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tests/testthat/test-sstModel.R
In sstModel: Swiss Solvency Test (SST) Standard Models
# unit tests for sstModel
context("S3 classe sstModel")
# checking constructor
test_that("sstModel is ok", {
## building marketRisk
cov.mat <- diag(2, 4, 4) %*% diag(rep(1, 4)) %*% diag(2, 4, 4)
name <- c("EURCHF", "equityCHF", "2YCHF", "AAACHF")
colnames(cov.mat) <- name
rownames(cov.mat) <- name
attr(cov.mat, "base.currency") <- "CHF"
mapping.table <- mappingTable(currency(name = "EURCHF",
from = "EUR",
to = "CHF"),
equity(name = "equityCHF",
type = "equity",
currency = "CHF"),
rate(name = "2YCHF",
currency = "CHF",
horizon = "k"),
spread(name = "AAACHF",
currency = "CHF",
rating = "AAA"),
rate(name = "2YCHF",
currency = "EUR",
horizon = "k",
scale = 0.8))
initial.values <- list()
initial.values$initial.fx <- data.frame(from = "EUR",
to = "CHF",
fx = 1.05,
stringsAsFactors = F)
initial.values$initial.rate <- data.frame(time = 1L,
currency = c("CHF", "EUR"),
rate = c(0.01, 0.01),
stringsAsFactors = F)
mapping.time <- data.frame(time = 1L, mapping = "k", stringsAsFactors = F)
## define an economic scenario
eco.table <- matrix(c(1,1,1,1,2,2,1,4,2,3), nrow=2)
colnames(eco.table) <- c(name, "participation")
rownames(eco.table) <- c("sc1","sc2")
eco.scenario <- macroEconomicScenarios(macro.economic.scenario.table = eco.table)
mr <- marketRisk(cov.mat = cov.mat,
mapping.table = mapping.table,
initial.values = initial.values,
mapping.time = mapping.time,
base.currency = "CHF")
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)
valid.param <- list(mvm = 3,
rtkr = 0,
rtkg = 0,
credit.risk = 3,
correction.term = 3,
expected.insurance.result = 10^6,
expected.financial.result = 10^5)
valid.param <- list(mvm = list(mvm.life = 2, mvm.health = 4, mvm.nonlife = 3),
rtkr = 0,
rtkg = 0,
credit.risk = 3,
correction.term = 3,
expected.insurance.result = 10^6,
expected.financial.result = 10^5)
p <- portfolio(market.items = list(asset(type = "equity", currency = "CHF", value = 1000),
liability(time = 1L, currency = "CHF", value = -400),
cashflow(time = 1L, currency = "CHF", rating = "AAA", 0.06, value = 500),
delta(name = "EURCHF", currency = "CHF", sensitivity = 30)),
participation.item = participation(currency = "CHF", value = 200),
life.item = life(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(10, 10)),
health.item = health(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(10, 10)),
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)
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"),
scenario.risk = scenarioRisk("tornado", 0.08, "CHF", -10),
participation.risk = participationRisk(volatility = 3),
macro.economic.scenarios = eco.scenario,
nhmr = 0.06,
reordering.parameters = list(list.correlation.matrix = list.correlation.matrix,
region.boundaries = region.boundaries,
region.probability = region.probability,
scenario.probability = scenario.probability),
standalones = list(standalone(name = "equity", equity(name = "equityCHF",
type = "equity",
currency = "CHF")),
standalone(name = "something", spread(name = "AAACHF",
currency = "CHF",
rating = "AAA"),
rate(name = "2YCHF",
currency = "EUR",
horizon = "k",
scale = 0.8))))
expect_error(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"),
scenario.risk = scenarioRisk("tornado", 0.08, "CHF", -10),
participation.risk = participationRisk(volatility = 3),
macro.economic.scenarios = eco.scenario,
nhmr = 0.06,
reordering.parameters = list(list.correlation.matrix = list.correlation.matrix,
region.boundaries = region.boundaries,
region.probability = region.probability,
scenario.probability = scenario.probability),
standalones = list(standalone(name = "equity", equity(name = "equityCHF",
type = "equity",
currency = "CHF")),
