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| -rw-r--r-- | R/tranche_mapping.R | 108 |
1 files changed, 108 insertions, 0 deletions
diff --git a/R/tranche_mapping.R b/R/tranche_mapping.R new file mode 100644 index 00000000..b1e059d2 --- /dev/null +++ b/R/tranche_mapping.R @@ -0,0 +1,108 @@ +if(.Platform$OS.type == "unix"){ + root.dir <- "/home/share/CorpCDOs" +}else{ + root.dir <- "//WDSENTINEL/share/CorpCDOs" +} +options(stringsAsFactors=FALSE) +source(file.path(root.dir, "code", "R", "cds_utils.R")) +source(file.path(root.dir, "code", "R", "cds_functions_generic.R")) +source(file.path(root.dir, "code", "R", "yieldcurve.R")) +source(file.path(root.dir, "code", "R", "optimization.R")) +library(lossdistrib) +load.index("hy21") +load.index("hy19") +n.int <- 250 +bps <- 1e-4 +attach(GHquad(n.int)) + +tradedate <- as.Date("2014-05-05") +exportYC(tradedate) +cdsdates <- as.Date(character(0)) +for(tenor in paste0(1:5, "y")){ + cdsdates <- c(cdsdates, cdsMaturity(tenor, date=tradedate)) +} +cds.cs <- couponSchedule(IMMDate(tradedate), cdsdates[length(cdsdates)], "Q", "FIXED", + 1, tradedate, IMMDate(tradedate, "prev")) + + +##build portfolio +buildSC <- function(quote, cs){ + SC <- new("creditcurve", + recovery=quote$recovery/100, + startdate=tradedate, + issuer=as.character(quote$ticker)) + quotes <- data.frame(maturity=cdsdates, upfront = as.numeric(quote[4:8]) * 0.01, + running=rep(quote$running*1e-4, 5)) + SC@curve <- cdshazardrate(quotes, SC@recovery, tradedate, cs) + return( SC ) +} + +set.singlenamesdata <- function(index, tradedate){ + index.name <- deparse(substitute(index)) + singlenames.data <- read.csv(file.path(root.dir, "Scenarios", "Calibration", + paste0(index.name, "_singlenames_", tradedate, ".csv"))) + nondefaulted <- singlenames.data[!singlenames.data$ticker %in% index$defaulted,] + index$portfolio <- c() + for(i in 1:nrow(nondefaulted)){ + index$portfolio <- c(index$portfolio, buildSC(nondefaulted[i,], cds.cs)) + } + index$issuerweights <- rep(1/length(index$portfolio), length(index$portfolio)) + index$recov <- sapply(index$portfolio, attr, "recovery") + assign(index.name, index, envir=parent.env(environment())) +} + +## load all the single names data +## calibrate the single names curves +set.singlenamesdata(hy21, tradedate) +set.singlenamesdata(hy19, tradedate) + +## load tranche data +set.tranchedata <- function(index, tradedate){ + index.name <- deparse(substitute(index)) + index$tranche.data <- read.csv(file.path(root.dir, "Scenarios", "Calibration", + paste0(index.name, "_tranches_", tradedate, ".csv")), header=TRUE) + index$indexref <- index$tranche.data$bidRefPrice[1]/100 + index$portfolio.tweaked <- tweakcurves(index$portfolio, index, tradedate)$portfolio + index$cs <- couponSchedule(IMMDate(tradedate), index$maturity,"Q", "FIXED", 0.05, 0, tradedate, + IMMDate(tradedate, "prev")) + index$defaultprob <- 1-SPmatrix(index$portfolio.tweaked, length(index$cs$dates)) + K <- c(0, 0.15, 0.25, 0.35, 1) + index$K <- adjust.attachments(K, index$loss, index$factor) + index$tranche.upf <- index$tranche.data$Mid + index$tranche.running <- index$tranche.data$Coupon + ##convert the quotes + ## - we convert to protection terms x->1-x/100 + ## - we remove accrued x->x-acc + ## - we weight it by the size of the tranche + ## - we take the cumsum to convert to 0-5, 0-10, 0-15 quotes, etc... + ## calibrate the tranches using base correlation + index$quotes <- cumsum(diff(index$K) * + (1-index$tranche.upf/100-cdsAccrued(tradedate, index$tranche.running))) + assign(index.name, index, envir=parent.env(environment())) +} + +set.tranchedata(hy19, tradedate) +set.tranchedata(hy21, tradedate) + +## load common parameters +Ngrid <- 201 +f <- function(rho, index, N, i){ + temp <- with(index, + BClossdistC(defaultprob, issuerweights, recov, rho, Z, w, N)) + return(abs(tranche.pv(temp$L, temp$R, index$cs, 0, index$K[i+1]) + index$quotes[i])) +} + +rhovec <- c() +for(i in 1:3){ + rho <- optimize(f, interval=c(0,1), index=hy21, N=Ngrid, i=i)$minimum + rhovec <- c(rhovec, rho) +} + +rhovec <- c(0, rhovec) +K <- c(0, 0.15, 0.25, 0.35, 1) +rhofun <- approxfun(K[-5], rhovec, rule=2) + +Kmapped <- rep(0, 3) +for(i in 2:4){ + Kmapped[i-1] <- skewmapping(hy21, rhofun, hy19, K[i], Z, w, 201)$minimum +} |