Nothing
tests/testthat/test-CurveCalibration.R
In QuantBondCurves: Calculates Bond Values and Interest Rate Curves for Finance
# 13. Curve Calibration Spot --------------------------------------------------
test_that("output has to have always the same length as nodes input vector", {
yield.curve <- c(0.04,0.06,0.07,0.08,0.09,0.10, 0.11,0.12,0.125)
nodes <- c(0.117,0.15,0.25,0.35,2,3,6,8)
expect_length(curve.calibration(market.assets = market.assets.input2(),
yield.curve = yield.curve,
asset.type = "TES",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
rate.type = 1,
fwd = 0,
freq = 1,
approximation = "constant") , length(nodes))
})
test_that("output has to have always the same length as nodes input vector", {
yield.curve <- c(0.04,0.06,0.07,0.08,0.09,0.10, 0.11,0.12,0.125)
nodes <- c(0.117)
expect_length(curve.calibration(market.assets = market.assets.input2(),
yield.curve = yield.curve,
asset.type = "TES",
analysis.date = "2019-01-03" ,
nodes = nodes,
fwd = 0,
daycount = "ACT/365",
rate.type = 1,
freq = 1,
approximation = "linear"), length(nodes))
})
test_that("if node date is after last maturty of bonds, then it is assumed that the rate associated
is the same as last final node", {
yield.curve <- c(0.04,0.06,0.07,0.08,0.09,0.10, 0.11,0.12,0.125)
nodes <- c(0.1,1,2,3,10,100)
expect_equal(as.numeric(curve.calibration(market.assets = market.assets.input2(),
yield.curve = yield.curve,
asset.type = "LIBORSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
rate.type = 1,
freq = 4,
fwd = 0,
approximation = "linear")[5]),
as.numeric(curve.calibration(market.assets = market.assets.input2(),
yield.curve = yield.curve,
asset.type = "LIBORSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
rate.type = 1,
freq = 4,
approximation = "linear")[6]))
})
test_that("constant option throws a constant curve", {
yield.curve <- c(0.04,0.06,0.07,0.08,0.09,0.10, 0.11,0.12,0.125)
nodes <- seq(0.255, 0.5, by = 0.025)
expect_setequal(curve.calibration(market.assets = market.assets.input2(),
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
rate.type = 1,
freq = 4,
approximation = "constant"
), rep(yield.curve[1],length(nodes)))
})
test_that("linear option throws a linear curve", {
yield.curve <- c(0.04,0.06,0.07,0.08,0.09,0.10, 0.11,0.12,0.125)
nodes <- seq(7.25, 8, by = 0.25)
market.assets <- market.assets.input2()
for (i in seq_along(nodes)) {
expect_gte(curve.calibration(market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2015-01-03" ,
nodes = nodes,
daycount = "ACT/365",
rate.type = 0,
freq = 4,
approximation = "linear"
)[i], yield.curve[3])
}
})
test_that("linear option throws a linear curve", {
yield.curve <- c(0.04,0.06,0.07,0.08,0.09,0.10, 0.11,0.12,0.125)
nodes <- seq(7.25, 8, by = 0.25)
market.assets <- market.assets.input2()
for (i in seq_along(nodes)) {
expect_lte(curve.calibration(market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2015-01-03" ,
nodes = nodes,
daycount = "ACT/365",
rate.type = 0,
freq = 4,
approximation = "linear"
)[i], yield.curve[4])
}
})
test_that("continously compounded rates have a shorter output rate than anually compounded", {
yield.curve <- c(0.04,0.06,0.07,0.08,0.09,0.10, 0.11,0.12,0.125)
nodes <- c(0.117,0.15,0.25,0.35,2,3,6,8)
market.assets <- market.assets.input2()
for (i in 1:length(nodes)) {
expect_lte(curve.calibration(market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2018-01-03" ,
nodes = nodes,
daycount = "ACT/365",
rate.type = 0,
freq = 4,
approximation = "constant")[i],
