diff options
| -rw-r--r-- | R/build_scenarios.R | 355 |
1 files changed, 183 insertions, 172 deletions
diff --git a/R/build_scenarios.R b/R/build_scenarios.R index 14a6ee25..5cdcbc6b 100644 --- a/R/build_scenarios.R +++ b/R/build_scenarios.R @@ -13,24 +13,24 @@ if(length(args) >= 1){ }
if(length(args) >=2){
- dealnames <- args[2:length(args)]
+ dealnames <- args[2:length(args)]
}else{
- data <- read.table(file.path(root.dir, "scripts", "scenarios.txt"))
- dealnames <- data$V1
- reinvflags <- data$V2
- unlink(file.path(root.dir, "scripts", "scenarios.txt"))
+ data <- read.table(file.path(root.dir, "scripts", "scenarios.txt"))
+ dealnames <- data$V1
+ reinvflags <- data$V2
+ unlink(file.path(root.dir, "scripts", "scenarios.txt"))
}
source(file.path(root.dir, "code", "R", "intex_deal_functions.R"))
source(file.path(root.dir, "code", "R", "index_definitions.R"))
prevBusDay <- function(workdate = Sys.Date()){
- i <- 1
- while(!isBusinessDay(calendar = "UnitedStates/GovernmentBond",
- workdate - i)){
- i <- i+1
- }
- return( workdate - i )
+ i <- 1
+ while(!isBusinessDay(calendar = "UnitedStates/GovernmentBond",
+ workdate - i)){
+ i <- i+1
+ }
+ return( workdate - i )
}
get.reinvassets <- function(dealname){
@@ -63,43 +63,43 @@ convert.reinvtoperct <- function(d){ compute.reinvprices <- function(df, forwards, cdrmonthly, recoverymonthly,
spread, fixedrate, rollingmat, reinvlag){
- ## reinvlag is in months
- ## rollingmat is in months
- floatbp <- c()
- fixedbp <- c()
- for(i in 0:(ncol(cdrmonthly)-1)){
- index <- (i+1):min(i+rollingmat, ncol(cdrmonthly))
- indexlagged <- index + reinvlag
- if(i==0){
- currdf <- df[index]
- laggeddf <- df[indexlagged]
- }else{
- currdf <- df[index]/df[i]
- laggeddf <- df[indexlagged]/df[i]
- }
- floatcoupon <- (forwards[index]+ spread)/12
- fixedcoupon <- fixedrate/12
- currbalance <- 1 - cdrmonthly[,index]/100/12
+ ## reinvlag is in months
+ ## rollingmat is in months
+ floatbp <- c()
+ fixedbp <- c()
+ for(i in 0:(ncol(cdrmonthly)-1)){
+ index <- (i+1):min(i+rollingmat, ncol(cdrmonthly))
+ indexlagged <- index + reinvlag
+ if(i==0){
+ currdf <- df[index]
+ laggeddf <- df[indexlagged]
+ }else{
+ currdf <- df[index]/df[i]
+ laggeddf <- df[indexlagged]/df[i]
+ }
+ floatcoupon <- (forwards[index]+ spread)/12
+ fixedcoupon <- fixedrate/12
+ currbalance <- 1 - cdrmonthly[,index]/100/12
- if(i < ncol(cdrmonthly)-1){
- currbalance <- t(apply(currbalance, 1, cumprod))
- recov <- -t(apply(cbind(1, currbalance), 1, diff)) *
- recoverymonthly[,index]
- fixedcl <- cbind(1,currbalance[,-length(index)])%*%(fixedcoupon*currdf)
- floatcl <- cbind(1,currbalance[,-length(index)])%*%(floatcoupon*currdf)
- pl <- currbalance[,dim(currbalance)[2]]*currdf[length(currdf)] +
- recov %*% laggeddf
