.risk = lr,
health.risk = hr,
nonlife.risk = nonLifeRisk(type = "simulations",
param = list(simulations = c(1, 2, 3, 4)),
currency = "CHF"),
nhmr = 0.06,
reordering.parameters = list(list.correlation.matrix = list(base=list.correlation.matrix[[1]])),
scenario.risk = scenarioRisk("tornado", 0.08, "CHF", -10000),
participation.risk = participationRisk(volatility = 0.5),
standalones = list(standalone(name = "std_equityCHF", equity(name = "equityCHF",
type = "equity",
currency = "CHF")),
standalone(name = "std_spreadAAACHF", spread(name = "AAACHF",
currency = "CHF",
rating = "AAA")),
standalone(name = "std_ratekCHF", rate(name = "kYCHF",
currency = "CHF",
horizon = "k"))
))
output <- compute(object = model, nsim = as.integer(100), nested.market.computations = T)
# life is null
p2 <- portfolio(market.items = list.marketItems,
participation.item = participation(currency = "CHF", value = 3000),
health.item = health(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(230, 500)),
base.currency = "CHF",
portfolio.parameters = valid.param)
model2 <- sstModel(portfolio = p2,
market.risk = mr,
health.risk = hr,
nonlife.risk = nonLifeRisk(type = "simulations",
param = list(simulations = c(1, 2, 3, 4)),
currency = "CHF"),
nhmr = 0.06,
reordering.parameters = list(list.correlation.matrix = list(base=list.correlation.matrix[[1]])),
scenario.risk = scenarioRisk("tornado", 0.08, "CHF", -10000),
participation.risk = participationRisk(volatility = 0.5),
standalones = list(standalone(name = "std_equityCHF", equity(name = "equityCHF",
type = "equity",
currency = "CHF")),
standalone(name = "std_spreadAAACHF", spread(name = "AAACHF",
currency = "CHF",
rating = "AAA")),
standalone(name = "std_ratekCHF", rate(name = "kYCHF",
currency = "CHF",
horizon = "k"))
))
output2 <- compute(object = model2, nsim = as.integer(100))
# health is null
p3 <- portfolio(market.items = list.marketItems,
participation.item = participation(currency = "CHF", value = 3000),
life.item = life(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(100, 2000)),
base.currency = "CHF",
portfolio.parameters = valid.param)
model3 <- sstModel(portfolio = p3,
market.risk = mr,
life.risk = lr,
nonlife.risk = nonLifeRisk(type = "simulations",
param = list(simulations = c(1, 2, 3, 4)),
currency = "CHF"),
nhmr = 0.06,
reordering.parameters = list(list.correlation.matrix = list(base=list.correlation.matrix[[1]])),
scenario.risk = scenarioRisk("tornado", 0.08, "CHF", -10000),
participation.risk = participationRisk(volatility = 0.5),
standalones = list(standalone(name = "std_equityCHF", equity(name = "equityCHF",
type = "equity",
currency = "CHF")),
standalone(name = "std_spreadAAACHF", spread(name = "AAACHF",
currency = "CHF",
rating = "AAA")),
standalone(name = "std_ratekCHF", rate(name = "kYCHF",
currency = "CHF",
horizon = "k"))
))
output3 <- compute(object = model3, nsim = as.integer(100))
# participation is null
p4 <- portfolio(market.items = list.marketItems,
life.item = life(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(100, 2000)),
health.item = health(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(230, 500)),
base.currency = "CHF",
portfolio.parameters = valid.param)
model4 <- sstModel(portfolio = p4,
market.risk = mr,
life.risk = lr,
health.risk = hr,
nonlife.risk = nonLifeRisk(type = "simulations",
param = list(simulations = c(1, 2, 3, 4)),
currency = "CHF"),
nhmr = 0.06,
reordering.parameters = list(list.correlation.matrix = list(base=list.correlation.matrix[[1]])),
scenario.risk = scenarioRisk("tornado", 0.08, "CHF", -10000),
standalones = list(standalone(name = "std_equityCHF", equity(name = "equityCHF",
type = "equity",
currency = "CHF")),
standalone(name = "std_spreadAAACHF", spread(name = "AAACHF",
currency = "CHF",
rating = "AAA")),
standalone(name = "std_ratekCHF", rate(name = "kYCHF",
currency = "CHF",
horizon = "k"))
))
output4 <- compute(object = model4, nsim = as.integer(100))
# only one market item with participation
p5 <- portfolio(market.items = list(list.marketItems[[1]]),
participation.item = participation(currency = "CHF", value = 3000),
life.item = life(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(100, 2000)),
health.item = health(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(230, 500)),
base.currency = "CHF",
portfolio.parameters = valid.param)
model5 <- sstModel(portfolio = p5,
market.risk = mr,
life.risk = lr,
health.risk = hr,
participation.risk = participationRisk(volatility = 0.5),
nonlife.risk = nonLifeRisk(type = "simulations",
param = list(simulations = c(1, 2, 3, 4)),
currency = "CHF"),
nhmr = 0.06,
reordering.parameters = list(list.correlation.matrix = list(base=list.correlation.matrix[[1]])),
scenario.risk = scenarioRisk("tornado", 0.08, "CHF", -10000),
standalones = list(standalone(name = "std_equityCHF", equity(name = "equityCHF",
type = "equity",
currency = "CHF")),
standalone(name = "std_spreadAAACHF", spread(name = "AAACHF",
currency = "CHF",
rating = "AAA")),
standalone(name = "std_ratekCHF", rate(name = "kYCHF",
currency = "CHF",
horizon = "k"))
))
output5 <- compute(object = model5, nsim = as.integer(100))
# only one market item without participation
p6 <- portfolio(market.items = list(list.marketItems[[1]]),
life.item = life(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(100, 2000)),
health.item = health(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(230, 500)),
base.currency = "CHF",
portfolio.parameters = valid.param)
model6 <- sstModel(portfolio = p6,
market.risk = mr,
life.risk = lr,
health.risk = hr,
nonlife.risk = nonLifeRisk(type = "simulations",
param = list(simulations = c(1, 2, 3, 4)),
currency = "CHF"),
nhmr = 0.06,
reordering.parameters = list(list.correlation.matrix = list(base=list.correlation.matrix[[1]])),
scenario.risk = scenarioRisk("tornado", 0.08, "CHF", -10000),
standalones = list(standalone(name = "std_equityCHF", equity(name = "equityCHF",
type = "equity",
currency = "CHF")),
standalone(name = "std_spreadAAACHF", spread(name = "AAACHF",
currency = "CHF",
rating = "AAA")),
standalone(name = "std_ratekCHF", rate(name = "kYCHF",
currency = "CHF",
horizon = "k"))
))
output6 <- compute(object = model6, nsim = as.integer(100))
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