curve.calibration(market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2018-01-03" ,
nodes = nodes,
daycount = "ACT/365",
rate.type = 1,
freq = 4,
approximation = "constant")[i])
}
})
test_that("asset.type isnt that relevant for methodology of calibration, can be determined with
the other parameters", {
yield.curve <- c(0.103,0.1044,0.1083,0.101,0.112,0.113,0.115,0.116,0.115,0.13)
names(yield.curve) <- c("1","2","3","4","5","6","7","8","9","10")
nodes <- c(0.117,0.15,0.25,0.35,2,3,6,8)
for (i in 1:length(nodes)) {
expect_lte(curve.calibration(market.assets = NULL,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2018-01-03" ,
nodes = nodes,
daycount = "ACT/365",
rate.type = 0,
freq = 4,
approximation = "linear")[i],
curve.calibration(market.assets = NULL,
yield.curve = yield.curve,
asset.type = "FixedIncome",
analysis.date = "2018-01-03" ,
nodes = nodes,
daycount = "ACT/365",
rate.type = 0,
freq = 4,
noSpots = 4,
approximation = "linear")[i])
}
})
test_that("freq can be a vector, for bonds", {
yield.curve <- c(0.04,0.06,0.07,0.08,0.09,0.10, 0.11,0.12,0.125)
nodes <- c(0.117,0.15,0.25,0.35,2,3,6,8)
expect_length(curve.calibration(market.assets = market.assets.input2(),
yield.curve = yield.curve,
asset.type = "FixedIncome",
analysis.date = "2019-01-03",
nodes = nodes,
daycount = "ACT/365",
noSpots = 1,
rate.type = 1,
fwd = 0,
freq = c(1,2,4,2,1,1,2,4),
approximation = "constant"), length(nodes))
})
# 13 b. Curve Calibration Fwd -----------------------------------------------
test_that("output has to have always the same length as nodes input vector", {
yield.curve <- c(0.103,0.1044,0.1083,0.101,0.112,0.113,0.115,0.116,0.115,0.13)
names(yield.curve) <- c("1","2","3","4","5","6","7","8","9","10")
nodes <- seq(0,10, by = 0.001)
expect_length(curve.calibration(market.assets = market.assets.input3(),
yield.curve = yield.curve,
asset.type = "TES",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
freq = 1,
fwd = 1,
approximation = "linear"), length(nodes))
})
test_that("output has to have always the same length as nodes input vector", {
yield.curve <- c(0.103,0.1044,0.1083,0.101,0.112,0.113,0.115,0.116,0.115,0.13)
names(yield.curve) <- c("1","2","3","4","5","6","7","8","9","10")
nodes <- c(0.117)
expect_length(curve.calibration (market.assets = market.assets.input3(),
yield.curve = yield.curve,
asset.type = "TES",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
freq = 4,
fwd = 1), length(nodes))
})
test_that("if node date is after last maturty of bonds, then it is assumed that the rate associated
is the same as last final node", {
nodes <- c(0.1,1,2,5,7,8,10,100)
yield.curve <- cbind(0.02,0.023,0.025,0.03,0.035,0.036,0.039,0.42,0.04)
colnames(yield.curve) <- cbind("0","0.08","0.25","0.5","5","6","7","8","9")
market.assets <- market.assets.input()[-10,]
expect_equal(as.numeric(curve.calibration (market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "LIBORSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
fwd = 1,
freq = 4)[7]),
as.numeric(curve.calibration(market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "LIBORSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
freq = 4,
fwd = 1)[8]))
})
#Piecewise linear spot vs forward
test_that("plot of curves is correct", {
skip("Test is for plotting curves")
skip_on_cran()
yield.curve <- c(0.103,0.1034,0.1092, 0.1161, 0.1233, 0.1280, 0.1310, 0.1320, 0.1325, 0.1320)
names(yield.curve) <- c(0,0.08,0.25,0.5,1,2,3,5,7,10)
for (i in 1:9) {
if (i %in% c(1:4) ) {
