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source("cds_functions_generic.R")
buildSC <- function(quote, cs, cdsdates){
SC <- new("creditcurve",
recovery=quote$recovery,
startdate=tradedate,
issuer=quote$ticker)
quotes <- data.frame(maturity=cdsdates, upfront = quote$upfront,
running=quote$running)
SC@curve <- cdshazardrate(quotes, SC@recovery, tradedate, cs)
return( SC )
}
get.cdsSchedule <- function(tradedate, indexmaturity){
cdsdates <- as.Date(character(0))
for(tenor in paste0(c(1:5, 7,10), "y")){
newdate <- cdsMaturity(tenor, date=tradedate)
cdsdates <- c(cdsdates, newdate)
if(newdate>=indexmaturity){
break
}
}
return( list(cs=couponSchedule(IMMDate(tradedate, noadj=TRUE), cdsdates[length(cdsdates)], "Q", "FIXED",
1, tradedate, IMMDate(tradedate, "prev")), cdsdates=cdsdates) )
}
set.singlenamesdata <- function(index, tradedate){
cds.cs <- get.cdsSchedule(tradedate, index$maturity)
quotes <- get.indexquotes(index$name, tradedate)
tenor <- names(cds.cs$cdsdates)
index$portfolio <- list()
for(i in seq_along(quotes$tickers)){
if(quotes$ticker[i] %in% c("IACI", "TITANC")){
quotes$spread_curve[i,] <- rep(0.001,8)
quotes$upfront_curve[i,] <- rep(0,8)
quotes$recovery[i,] <- rep(0.4,8)
}
quotes$upfront_curve[i, tenor] <- pmax(-yearFrac(tradedate+2,cds.cs$cdsdates)*
quotes$spread_curve[i, tenor]*1e-2,
quotes$upfront_curve[i, tenor])
quote <- list(ticker = quotes$ticker[i],
running = quotes$spread_curve[i, tenor] * 1e-4,
upfront = quotes$upfront_curve[i, tenor] * 0.01,
recovery = as.double(quotes$recovery[i,tenor][1]))
index$portfolio <- c(index$portfolio, buildSC(quote, cds.cs$cs, cds.cs$cdsdates))
}
index$issuerweights <- rep(1/length(index$portfolio), length(index$portfolio))
index$recov <- sapply(index$portfolio, attr, "recovery")
return( index )
}
set.tranchedata <- function(index, tradedate){
temp <- get.tranchequotes(index$name, index$tenor, tradedate)
index$quotes <- data.frame(maturity=index$maturity,
refspread=temp$indexrefspread[1],
refprice=temp$indexrefprice[1])
if(index$name=="ig19" || index$name=="ig21"){
index$quotes$spread <- 0.01
}else{
index$quotes$spread <- index$quotes$refspread*1e-4
}
index$cs <- couponSchedule(IMMDate(tradedate, noadj=TRUE), index$maturity,"Q", "FIXED", 1,
0, tradedate, IMMDate(tradedate, "prev"))
if(!is.na(index$quotes$refprice) && index$quotes$refprice != 0){
index$quotes$price <- index$quotes$refprice/100
}else{
##rewrite as a snac function
sc <- new("flatcurve", h=index$quotes$refspread[1]*1e-4/(1-index$recovery))
startdate <- tradedate + 1
cds.pv <- couponleg(index$cs, sc, startdate)*index$quotes$spread -
defaultleg(index$cs, sc, index$recovery, startdate)
index$quotes$price <- 1 + cds.pv - cdsAccrued(tradedate, index$quotes$spread[1])
}
tweak <- tweakcurves(index, tradedate)
index$portfolio <- NULL
index <- c(index, tweak)
index$defaultprob <- 1 - SPmatrix(index$portfolio, length(index$cs$dates))
negprob <- which(index$defaultprob<0, arr.ind=T)
if(nrow(negprob) > 0){
stop(paste(index$portfolio[[negprob[1,1]]]@issuer, "has negative probability, check single names data"))
}
K <- c(0, temp$detach/100)
