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-rw-r--r--R/script_calibrate_tranches.R97
1 files changed, 30 insertions, 67 deletions
diff --git a/R/script_calibrate_tranches.R b/R/script_calibrate_tranches.R
index 14d346b1..12cb51f7 100644
--- a/R/script_calibrate_tranches.R
+++ b/R/script_calibrate_tranches.R
@@ -15,6 +15,7 @@ source(file.path(root.dir, "code", "R", "cds_utils.R"))
source(file.path(root.dir, "code", "R", "cds_functions_generic.R"))
source(file.path(root.dir, "code", "R", "yieldcurve.R"))
source(file.path(root.dir, "code", "R", "optimization.R"))
+source(file.path(root.dir, "code", "R", "calibration.R"))
load.index("hy21")
##figure out the tradedate
@@ -27,116 +28,79 @@ if(length(args) >= 1){
exportYC(tradedate)
## calibrate HY21
## calibrate the single names curves
-singlenames.data <- read.csv(file.path(root.dir, "Scenarios", "Calibration",
- paste0("hy21_singlenames_", tradedate, ".csv")))
-nondefaulted <- singlenames.data[!singlenames.data$ticker %in% hy21$defaulted,]
-bps <- 1e-4
-
-cdsdates <- as.Date(character(0))
-for(tenor in paste0(1:5, "y")){
- cdsdates <- c(cdsdates, cdsMaturity(tenor, date=tradedate))
-}
-
-hy21portfolio <- c()
-cs <- couponSchedule(IMMDate(tradedate), cdsdates[length(cdsdates)], "Q", "FIXED",
- 1, tradedate, IMMDate(tradedate, "prev"))
-for(i in 1:nrow(nondefaulted)){
- SC <- new("creditcurve",
- recovery=nondefaulted$recovery[i]/100,
- startdate=tradedate,
- issuer=as.character(nondefaulted$ticker[i]))
- quotes <- data.frame(maturity=cdsdates, upfront = as.numeric(nondefaulted[i,4:8]) /100,
- running=rep(nondefaulted$running[i] * bps, 5))
- SC@curve <- cdshazardrate(quotes, nondefaulted$recovery[i]/100, tradedate, cs)
- hy21portfolio <- c(hy21portfolio, SC)
-}
-
-issuerweights <- rep(1/length(hy21portfolio), length(hy21portfolio))
+set.singlenamesdata(hy21, tradedate)
+set.tranchedata(hy21, tradedate)
## load tranche data
-K <- c(0, 0.15, 0.25, 0.35, 1)
-Kmodified <- adjust.attachments(K, hy21$loss, hy21$factor)
-market.data <- read.csv(file.path(root.dir, "Scenarios", "Calibration",
- paste0("hy21_tranches_", tradedate, ".csv")))
-
-tranche.upf <- market.data$Mid
-tranche.running <- c(0.05, 0.05, 0.05, 0.05)
-# get the index ref
-hy21$indexref <- market.data$bidRefPrice[1]/100
-hy21portfolio.tweaked <- tweakcurves(hy21portfolio, hy21, tradedate)$portfolio
-cs <- couponSchedule(IMMDate(tradedate), hy21$maturity,"Q", "FIXED", 0.05, 0, tradedate, IMMDate(tradedate, "prev"))
-SurvProb <- SPmatrix(hy21portfolio.tweaked, length(cs$dates))
-
-Ngrid <- 2 * nrow(nondefaulted) + 1
-recov <- sapply(hy21portfolio.tweaked, attr, "recovery")
+n.credit <- length(hy21$portfolio)
+Ngrid <- 2 * n.credit + 1
acc <- cdsAccrued(tradedate, 0.05)
##calibrate by modifying the factor distribution
bottomup <- 1:3
topdown <- 2:4
n.int <- 500
-n.credit <- length(hy21portfolio)
+n.credit <- length(hy21$portfolio)
errvec <- c()
quadrature <- GHquad(n.int)
w <- quadrature$w
Z <- quadrature$Z
w.mod <- w
-defaultprob <- 1 - SurvProb
-p <- defaultprob
+p <- hy21$defaultprob
rho <- rep(0.45, n.credit)
-
result <- matrix(0, 4, n.int)
err <- Inf
while(err >0.01){
- Rstoch <- array(0, dim=c(n.credit, n.int, ncol(SurvProb)))
- for(t in 1:ncol(SurvProb)){
+ Rstoch <- array(0, dim=c(n.credit, n.int, ncol(hy21$defaultprob)))