standalone(name = "something", spread(name = "AAACHF",
currency = "CHF",
rating = "AAA"),
rate(name = "2YCHF",
currency = "EUR",
horizon = "l")))),
"standalones")
expect_error(sstModel(portfolio = p,
market.risk = mr,
life.risk = NULL,
health.risk = hr,
nonlife.risk = nonLifeRisk(type = "simulations",
param = list(simulations=c(1, 2, 3, 4)),
currency = "CHF"),
scenario.risk = scenarioRisk("tornado", 0.08, "EUR", -10),
participation.risk = participationRisk(volatility = 3),
macro.economic.scenarios = eco.scenario,
nhmr = 0.06,
reordering.parameters = list(list.correlation.matrix = list.correlation.matrix,
region.boundaries = region.boundaries,
region.probability = region.probability,
scenario.probability = scenario.probability),
standalones = list(standalone(name = "equity", equity(name = "equityCHF",
type = "equity",
currency = "CHF")),
standalone(name = "something", spread(name = "AAACHF",
currency = "CHF",
rating = "AAA"),
rate(name = "2YCHF",
currency = "EUR",
horizon = "k",
scale = 0.8)))),
"Missing")
expect_error(sstModel(portfolio = p,
market.risk = mr,
life.risk = lr,
health.risk = NULL,
nonlife.risk = NULL,
scenario.risk = scenarioRisk("tornado", 0.08, "EUR", -10),
participation.risk = participationRisk(volatility = 3),
macro.economic.scenarios = eco.scenario,
nhmr = 0.06,
reordering.parameters = list(list.correlation.matrix = list.correlation.matrix,
region.boundaries = region.boundaries,
region.probability = region.probability,
scenario.probability = scenario.probability),
standalones = list(standalone(name = "equity", equity(name = "equityCHF",
type = "equity",
currency = "CHF")),
standalone(name = "something", spread(name = "AAACHF",
currency = "CHF",
rating = "AAA"),
rate(name = "2YCHF",
currency = "EUR",
horizon = "k",
scale = 0.8)))),
"Missing")
})
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sstModel documentation built on May 2, 2019, 12:16 p.m.
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# unit tests for sstModel
context("S3 classe sstModel")
# checking constructor
test_that("sstModel is ok", {
## building marketRisk
cov.mat <- diag(2, 4, 4) %*% diag(rep(1, 4)) %*% diag(2, 4, 4)
name <- c("EURCHF", "equityCHF", "2YCHF", "AAACHF")
colnames(cov.mat) <- name
rownames(cov.mat) <- name
attr(cov.mat, "base.currency") <- "CHF"
mapping.table <- mappingTable(currency(name = "EURCHF",
from = "EUR",
to = "CHF"),
equity(name = "equityCHF",
type = "equity",
currency = "CHF"),
rate(name = "2YCHF",
currency = "CHF",
horizon = "k"),
spread(name = "AAACHF",
currency = "CHF",
rating = "AAA"),
rate(name = "2YCHF",
currency = "EUR",
horizon = "k",
scale = 0.8))
initial.values <- list()
initial.values$initial.fx <- data.frame(from = "EUR",
to = "CHF",
fx = 1.05,
stringsAsFactors = F)
initial.values$initial.rate <- data.frame(time = 1L,
currency = c("CHF", "EUR"),
rate = c(0.01, 0.01),
stringsAsFactors = F)
mapping.time <- data.frame(time = 1L, mapping = "k", stringsAsFactors = F)
## define an economic scenario
eco.table <- matrix(c(1,1,1,1,2,2,1,4,2,3), nrow=2)
colnames(eco.table) <- c(name, "participation")
rownames(eco.table) <- c("sc1","sc2")
eco.scenario <- macroEconomicScenarios(macro.economic.scenario.table = eco.table)
mr <- marketRisk(cov.mat = cov.mat,
mapping.table = mapping.table,
initial.values = initial.values,
mapping.time = mapping.time,
base.currency = "CHF")
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)
valid.param <- list(mvm = 3,
rtkr = 0,
rtkg = 0,
credit.risk = 3,
correction.term = 3,
expected.insurance.result = 10^6,
expected.financial.result = 10^5)
valid.param <- list(mvm = list(mvm.life = 2, mvm.health = 4, mvm.nonlife = 3),
rtkr = 0,
rtkg = 0,
credit.risk = 3,
correction.term = 3,
expected.insurance.result = 10^6,
expected.financial.result = 10^5)
p <- portfolio(market.items = list(asset(type = "equity", currency = "CHF", value = 1000),