index$K.orig <- K
index$K <- adjust.attachments(K, index$loss, index$factor)
## compute dirty protection price
accrued <- cdsAccrued(tradedate, temp$trancherunningmid*1e-4)
if(length(grep("hy", index$name, ignore.case=TRUE))>0){
dirtyquotes <- 1 - temp$trancheupfrontmid/100 - accrued
}else{
dirtyquotes <- temp$trancheupfrontmid/100 - accrued
}
index$tranches <- data.frame(upfront=temp$trancheupfrontmid,
running=temp$trancherunningmid * 1e-4,
quotes=dirtyquotes,
mkt.delta=temp$tranchedelta,
row.names=paste(index$K.orig[-length(index$K.orig)]*100,
index$K.orig[-1]*100, sep="-"))
return( index )
}
build.skew <- function(index, type="bottomup"){
require(lossdistrib)
aux <- function(rho, index, K, quote, spread, complement){
temp <- BCtranche.legs(index, K, rho, complement)
return(abs(temp$pl+temp$cl*spread + quote))
}
rhovec <- rep(NA, length(index$K))
dK <- diff(index$K)
if(type=="bottomup"){
for(j in 1:(length(dK)-1)){
##use the current tranche coupon
## we compute the 0-index$K[j+1] equivalent quote using the coupon of the jth quote
tranchepv <- BCtranche.legs(index, index$K[j], rhovec[j])
q <- index$tranches$quotes[j] * dK[j] -
tranchepv$pl - tranchepv$cl*index$tranches$running[j]
rho <- optimize(aux, interval=c(0,1), index=index, K=index$K[j+1], quote=q,
spread=index$tranches$running[j], complement=FALSE)$minimum
rhovec[j+1] <- rho
}
}else if(type=="topdown"){
for(j in length(dK):2){
tranchepv <- BCtranche.legs(index, index$K[j+1], rhovec[j+1], complement=TRUE)
q <- index$tranche.quotes[j] * dK[j] -
tranchepv$pl - tranchepv$cl * index$tranches$running[j]
rho <- optimize(aux, interval=c(0,1), index=index, K=index$K[j], quote=q,
spread=index$tranches$running[j], complement=TRUE)$minimum
rhovec[j] <- rho
}
}
return( rhovec )
}
build.MFdist <- function(index, type="bottomup", tol=1e-2){
index$w.mod <- index$w
p <- index$defaultprob
n.credit <- length(index$issuerweights)
rho <- rep(0.45, n.credit)
result <- matrix(0, 4, n.int)
n.tranches <- length(index$K)-1
err <- Inf
if(type=="bottomup"){
select <- 1:(n.tranches-1)
}else if(type=="topdown"){
select <- 2:n.tranches
}
while(err > tol){
Rstoch <- MFrecovery(index, p)
L <- array(0, dim=c(index$N, n.int, ncol(index$defaultprob)))
R <- array(0, dim=c(index$N, n.int, ncol(index$defaultprob)))
for(t in 1:ncol(index$defaultprob)){
S <- 1 - Rstoch[,,t]
L[,,t] <- lossdistCZ(p[,t], index$issuerweights, S, index$N, 0, rho, index$Z)
R[,,t] <- lossdistCZ(p[,t], index$issuerweights, 1-S, index$N, 0, rho, index$Z)
}
for(i in 1:n.int){
dist <- list(L=L[,i,], R=R[,i,])
result[,i] <- MFtranche.pv(index, dist, protection=TRUE)$bp
}
## solve the optimization problem
program <- KLfit(result[select,], index$w, index$tranches$quotes[select])
err <- 0
for(i in 1:n.credit){
for(j in 1:ncol(p)){
err <- err + abs(crossprod(shockprob(p[i,j], rho[i],
index$Z), program$weight) - index$defaultprob[i,j])
}
}
## update the new probabilities
p <- MFupdate.probC(index$Z, program$weight, rho, index$defaultprob)
index$w.mod <- program$weight
cat("=")
}
cat("\n")
return(index$w.mod)
}
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