+ for(t in 1:ncol(hy21$defaultprob)){
for(i in 1:n.credit){
- Rstoch[i,,t] <- stochasticrecovC(recov[i], 0, Z, w.mod, rho[i], defaultprob[i,t], p[i,t])
+ Rstoch[i,,t] <- stochasticrecovC(hy21$recov[i], 0, Z, w.mod, rho[i],
+ hy21$defaultprob[i,t], p[i,t])
}
}
- L <- array(0, dim=c(n.int, Ngrid, ncol(defaultprob)))
- R <- array(0, dim=c(n.int, Ngrid, ncol(defaultprob)))
- for(t in 1:ncol(defaultprob)){
+ L <- array(0, dim=c(n.int, Ngrid, ncol(hy21$defaultprob)))
+ R <- array(0, dim=c(n.int, Ngrid, ncol(hy21$defaultprob)))
+ for(t in 1:ncol(hy21$defaultprob)){
S <- 1 - Rstoch[,,t]
- L[,,t] <- t(lossdistCZ(p[,t], issuerweights, S, Ngrid, 0, rho, Z))
- R[,,t] <- t(lossdistCZ(p[,t], issuerweights, 1-S, Ngrid, 0, rho, Z))
+ L[,,t] <- t(lossdistCZ(p[,t], hy21$issuerweights, S, Ngrid, 0, rho, Z))
+ R[,,t] <- t(lossdistCZ(p[,t], hy21$issuerweights, 1-S, Ngrid, 0, rho, Z))
}
for(i in 1:n.int){
- result[,i] <- tranche.pvvec(Kmodified, L[i,,], R[i,,], cs) - acc
+ result[,i] <- tranche.pvvec(hy21$K, L[i,,], R[i,,], hy21$cs) - acc
}
## solve the optimization problem
- program <- KLfit(100*(result[bottomup,]+1), w, tranche.upf[bottomup])
+ program <- KLfit(100*(result[bottomup,]+1), w, hy21$tranche.upf[bottomup])
err <- 0
for(i in 1:n.credit){
for(j in 1:ncol(p)){
- err <- err + abs(crossprod(shockprob(p[i,j], rho[i], Z), program$weight) - defaultprob[i,j])
+ err <- err + abs(crossprod(shockprob(p[i,j], rho[i], Z), program$weight) - hy21$defaultprob[i,j])
}
}
errvec <- c(errvec, err)
## update the new probabilities
- p <- MFupdate.probC(Z, program$weight, rho, defaultprob)
+ p <- MFupdate.probC(Z, program$weight, rho, hy21$defaultprob)
errvec <- c(errvec, err)
w.mod <- program$weight
cat(err,"\n")
}
-Rstoch <- array(0, dim=c(n.credit, n.int, ncol(SurvProb)))
-for(t in 1:ncol(SurvProb)){
+Rstoch <- array(0, dim=c(n.credit, n.int, ncol(hy21$defaultprob)))
+for(t in 1:ncol(hy21$defaultprob)){
for(i in 1:n.credit){
- Rstoch[i,,t] <- stochasticrecovC(recov[i], 0, Z, w.mod, rho[i], defaultprob[i,t], p[i,t])
+ Rstoch[i,,t] <- stochasticrecovC(hy21$recov[i], 0, Z, w.mod, rho[i], hy21$defaultprob[i,t], p[i,t])
}
}
Lw <- matrix(0, Ngrid, n.int)
Rw <- matrix(0, Ngrid, n.int)
-L <- matrix(0, Ngrid, ncol(defaultprob))
-R <- matrix(0, Ngrid, ncol(defaultprob))
-for(t in 1:ncol(defaultprob)){
+L <- matrix(0, Ngrid, ncol(hy21$defaultprob))
+R <- matrix(0, Ngrid, ncol(hy21$defaultprob))
+for(t in 1:ncol(hy21$defaultprob)){
S <- 1 - Rstoch[,,t]
- Lw <- lossdistCZ(p[,t], issuerweights, S, Ngrid, 0, rho, Z)
- Rw <- lossdistCZ(p[,t], issuerweights, 1-S, Ngrid, 0, rho, Z)
+ Lw <- lossdistCZ(p[,t], hy21$issuerweights, S, Ngrid, 0, rho, Z)
+ Rw <- lossdistCZ(p[,t], hy21$issuerweights, 1-S, Ngrid, 0, rho, Z)
L[,t] <- Lw%*%w.mod
R[,t] <- Rw%*%w.mod
}
@@ -148,6 +112,5 @@ write.table(data.frame(Z=Z, w=w.mod),
paste0("calibration-", tradedate, ".csv")),
col.names=T, row.names=F, sep=",")
-save(singlenames.data, hy21, tranche.upf, dist,
- file = file.path(root.dir, "Scenarios", "Calibration",
- paste0("marketdata-", tradedate, ".RData")), compress="xz")
+save(hy21, dist, file = file.path(root.dir, "Scenarios", "Calibration",
+ paste0("marketdata-", tradedate, ".RData")), compress="xz")
generated by cgit v1.2.3-70-g09d2 (git 2.52.0) at 2026-01-17 00:09:05 +0000