xf <- curve.calibration (market.assets = NULL,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
fwd = 1,
freq = 4,
approximation = "linear",
npieces = i,
nsimul = nsimul,
rate.type = 0,
obj = "Rates")
y <- as.numeric(names(xf))
plot(y,xf,type = "p", col = "purple", xlab = "Tasa", ylab = "t", ylim = c(0,0.20))
legend("bottomright", legend = c("Forward"), col = c("purple"),lty=1:1,cex = 0.8)
} else {
x <- curve.calibration (market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
fwd = 0,
freq = 4,
approximation = "linear",
npieces = i - 4,
nsimul = nsimul,
rate.type = 0,
obj = "Rates")
y <- as.numeric(names(x))
xf <- curve.calibration (market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
fwd = 1,
freq = 4,
approximation = "linear",
npieces = i,
nsimul = nsimul,
rate.type = 0,
obj = "Rates")
plot(y,x,type = "p", col = "blue", xlab = "t", ylab = "Tasa", ylim = c(0,0.20))
points(y,xf, col = "purple")
legend("bottomright", legend = c("Spot","Forward"), col = c("blue","purple"),lty=1:2,cex = 0.8)
}
}
#Bootstrapping Method
xf <- curve.calibration (market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03",
nodes = nodes,
daycount = "ACT/365",
fwd = 1,
freq = 4,
approximation = "linear",
npieces = NULL,
rate.type = 0,
obj = "Price")
y <- as.numeric(names(xf))
x <- curve.calibration (market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
fwd = 0,
freq = 4,
approximation = "linear",
npieces = NULL,
rate.type = 0,
obj = "Rates")
plot(y,x,type = "p", col = "blue", xlab = "t", ylab = "Tasa", ylim = c(0,0.20))
points(y,xf, col = "purple")
legend("topleft", legend = c("Spot","Forward"), col = c("blue","purple"),lty=1:2,cex = 0.8)
})
#Piecewise constant spot vs forward
test_that("plot of constant curves is correct", {
skip("Test is for plotting curves")
skip_on_cran()
for (i in 1:9) {
if (i %in% c(1:4) ) {
xf <- curve.calibration (market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
fwd = 1,
freq = 4,
approximation = "constant",
npieces = i,
nsimul = nsimul,
rate.type = 0,
obj = "Rates")
y <- as.numeric(names(xf))
plot(y,xf,type = "p", col = "purple", xlab = "Tasa", ylab = "t",ylim = c(0,0.20))
legend("bottomright", legend = c("Forward"), col = c("purple"),lty=1:1,cex = 0.8)
} else {
x <- curve.calibration (market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
fwd = 0,
freq = 4,
approximation = "constant",
npieces = i - 4,
nsimul = nsimul,
rate.type = 0,
obj = "Rates")
y <- as.numeric(names(x))
xf <- curve.calibration (market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
fwd = 1,
freq = 4,
approximation = "constant",
npieces = i,
nsimul = nsimul,
rate.type = 0,
obj = "Rates")
plot(y,x,type = "p", col = "blue", xlab = "t", ylab = "Tasa", ylim = c(0,0.20))
points(y,xf, col = "purple")
legend("bottomright", legend = c("Spot","Forward"), col = c("blue","purple"),lty=1:2,cex = 0.8)
}
}
#Bootstrapping Method
xf <- curve.calibration (market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
fwd = 1,
freq = 4,
approximation = "constant",
npieces = NULL,
rate.type = 0,
obj = "Rates")
y <- as.numeric(names(xf))
x <- curve.calibration (market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
fwd = 0,
freq = 4,
approximation = "constant",
npieces = NULL,
rate.type = 0,
obj = "Rates")
plot(y,x,type = "p", col = "blue", xlab = "t", ylab = "Tasa", ylim = c(0,0.15))
points(y,xf, col = "purple")
legend("bottomright", legend = c("Spot","Forward"), col = c("blue","purple"),lty=1:2,cex = 0.8)
})
