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Diffstat (limited to 'build_SC.R')
| -rw-r--r-- | build_SC.R | 399 |
1 files changed, 399 insertions, 0 deletions
diff --git a/build_SC.R b/build_SC.R new file mode 100644 index 00000000..f7e2ba75 --- /dev/null +++ b/build_SC.R @@ -0,0 +1,399 @@ +library(RQuantLib)
+library(statmod)
+root = "//WDSENTINEL/share/CorpCDOs/R"
+setwd(root)
+source(file.path(root, "yieldCurve.R"))
+source(file.path(root, "cds_functions_generic.R"))
+source(file.path(root, "etdb.R"))
+load(file.path(root, "bloomberg_data.RData"))
+MarkitData <- getMarkitIRData()
+L1m <- buildMarkitYC(MarkitData, dt = 1/12)
+L2m <- buildMarkitYC(MarkitData, dt = 1/6)
+L3m <- buildMarkitYC(MarkitData)
+L6m <- buildMarkitYC(MarkitData, dt = 1/2)
+setEvaluationDate(as.Date(MarkitData$effectiveasof))
+
+
+bps <- 1e-4
+global.params <- list()
+global.params$recovery.assumptions <- list("Loan"=0.7,
+ "SecondLien"=0.3,
+ "Bond"=0.3,
+ "Mezzanine"=0.15,
+ "Adj_Covlite"=0.1)
+
+global.params$cdoprices <- list("Aaa"=90,
+ "Aa"=80,
+ "A"=70,
+ "Baa"=60,
+ "Ba"=50,
+ "B"=40,
+ "NR"=40)
+#reinvest in 7 years assets
+global.params$rollingmaturity <- 7 * 365
+global.params$defaultedlag <- 90
+global.params$defaultcorr <- 0.4
+global.params$defaultbondhazardrate <- 500 * bps
+global.params$defaultloanhazardrate <- 400 * bps
+global.params$alpha <- 0.25
+global.params$beta <- 15
+global.params$shape <- function(T)0.25+(1-exp(-T/5))
+
+cdorating <- function(cusip){
+ return( sub("[0-9]","", dataMtge[dataMtge$CUSIP %in% cusip,]$RTG_MDY_INITIAL ))
+}
+
+getcollateral <- function(dealname, date=Sys.Date()){
+ sqlstring <- sprintf("select * from et_aggdealinfo_historical('%s', '%s')", dealname, date)
+ collatdata <- dbGetQuery(dbCon, sqlstring)
+ return(collatdata)
+}
+
+getdealdata <- function(dealname, date=Sys.Date()){
+ sqlstring <- sprintf("select * from clo_universe where dealname='%s' order by \"Latest Update\"", dealname)
+ return( dbGetQuery(dbCon, sqlstring)[1,] )
+}
+
+recovery <- function(collateral) {
+ ## return assumed recovery based on assumptions from recovery.assumptions
+ if(!is.na(collateral$secondlien) && collateral$secondlien){
+ collateral$assettype <- "SecondLien"
+ }
+ recovery <- with(global.params,
+ as.numeric(recovery.assumptions[collateral$assettype]))
+ if( !is.na(collateral$covlite) && collateral$covlite) {
+ recovery <- recovery - global.params$recovery.assumptions$Adj_Covlite
+ }
+ if( !is.na(collateral$iscdo) && collateral$iscdo ){
+ recovery <- 0
+ }
+ ## price is too low need to lower the assumed recovery
+ if(!is.na(collateral$price) && recovery > collateral$price/100 - 0.1){
+ recovery <- max(collateral$price/100-0.2, 0)
+ }
+ return(recovery)
+}
+
+dealnamefromcusip <- function(cusips){
+ ## wrapper around the sql procedure, not the fastest probably
+ r <- NULL
+ for(i in 1:length(cusips)){
+ sqlstr <- sprintf("select * from dealname_from_cusip('%s')", cusips[i])
+ r <- c(r, as.character(dbGetQuery(dbCon, sqlstr)))
+ }
+ return( r )
+}
+
+fithazardrate.fast <- function(collateral, eps=1e-6){
+ lambda <- 0.05
+ cs <- couponSchedule(collateral$nextpaydate, collateral$maturity,
+ collateral$frequency, collateral$fixedorfloat,
+ collateral$grosscoupon * 0.01, collateral$spread*0.01)
+ R <- recovery(collateral)
+ while(abs(bondprice(lambda, cs, R) * 100 - collateral$price) > eps){
+ lambda <- lambda - (bondprice(lambda, cs, R) - 0.01*collateral$price)/dbondprice(lambda, cs, R)
+ }