liability(time = 1L, currency = "CHF", value = -400),
cashflow(time = 1L, currency = "CHF", rating = "AAA", 0.06, value = 500),
delta(name = "EURCHF", currency = "CHF", sensitivity = 30)),
participation.item = participation(currency = "CHF", value = 200),
life.item = life(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(10, 10)),
health.item = health(name = c("storno", "invalidity"), currency = c("CHF", "CHF"), sensitivity = c(10, 10)),
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)
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"),
scenario.risk = scenarioRisk("tornado", 0.08, "CHF", -10),
participation.risk = participationRisk(volatility = 3),
macro.economic.scenarios = eco.scenario,
nhmr = 0.06,
reordering.parameters = list(list.correlation.matrix = list.correlation.matrix,
region.boundaries = region.boundaries,
region.probability = region.probability,
scenario.probability = scenario.probability),
standalones = list(standalone(name = "equity", equity(name = "equityCHF",
type = "equity",
currency = "CHF")),
standalone(name = "something", spread(name = "AAACHF",
currency = "CHF",
rating = "AAA"),
rate(name = "2YCHF",
currency = "EUR",
horizon = "k",
scale = 0.8))))
expect_error(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"),
scenario.risk = scenarioRisk("tornado", 0.08, "CHF", -10),
participation.risk = participationRisk(volatility = 3),
macro.economic.scenarios = eco.scenario,
nhmr = 0.06,
reordering.parameters = list(list.correlation.matrix = list.correlation.matrix,
region.boundaries = region.boundaries,
region.probability = region.probability,
scenario.probability = scenario.probability),
standalones = list(standalone(name = "equity", equity(name = "equityCHF",
type = "equity",
currency = "CHF")),
standalone(name = "something", spread(name = "AAACHF",
currency = "CHF",
rating = "AAA"),
rate(name = "2YCHF",
currency = "EUR",
horizon = "l")))),
"standalones")
expect_error(sstModel(portfolio = p,
market.risk = mr,
life.risk = NULL,
health.risk = hr,
nonlife.risk = nonLifeRisk(type = "simulations",
param = list(simulations=c(1, 2, 3, 4)),
currency = "CHF"),
scenario.risk = scenarioRisk("tornado", 0.08, "EUR", -10),
participation.risk = participationRisk(volatility = 3),
macro.economic.scenarios = eco.scenario,
nhmr = 0.06,
reordering.parameters = list(list.correlation.matrix = list.correlation.matrix,
region.boundaries = region.boundaries,
region.probability = region.probability,
scenario.probability = scenario.probability),
standalones = list(standalone(name = "equity", equity(name = "equityCHF",
type = "equity",
currency = "CHF")),
standalone(name = "something", spread(name = "AAACHF",
currency = "CHF",
rating = "AAA"),
rate(name = "2YCHF",
currency = "EUR",
horizon = "k",
scale = 0.8)))),
"Missing")
expect_error(sstModel(portfolio = p,
market.risk = mr,
life.risk = lr,
health.risk = NULL,
nonlife.risk = NULL,
scenario.risk = scenarioRisk("tornado", 0.08, "EUR", -10),
participation.risk = participationRisk(volatility = 3),
macro.economic.scenarios = eco.scenario,
nhmr = 0.06,
reordering.parameters = list(list.correlation.matrix = list.correlation.matrix,
region.boundaries = region.boundaries,
region.probability = region.probability,
scenario.probability = scenario.probability),
standalones = list(standalone(name = "equity", equity(name = "equityCHF",
type = "equity",
currency = "CHF")),
standalone(name = "something", spread(name = "AAACHF",
currency = "CHF",
rating = "AAA"),
rate(name = "2YCHF",
currency = "EUR",
horizon = "k",
scale = 0.8)))),
"Missing")
})
Try the sstModel package in your browser
Any scripts or data that you put into this service are public.
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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