# 14. Curve Calculation ---------------------------------------------------
test_that("historical rates that begin before the previous curve, must be eliminated", {
previous.curve <- matrix(0.04,nrow = 2,ncol = 28)
rownames(previous.curve) <- c("2014-01-01","2015-01-01")
colnames(previous.curve) <- c(0, 0.25, 0.5, 1:25)
expect_equal(as.numeric(curve.calculation(previous.curve = previous.curve,
market.assets = market.assets.input4(),
serie = serie.input(),
asset.type = "TES",
rate.type = 1,
freq = 1,
fwd = 0,
daycount = NULL,
approximation = "linear",
nodes = c(0, 0.25, 0.5, 1:25))[1,]), rep(0.04,28) )
})
test_that("historical rates that begin before the previous curve, must be eliminated", {
previous.curve <- matrix(0.04,nrow = 2,ncol = 28)
rownames(previous.curve) <- c("2014-01-01","2015-01-01")
colnames(previous.curve) <- c(0, 0.25, 0.5, 1:25)
expect_equal(as.numeric(curve.calculation(previous.curve = previous.curve,
market.assets = market.assets.input4(),
serie = serie.input(),
asset.type = "TES",
noSpots = 1,
rate.type = 1,
freq = 1,
fwd = 0,
daycount = NULL,
approximation = "linear",
nodes = c(0, 0.25, 0.5, 1:25))[2,]), rep(0.04,28) )
})
test_that("historical rates that begin before the previous curve, must be eliminated,
when constructing an instantaneous forward curve", {
previous.curve <- matrix(0.04,nrow = 2,ncol = 28)
rownames(previous.curve) <- c("2014-01-01","2015-01-01")
colnames(previous.curve) <- c(0, 0.25, 0.5, 1:25)
expect_equal(as.numeric(curve.calculation(previous.curve = previous.curve,
market.assets = market.assets.input4(),
serie = serie.input(),
asset.type = "IBRSwaps",
noSpots = 4,
rate.type = 0,
freq = 4,
fwd = 1,
daycount = NULL,
approximation = "constant",
nodes = c(0, 0.25, 0.5, 1:25))[1,]), rep(0.04,28) )
})
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# 13. Curve Calibration Spot --------------------------------------------------
test_that("output has to have always the same length as nodes input vector", {
yield.curve <- c(0.04,0.06,0.07,0.08,0.09,0.10, 0.11,0.12,0.125)
nodes <- c(0.117,0.15,0.25,0.35,2,3,6,8)
expect_length(curve.calibration(market.assets = market.assets.input2(),
yield.curve = yield.curve,
asset.type = "TES",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
rate.type = 1,
fwd = 0,
freq = 1,
approximation = "constant") , length(nodes))
})
test_that("output has to have always the same length as nodes input vector", {
yield.curve <- c(0.04,0.06,0.07,0.08,0.09,0.10, 0.11,0.12,0.125)
nodes <- c(0.117)
expect_length(curve.calibration(market.assets = market.assets.input2(),
yield.curve = yield.curve,
asset.type = "TES",
analysis.date = "2019-01-03" ,
nodes = nodes,
fwd = 0,
daycount = "ACT/365",
rate.type = 1,
freq = 1,
approximation = "linear"), length(nodes))
})
test_that("if node date is after last maturty of bonds, then it is assumed that the rate associated
is the same as last final node", {
yield.curve <- c(0.04,0.06,0.07,0.08,0.09,0.10, 0.11,0.12,0.125)
nodes <- c(0.1,1,2,3,10,100)
expect_equal(as.numeric(curve.calibration(market.assets = market.assets.input2(),
yield.curve = yield.curve,
asset.type = "LIBORSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
rate.type = 1,
freq = 4,
fwd = 0,
approximation = "linear")[5]),
as.numeric(curve.calibration(market.assets = market.assets.input2(),
yield.curve = yield.curve,
asset.type = "LIBORSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
rate.type = 1,
freq = 4,
approximation = "linear")[6]))
})
test_that("constant option throws a constant curve", {