+ return( lambda )
+}
+
+vanillabondprice <- function(h, collateral, prepay=TRUE) {
+ R <- recovery(collateral)
+ cs <- couponSchedule(collateral$nextpaydate, collateral$maturity,
+ collateral$frequency, collateral$fixedorfloat,
+ collateral$grosscoupon*0.01, collateral$spread*0.01)
+ if(prepay){
+ dpc <- new("defaultprepaycurve", dates=cs$dates, hazardrates=rep(h,length(cs$dates)),
+ prepayrates=rep(k(h), length(cs$dates)))
+ }else{
+ dpc <- new("defaultprepaycurve", dates=cs$dates, hazardrates=rep(h,length(cs$dates)),
+ prepayrates=numeric(0))
+ }
+ return( bondprice(cs, dpc, R) )
+}
+
+dvanillabondprice <- function(hazardrate, collateral) {
+ R <- recovery(collateral)
+ cs <- couponSchedule(collateral$nextpaydate, collateral$maturity,
+ collateral$frequency, collateral$fixedorfloat,
+ collateral$grosscoupon*0.01, collateral$spread*0.01)
+ return( bondprice(hazardrate, cs, R) )
+}
+
+fithazardrate <- function(collateral){
+ R <- recovery(collateral)
+ cs <- couponSchedule(collateral$nextpaydate, collateral$maturity,
+ collateral$frequency, collateral$fixedorfloat,
+ collateral$grosscoupon*0.01, collateral$spread*0.01)
+ f <- function(lambda){
+ u <- bondprice(lambda, cs, R )
+ return( (u * 100-collateral$price)^2 )
+ }
+ return( optimize(f, c(0,1), tol=1e-6)$minimum )
+}
+
+
+maturity <- function(creditcurve){
+ if(class(creditcurve)=="creditcurve"){
+ dates <- creditcurve@curve@dates
+ if(length(dates)){
+ return( dates[length(dates)] )
+ }else{
+ return( creditcurve@startdate )
+ }
+ }else{
+ stop("not of class creditcurve")
+ }
+}
+
+stackcurve <- function(SC, line.item, startdate, global.params){
+ newdates <- seq(startdate, line.item$maturity, by="3 months")
+ if(line.item$assettype=="Loan"){
+ hvec <- global.params$shape(yearFrac(today(), newdates[-1])) * global.params$defaultloanhazardrate
+ kvec <- global.params$alpha * exp(-global.params$beta * hvec)
+ }else if(line.item$assettype=="Bond" || line.item$iscdo){
+ hvec <- global.params$shape(yearFrac(today(), newdates[-1])) * global.params$defaultbondhazardrate
+ kvec <- rep(0, length(hvec))
+ }
+ SC@curve@hazardrates <- c(SC@curve@hazardrates, hvec)
+ SC@curve@prepayrates <- c(SC@curve@prepayrates, kvec)
+ SC@curve@dates <- c(SC@curve@dates, newdates[-1])
+ return(SC)
+}
+
+buildSC <- function(line.item, global.params, startdate=today()){
+ ## cat(i, "\n")
+ line.item <- collatdata[i,]
+ ## cat(line.item$issuername, "\n")
+ if( is.na(line.item$maturity) ){
+ stop("empty maturity")
+ }
+ ##most likely equity, doesn't impact the risk anyway
+ if(line.item$currentbalance < 1){
+ next
+ }
+ if(!is.na(line.item$iscdo) && line.item$iscdo && is.na(line.item$price)){
+ ##we have prices for some cdos e.g. 210795PS3
+ orig.moody <- cdorating(line.item$cusip)
+ if(length(orig.moody)==0){
+ orig.moody <- "NR"
+ }
+ line.item$price <- as.numeric(global.params$cdoprices[orig.moody])
+ }
+ ##build survival curve
+ SC <- new("creditcurve", recovery=recovery(line.item), startdate=startdate,
+ issuer=line.item$issuername)
+ SC@curve <- new("defaultprepaycurve", dates=as.Date(character(0)))
+ ## defaulted asset
+ if(!is.na(line.item$defaultedflag) && line.item$defaultedflag){
+ line.item$currentbalance <- line.item$currentbalance * line.item$price/100
+ SC@startdate <- startdate + global.params$defaultedlag
+ line.item$maturity <- min(dealdata$maturity, SC@startdate + global.params$rollingmaturity)
+ ## automatic reinvest
+ SC<- stackcurve(SC, line.item, SC@startdate, global.params)
