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| -rw-r--r-- | R/tranche_mapping.R | 108 |
1 files changed, 0 insertions, 108 deletions
diff --git a/R/tranche_mapping.R b/R/tranche_mapping.R deleted file mode 100644 index b1e059d2..00000000 --- a/R/tranche_mapping.R +++ /dev/null @@ -1,108 +0,0 @@ -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 -} |