yield.curve <- c(0.04,0.06,0.07,0.08,0.09,0.10, 0.11,0.12,0.125)
nodes <- seq(0.255, 0.5, by = 0.025)
expect_setequal(curve.calibration(market.assets = market.assets.input2(),
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
rate.type = 1,
freq = 4,
approximation = "constant"
), rep(yield.curve[1],length(nodes)))
})
test_that("linear option throws a linear curve", {
yield.curve <- c(0.04,0.06,0.07,0.08,0.09,0.10, 0.11,0.12,0.125)
nodes <- seq(7.25, 8, by = 0.25)
market.assets <- market.assets.input2()
for (i in seq_along(nodes)) {
expect_gte(curve.calibration(market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2015-01-03" ,
nodes = nodes,
daycount = "ACT/365",
rate.type = 0,
freq = 4,
approximation = "linear"
)[i], yield.curve[3])
}
})
test_that("linear option throws a linear curve", {
yield.curve <- c(0.04,0.06,0.07,0.08,0.09,0.10, 0.11,0.12,0.125)
nodes <- seq(7.25, 8, by = 0.25)
market.assets <- market.assets.input2()
for (i in seq_along(nodes)) {
expect_lte(curve.calibration(market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2015-01-03" ,
nodes = nodes,
daycount = "ACT/365",
rate.type = 0,
freq = 4,
approximation = "linear"
)[i], yield.curve[4])
}
})
test_that("continously compounded rates have a shorter output rate than anually compounded", {
yield.curve <- c(0.04,0.06,0.07,0.08,0.09,0.10, 0.11,0.12,0.125)
nodes <- c(0.117,0.15,0.25,0.35,2,3,6,8)
market.assets <- market.assets.input2()
for (i in 1:length(nodes)) {
expect_lte(curve.calibration(market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2018-01-03" ,
nodes = nodes,
daycount = "ACT/365",
rate.type = 0,
freq = 4,
approximation = "constant")[i],
curve.calibration(market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2018-01-03" ,
nodes = nodes,
daycount = "ACT/365",
rate.type = 1,
freq = 4,
approximation = "constant")[i])
}
})
test_that("asset.type isnt that relevant for methodology of calibration, can be determined with
the other parameters", {
yield.curve <- c(0.103,0.1044,0.1083,0.101,0.112,0.113,0.115,0.116,0.115,0.13)
names(yield.curve) <- c("1","2","3","4","5","6","7","8","9","10")
nodes <- c(0.117,0.15,0.25,0.35,2,3,6,8)
for (i in 1:length(nodes)) {
expect_lte(curve.calibration(market.assets = NULL,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2018-01-03" ,
nodes = nodes,
daycount = "ACT/365",
rate.type = 0,
freq = 4,
approximation = "linear")[i],
curve.calibration(market.assets = NULL,
yield.curve = yield.curve,
asset.type = "FixedIncome",
analysis.date = "2018-01-03" ,
nodes = nodes,
daycount = "ACT/365",
rate.type = 0,
freq = 4,
noSpots = 4,
approximation = "linear")[i])
}
})
test_that("freq can be a vector, for bonds", {
yield.curve <- c(0.04,0.06,0.07,0.08,0.09,0.10, 0.11,0.12,0.125)
nodes <- c(0.117,0.15,0.25,0.35,2,3,6,8)
expect_length(curve.calibration(market.assets = market.assets.input2(),
yield.curve = yield.curve,
asset.type = "FixedIncome",
analysis.date = "2019-01-03",
nodes = nodes,
daycount = "ACT/365",
noSpots = 1,
rate.type = 1,
fwd = 0,
freq = c(1,2,4,2,1,1,2,4),
approximation = "constant"), length(nodes))
})
# 13 b. Curve Calibration Fwd -----------------------------------------------
test_that("output has to have always the same length as nodes input vector", {
yield.curve <- c(0.103,0.1044,0.1083,0.101,0.112,0.113,0.115,0.116,0.115,0.13)
names(yield.curve) <- c("1","2","3","4","5","6","7","8","9","10")
nodes <- seq(0,10, by = 0.001)
expect_length(curve.calibration(market.assets = market.assets.input3(),
yield.curve = yield.curve,