+ }else if( is.na(line.item$price) ){ #missing price
+ if(line.item$maturity <= startdate){
+ if(startdate<=dealdata$"Reinv End Date"){ #reinvest
+ line.item$maturity <- min(dealdata$maturity, startdate + global.params$rollingmaturity)
+ SC <- stackcurve(SC, line.item, SC@startdate, global.params)
+ }else{ #no reinvestment
+ SC@dates <- startdate
+ SC@hazardrates <- 0
+ SC@prepayrates <- 0
+ }
+ SC <- stackcurve(SC, line.item, SC@startdate, global.params)
+ }else{
+ SC <- stackcurve(SC, line.item, SC@startdate, global.params)
+ }
+ }else{
+ ## normal case
+ if(line.item$maturity > startdate){
+ if(line.item$assettype=="Bond"){ #no prepay rate
+ alpha <- 0
+ }else{
+ alpha <- global.params$alpha
+ }
+ try <- bondhazardrate.shaped(line.item, global.params$shape,
+ recovery(line.item), alpha)
+ if(!is.null(try)){
+ SC@curve <- try
+ }
+ }
+ }
+ ## if(length(maturity(SC))==0){
+ ## browser()
+ ## }
+ if(maturity(SC) <= dealdata$"Reinv End Date"){ #we reinvest
+ newstartdate <- line.item$maturity
+ line.item$maturity <- min(dealdata$maturity, newstartdate + global.params$rollingmaturity)
+ SC <- stackcurve(SC, line.item, newstartdate, global.params)
+ }
+}
+
+buildSC.portfolio <- function(dealname, global.params, startdate=today()) {
+ dealdata <- getdealdata(dealname)
+ collatdata <- getcollateral(dealname)
+ notionalvec <- c()
+ SCvec <- c()
+ betavec <- c()
+ for(i in 1:nrow(collatdata)){
+ ## cat(i, "\n")
+ line.item <- collatdata[i,]
+ ## cat(line.item$issuername, "\n")
+ if( is.na(line.item$maturity) ){
+ stop("empty maturity")
+ }
+ #most likely equity, doesn't impact the risk anyway
+ if(line.item$currentbalance < 1){
+ next
+ }
+ if(!is.na(line.item$iscdo) && line.item$iscdo && is.na(line.item$price)){
+ #we have prices for some cdos e.g. 210795PS3
+ orig.moody <- cdorating(line.item$cusip)
+ if(length(orig.moody)==0){
+ orig.moody <- "NR"
+ }
+ line.item$price <- as.numeric(global.params$cdoprices[orig.moody])
+ }
+ #build survival curve
+ SC <- new("creditcurve", recovery=recovery(line.item), startdate=startdate,
+ issuer=line.item$issuername)
+ SC@curve <- new("defaultprepaycurve", dates=as.Date(character(0)))
+ ##expired asset
+ ## if(i ==185){
+ ## browser()
+ ## }
+ ## defaulted asset
+ if(!is.na(line.item$defaultedflag) && line.item$defaultedflag){
+ line.item$currentbalance <- line.item$currentbalance * line.item$price/100
+ SC@startdate <- startdate + global.params$defaultedlag
+ line.item$maturity <- min(dealdata$maturity, SC@startdate + global.params$rollingmaturity)
+ ## automatic reinvest
+ SC<- stackcurve(SC, line.item, SC@startdate, global.params)
+ }else if( is.na(line.item$price) ){ #missing price
+ if(line.item$maturity <= startdate){
+ if(startdate<=dealdata$"Reinv End Date"){ #reinvest
+ line.item$maturity <- min(dealdata$maturity, startdate + global.params$rollingmaturity)
+ SC <- stackcurve(SC, line.item, SC@startdate, global.params)
+ }else{ #no reinvestment
+ SC@dates <- startdate
+ SC@hazardrates <- 0
+ SC@prepayrates <- 0
+ }
+ SC <- stackcurve(SC, line.item, SC@startdate, global.params)
+ }else{
+ SC <- stackcurve(SC, line.item, SC@startdate, global.params)
+ }
+ }else{
+ ## normal case
+ if(line.item$maturity > startdate){
+ if(line.item$assettype=="Bond"){ #no prepay rate
+ alpha <- 0
+ }else{
+ alpha <- global.params$alpha
+ }
+ try <- bondhazardrate.shaped(line.item, global.params$shape,
+ recovery(line.item), alpha)
+ if(!is.null(try)){
+ SC@curve <- try
