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Diffstat (limited to 'R/intex_deals_functions.R')
| -rw-r--r-- | R/intex_deals_functions.R | 253 |
1 files changed, 253 insertions, 0 deletions
diff --git a/R/intex_deals_functions.R b/R/intex_deals_functions.R new file mode 100644 index 00000000..a85b9f24 --- /dev/null +++ b/R/intex_deals_functions.R @@ -0,0 +1,253 @@ +library(RQuantLib)
+library(statmod)
+root = "//WDSENTINEL/share/CorpCDOs/"
+source(file.path(root, "R", "yieldCurve.R"))
+source(file.path(root, "R", "cds_functions_generic.R"))
+source(file.path(root, "R", "etdb.R"))
+source(file.path(root, "R", "tranche_functions.R"))
+load(file.path(root, "R", "bloomberg_data.RData"))
+
+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(dealnames){
+ sqlstring <- sprintf("select * from latest_clo_universe where dealname in ('%s')",
+ paste(dealnames, collapse="','"))
+ return( dbGetQuery(dbCon, sqlstring) )
+}
+
+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$price/100-0.2, 0)
+ }
+ return(recovery)
+}
+
+dealnamefromcusip <- function(cusips){
+ ## wrapper around the sql procedure, not the fastest probably
+ r <- NULL
+ for(i in 1:length(cusips)){
+ sqlstr <- sprintf("select * from dealname_from_cusip('%s')", cusips[i])
+ r <- c(r, as.character(dbGetQuery(dbCon, sqlstr)))
+ }
+ return( r )
+}
+
+cusipsfromdealnames <- function(dealnames){
+ unlist(strsplit(getdealdata(dealnames)$"Deal Cusip List", ","))
+}
+
+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)$minimum )
+}
+
+
+maturity <- function(creditcurve){
+ if(class(creditcurve)=="creditcurve"){
+ dates <- creditcurve@curve@dates
+ if(length(dates)){
+ return( dates[length(dates)] )
+ }else{
+ return( creditcurve@startdate )
+ }
+ }else{
+ stop("not of class creditcurve")
+ }
+}
+
+stackcurve <- function(SC, line.item, global.params, startdate){
+ newdates <- seq(startdate, line.item$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$defaultbondhazardrate
+ kvec <- rep(0, length(hvec))
+ }
+ SC@curve@hazardrates <- c(SC@curve@hazardrates, hvec)
+ SC@curve@prepayrates <- c(SC@curve@prepayrates, kvec)
+ SC@curve@dates <- c(SC@curve@dates, newdates[-1])
+ return(SC)
+}
+
+buildSC.matured <- function(SC, line.item, reinvdate, dealmaturity, global.params, startdate){
+ if(startdate<=reinvdate){ #reinvest
+ line.item$maturity <- min(dealmaturity, startdate + global.params$rollingmaturity)
+ SC <- stackcurve(SC, line.item, global.params, startdate)
+ }else{ #no reinvestment
+ SC@curve@dates <- startdate
+ SC@curve@hazardrates <- 0
+ SC@curveprepayrates <- 0
+ }
+ return( SC )
+}
+
+buildSC <- function(line.item, reinvdate, dealmaturity, global.params, startdate){
+ ## cat(line.item$issuername, "\n")
+ 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$defaultedflag){
+ if(!is.na(line.item$price)){
+ line.item$currentbalance <- line.item$currentbalance * line.item$price/100
+ }else{
+ line.item$currentbalance <- line.item$currentbalance * recovery(line.item)
+ }
+ SC@startdate <- startdate + global.params$defaultedlag
+ line.item$maturity <- min(dealmaturity, SC@startdate + global.params$rollingmaturity)
+ ## automatic reinvest
+ SC<- stackcurve(SC, line.item, global.params, SC@startdate)
+ }else if(line.item$maturity<=startdate){#matured asset
+ SC <- buildSC.matured(SC, line.item, reinvdate, dealmaturity, global.params, startdate)
+ }else if(is.na(line.item$price)){ #missing price
+ SC <- stackcurve(SC, line.item, global.params, SC@startdate)
+ }else{ #normal case
+ if(line.item$assettype=="Bond"){ #no prepay rate
+ alpha <- 0
+ }else{
+ alpha <- global.params$alpha
+ }
+ try <- bondhazardrate.shaped(line.item, global.params$shape,
+ recovery(line.item), alpha)
+ if(is.null(try)){
+ SC <- stackcurve(SC, line.item, global.params, SC@startdate)
+ }else{
+ SC@curve <- try
+ }
+ }
+ if(maturity(SC) <= reinvdate){ #we reinvest
+ newstartdate <- line.item$maturity
+ line.item$maturity <- min(dealmaturity, newstartdate + global.params$rollingmaturity)
+ SC <- stackcurve(SC, line.item, global.params, newstartdate)
+ }
+ return( list(SC=SC, notional=line.item$currentbalance) )
+}
+
+buildSC.portfolio <- function(dealname, global.params, startdate=today()) {
+ dealdata <- getdealdata(dealname)
+ collatdata <- getcollateral(dealname)
+ notionalvec <- c()
+ SCvec <- c()
+ betavec <- c()
+ for(i in 1:nrow(collatdata)){
+ line.item <- collatdata[i,]
+ if( is.na(line.item$maturity) ){
+ stop("empty maturity")
+ }
+ ##most likely equity, doesn't impact the risk anyway
+ if(line.item$currentbalance < 1){
+ next
+ }
+ temp <- buildSC(line.item, dealdata$"Reinv End Date", dealdata$maturity, global.params, startdate)
+ notionalvec <- c(notionalvec, temp$notional)
+ SCvec <- c(SCvec, temp$SC)
+ betavec <- c(betavec, if(!is.na(line.item$iscdo) && line.item$iscdo) 1 else
+ global.params$defaultcorr)
+ }
+ return( list(notional=notionalvec, SC=SCvec, beta=betavec) )
+}
+
+cdrfromscenarios <- function(scenarios, dates){
+ ## compute the forward cdr rates to pass to intex
+ ## so that we match the default curves in scenarios
+ cdr <- matrix(0, nrow(scenarios), ncol(scenarios))
+ for(i in 1:nrow(scenarios)){
+ cdr[i,] <- 100*(1-exp(diff(c(0, log(1-scenarios[i,])))))/diff(c(0, yearFrac(today(), dates)))
+ }
+ return( cdr )
+}
+
+recoveryfromscenarios <- function(scenariosd, scenariosr){
+ ## compute the forward recovery rate based on the term
+ ## structure of recovery scenarios
+ ## we run into trouble for very stressed scenarios
+ ## this code should cap the scenarios at 0 it this happens
+ intexrecov <- matrix(0, n.scenarios, ncol(scenariosr))
+ for(i in 1:n.scenarios){
+ current <- 1
+ intexrecov[i,1] <- scenariosr[i,1]
+ for(t in 2:ncol(scenariosr)){
+ w <- scenariosd[i,current]/scenariosd[i,t]
+ if(scenariosr[i,t]-w*scenariosr[i,current]>=0){
+ intexrecov[i,t] <- (scenariosr[i,t]-w*scenariosr[i,current])/(1-w)
+ current <- current+1
+ }else{
+ intexrecov[i,t] <- 0
+ }
+ }
+ }
+ return(intexrecov)
+}
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