asset.type = "TES",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
freq = 1,
fwd = 1,
approximation = "linear"), length(nodes))
})
test_that("output has to have always the same length as nodes input vector", {
yield.curve <- c(0.103,0.1044,0.1083,0.101,0.112,0.113,0.115,0.116,0.115,0.13)
names(yield.curve) <- c("1","2","3","4","5","6","7","8","9","10")
nodes <- c(0.117)
expect_length(curve.calibration (market.assets = market.assets.input3(),
yield.curve = yield.curve,
asset.type = "TES",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
freq = 4,
fwd = 1), length(nodes))
})
test_that("if node date is after last maturty of bonds, then it is assumed that the rate associated
is the same as last final node", {
nodes <- c(0.1,1,2,5,7,8,10,100)
yield.curve <- cbind(0.02,0.023,0.025,0.03,0.035,0.036,0.039,0.42,0.04)
colnames(yield.curve) <- cbind("0","0.08","0.25","0.5","5","6","7","8","9")
market.assets <- market.assets.input()[-10,]
expect_equal(as.numeric(curve.calibration (market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "LIBORSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
fwd = 1,
freq = 4)[7]),
as.numeric(curve.calibration(market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "LIBORSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
freq = 4,
fwd = 1)[8]))
})
#Piecewise linear spot vs forward
test_that("plot of curves is correct", {
skip("Test is for plotting curves")
skip_on_cran()
yield.curve <- c(0.103,0.1034,0.1092, 0.1161, 0.1233, 0.1280, 0.1310, 0.1320, 0.1325, 0.1320)
names(yield.curve) <- c(0,0.08,0.25,0.5,1,2,3,5,7,10)
for (i in 1:9) {
if (i %in% c(1:4) ) {
xf <- curve.calibration (market.assets = NULL,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
fwd = 1,
freq = 4,
approximation = "linear",
npieces = i,
nsimul = nsimul,
rate.type = 0,
obj = "Rates")
y <- as.numeric(names(xf))
plot(y,xf,type = "p", col = "purple", xlab = "Tasa", ylab = "t", ylim = c(0,0.20))
legend("bottomright", legend = c("Forward"), col = c("purple"),lty=1:1,cex = 0.8)
} else {
x <- curve.calibration (market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
fwd = 0,
freq = 4,
approximation = "linear",
npieces = i - 4,
nsimul = nsimul,
rate.type = 0,
obj = "Rates")
y <- as.numeric(names(x))
xf <- curve.calibration (market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
fwd = 1,
freq = 4,
approximation = "linear",
npieces = i,
nsimul = nsimul,
rate.type = 0,
obj = "Rates")
plot(y,x,type = "p", col = "blue", xlab = "t", ylab = "Tasa", ylim = c(0,0.20))
points(y,xf, col = "purple")
legend("bottomright", legend = c("Spot","Forward"), col = c("blue","purple"),lty=1:2,cex = 0.8)
}
}
#Bootstrapping Method
xf <- curve.calibration (market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03",
nodes = nodes,
daycount = "ACT/365",
fwd = 1,
freq = 4,
approximation = "linear",
npieces = NULL,
rate.type = 0,
obj = "Price")
y <- as.numeric(names(xf))
x <- curve.calibration (market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
fwd = 0,
freq = 4,
approximation = "linear",
npieces = NULL,
rate.type = 0,
obj = "Rates")
plot(y,x,type = "p", col = "blue", xlab = "t", ylab = "Tasa", ylim = c(0,0.20))
points(y,xf, col = "purple")
legend("topleft", legend = c("Spot","Forward"), col = c("blue","purple"),lty=1:2,cex = 0.8)
})
#Piecewise constant spot vs forward
test_that("plot of constant curves is correct", {
skip("Test is for plotting curves")
skip_on_cran()
for (i in 1:9) {
if (i %in% c(1:4) ) {