+ }
+ }
+ }
+ ## if(length(maturity(SC))==0){
+ ## browser()
+ ## }
+ if(maturity(SC) <= dealdata$"Reinv End Date"){ #we reinvest
+ newstartdate <- line.item$maturity
+ line.item$maturity <- min(dealdata$maturity, newstartdate + global.params$rollingmaturity)
+ SC <- stackcurve(SC, line.item, newstartdate, global.params)
+ }
+
+ notionalvec <- c(notionalvec, line.item$currentbalance)
+ SCvec <- c(SCvec, SC)
+ betavec <- c(betavec, if(!is.na(line.item$iscdo) && line.item$iscdo) 1 else
+ global.params$defaultcorr)
+ }
+ return( list(notional=notionalvec, SC=SCvec, beta=betavec) )
+}
+
+## duration <- function(creditcurve){
+## # computes the duration for a hazard rate curve
+## T <- yearFrac(creditcurve@startdate, creditcurve@curve@dates)
+## r <- DiscountCurve(L3m$params, L3m$tsQuotes, T)$forwards
+## h <- creditcurve@curve@hazardrates
+## if(class(creditcurve)=="creditcurve"){
+## T.ext <- c(0, T)
+## s <- (exp(- (h + r) * T.ext[-1]) - exp(- (h + r)* T.ext[-length(T.ext)]))/(h+r)
+## }else{
+## stop("not of class credit curve")
+## }
+## return( - sum(s) )
+## }
+
+
+## dealnames <- c("babs072", "symph4", "flags5", "cent11", "wasatl", "oceant2", "acacl071", "limes")
+
+## for(dealname in dealnames){
+## cat(dealname,"\n")
+## collatdata <- dbGetQuery(dbCon,
+## paste("select * from et_aggdealinfo_historical(", dealname, ",",
+## Sys.Date(),")",
+## sep="'"))
+## dealdata <- dbGetQuery(dbCon,
+## paste("select maturity, \"Reinv End Date\" from clo_universe where dealname='", dealname, "'",sep=""))
+## portfolio <- buildSC.portfolio(today(), collatdata, dealdata)
+## }
+
+## dealname <- "symph4"
+## maturity18 <- as.Date("2017-06-20")
+## probs <- as.numeric(lapply(portfolio$SC, survivalProbability2, maturity18))
+## weights <- portfolio$notional/sum(portfolio$notional)
+## S <- weights * (1-as.numeric(lapply(portfolio$SC, attr, "recovery")))
+## L.ind <- lossdistrib3(1-probs, S, 0.01)
+## EL <- crossprod(seq(0,1,0.01), L.ind)
+
+## library(statmod)
+## n.int <- 500
+## Z <- gauss.quad.prob(n.int, "normal")$nodes
+## w <- gauss.quad.prob(n.int, "normal")$weights
+## rho <- 0.35
+
+## g <- 1 - probs
+## R <- as.numeric(lapply(portfolio$SC, attr, "recovery"))
+## r <- matrix(0, 101, 11)
+## rho <- seq(0,1,0.1)
+## rho[11] <- 0.999
+## for(j in 1:11){
+## Lrho <- matrix(0,101,500)
+## for(i in 1:length(Z)){
+## g.shocked <- shockprob(g, rho[j], Z[i])
+## R.shocked <- stochasticrecov.simple(R, 0, Z[i], rho[j], g)
+## Lrho[,i] <- lossdistrib3(g.shocked, (1-R.shocked) * weights, 0.01)
+## }
+## r[,j] <- Lrho%*%w
+## }
+
+## R.shocked <- matrix(0,267,n.int)
+## for(i in 1:length(Z)){
+## R.shocked [,i] <- stochasticrecov.simple(R, 0, Z[i], rho[j], g)
+## }
+
+
+dpc <- new("defaultprepaycurve", dates=cs$dates, hazardrates=rep(0.05,length(cs$dates)),
+ prepayrates=rep(0.01, length(cs$dates)))
+
+dc <- new("defaultcurve", dates=cs$dates, hazardrates=rep(0.05,length(cs$dates)))
+
+octagon8.collateral <- getcollateral("octagon8")
+octagon8.dealdata <- getdealdata("octagon8")
+pomme <- buildSC.portfolio(today(), octagon8.collateral, octagon8.dealdata)
+
+collateral <- octagon8.collateral[1,]
+cs <- couponSchedule(collateral$nextpaydate, collateral$maturity,
+ collateral$frequency, collateral$fixedorfloat,
+ collateral$grosscoupon*0.01, collateral$spread*0.01)
+
+k <- function(h, gamma = 15){
+ 0.25*exp(-gamma * h)
+}
+
+test <- buildSC.portfolio("stonln1", global.params)
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