xf <- curve.calibration (market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
fwd = 1,
freq = 4,
approximation = "constant",
npieces = i,
nsimul = nsimul,
rate.type = 0,
obj = "Rates")
y <- as.numeric(names(xf))
plot(y,xf,type = "p", col = "purple", xlab = "Tasa", ylab = "t",ylim = c(0,0.20))
legend("bottomright", legend = c("Forward"), col = c("purple"),lty=1:1,cex = 0.8)
} else {
x <- curve.calibration (market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
fwd = 0,
freq = 4,
approximation = "constant",
npieces = i - 4,
nsimul = nsimul,
rate.type = 0,
obj = "Rates")
y <- as.numeric(names(x))
xf <- curve.calibration (market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
fwd = 1,
freq = 4,
approximation = "constant",
npieces = i,
nsimul = nsimul,
rate.type = 0,
obj = "Rates")
plot(y,x,type = "p", col = "blue", xlab = "t", ylab = "Tasa", ylim = c(0,0.20))
points(y,xf, col = "purple")
legend("bottomright", legend = c("Spot","Forward"), col = c("blue","purple"),lty=1:2,cex = 0.8)
}
}
#Bootstrapping Method
xf <- curve.calibration (market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
fwd = 1,
freq = 4,
approximation = "constant",
npieces = NULL,
rate.type = 0,
obj = "Rates")
y <- as.numeric(names(xf))
x <- curve.calibration (market.assets = market.assets,
yield.curve = yield.curve,
asset.type = "IBRSwaps",
analysis.date = "2019-01-03" ,
nodes = nodes,
daycount = "ACT/365",
fwd = 0,
freq = 4,
approximation = "constant",
npieces = NULL,
rate.type = 0,
obj = "Rates")
plot(y,x,type = "p", col = "blue", xlab = "t", ylab = "Tasa", ylim = c(0,0.15))
points(y,xf, col = "purple")
legend("bottomright", legend = c("Spot","Forward"), col = c("blue","purple"),lty=1:2,cex = 0.8)
})
# 14. Curve Calculation ---------------------------------------------------
test_that("historical rates that begin before the previous curve, must be eliminated", {
previous.curve <- matrix(0.04,nrow = 2,ncol = 28)
rownames(previous.curve) <- c("2014-01-01","2015-01-01")
colnames(previous.curve) <- c(0, 0.25, 0.5, 1:25)
expect_equal(as.numeric(curve.calculation(previous.curve = previous.curve,
market.assets = market.assets.input4(),
serie = serie.input(),
asset.type = "TES",
rate.type = 1,
freq = 1,
fwd = 0,
daycount = NULL,
approximation = "linear",
nodes = c(0, 0.25, 0.5, 1:25))[1,]), rep(0.04,28) )
})
test_that("historical rates that begin before the previous curve, must be eliminated", {
previous.curve <- matrix(0.04,nrow = 2,ncol = 28)
rownames(previous.curve) <- c("2014-01-01","2015-01-01")
colnames(previous.curve) <- c(0, 0.25, 0.5, 1:25)
expect_equal(as.numeric(curve.calculation(previous.curve = previous.curve,
market.assets = market.assets.input4(),
serie = serie.input(),
asset.type = "TES",
noSpots = 1,
rate.type = 1,
freq = 1,
fwd = 0,
daycount = NULL,
approximation = "linear",
nodes = c(0, 0.25, 0.5, 1:25))[2,]), rep(0.04,28) )
})
test_that("historical rates that begin before the previous curve, must be eliminated,
when constructing an instantaneous forward curve", {
previous.curve <- matrix(0.04,nrow = 2,ncol = 28)
rownames(previous.curve) <- c("2014-01-01","2015-01-01")
colnames(previous.curve) <- c(0, 0.25, 0.5, 1:25)
expect_equal(as.numeric(curve.calculation(previous.curve = previous.curve,
market.assets = market.assets.input4(),
serie = serie.input(),
asset.type = "IBRSwaps",
noSpots = 4,
rate.type = 0,
freq = 4,
fwd = 1,
daycount = NULL,
approximation = "constant",
nodes = c(0, 0.25, 0.5, 1:25))[1,]), rep(0.04,28) )
})
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