- }else{
- recov <- -t(apply(cbind(1, currbalance), 1, diff)) *
- recoverymonthly[,index]
- fixedcl <- as.numeric(currbalance*fixedcoupon*currdf)
- floatcl <- as.numeric(currbalance*floatcoupon*currdf)
- pl <- as.numeric(currbalance * currdf + recov * laggeddf)
- }
- floatbp <- cbind(floatbp, pl+floatcl)
- fixedbp <- cbind(fixedbp, pl+fixedcl)
+ if(i < ncol(cdrmonthly)-1){
+ currbalance <- t(apply(currbalance, 1, cumprod))
+ recov <- -t(apply(cbind(1, currbalance), 1, diff)) *
+ recoverymonthly[,index]
+ fixedcl <- cbind(1,currbalance[,-length(index)])%*%(fixedcoupon*currdf)
+ floatcl <- cbind(1,currbalance[,-length(index)])%*%(floatcoupon*currdf)
+ pl <- currbalance[,dim(currbalance)[2]]*currdf[length(currdf)] +
+ recov %*% laggeddf
+ }else{
+ recov <- -t(apply(cbind(1, currbalance), 1, diff)) *
+ recoverymonthly[,index]
+ fixedcl <- as.numeric(currbalance*fixedcoupon*currdf)
+ floatcl <- as.numeric(currbalance*floatcoupon*currdf)
+ pl <- as.numeric(currbalance * currdf + recov * laggeddf)
}
- return( list(loan=floatbp, bond=fixedbp) )
+ floatbp <- cbind(floatbp, pl+floatcl)
+ fixedbp <- cbind(fixedbp, pl+fixedcl)
+ }
+ return( list(loan=floatbp, bond=fixedbp) )
}
calibration.date <- prevBusDay(workdate)
@@ -123,148 +123,159 @@ recoverylag <- 90 ##days ## need to match parameters in build_portfolios.R
reinvspread <- 0.025
reinvfixed <- 0.07
-rollingmaturity <- 84 ##months
+basecase.rollingmaturity <- 84 ##months
reinvlag <- 3 ##months
n.scenarios <- 100
recov.adj <- 0.925
for(j in seq_along(dealnames)){
- load(file.path(root.dir, "Scenarios", paste("Portfolios", workdate, sep="_"),
- paste(dealnames[j], "RData", sep=".")))
- if(is.na(deal.data$"Reinv End Date")){
- reinvflags[j] <- FALSE
- }
- dp <- A$DP
- pp <- A$PP
- dpmod <- MFupdate.probC(Z, w, deal.portfolio$beta, dp)
- ppmod <- MFupdate.probC(-Z, w, deal.portfolio$beta, pp)
- dist.joint <- MFlossdist.prepay.joint(w, Z, deal.portfolio$beta, dp, dpmod, pp, ppmod,
- deal.weights, 1-S, Ngrid)
+ load(file.path(root.dir, "Scenarios", paste("Portfolios", workdate, sep="_"),
+ paste(dealnames[j], "RData", sep=".")))
+ if(is.na(deal.data$"Reinv End Date")){
+ reinvflags[j] <- FALSE
+ }
+ dp <- A$DP
+ pp <- A$PP
+ dpmod <- MFupdate.probC(Z, w, deal.portfolio$beta, dp)
+ ppmod <- MFupdate.probC(-Z, w, deal.portfolio$beta, pp)
+ dist.joint <- MFlossdist.prepay.joint(w, Z, deal.portfolio$beta, dp, dpmod, pp, ppmod,
+ deal.weights, 1-S, Ngrid)
- distDR <- dist.transform(dist.joint)
- ## compute E(R|D)
- R <- matrix(0, Ngrid, dim(distDR)[1])
- for(t in 1:dim(distDR)[1]){
- R[,t] <- sweep(distDR[t,,], 1, rowSums(distDR[t,,]), "/") %*% support
- R[1,t] <- 0
- if(t >= 2){
- R[,t] <- pmax(R[,t], R[,t-1])
- }
+ distDR <- dist.transform(dist.joint)
+ ## compute E(R|D)
+ R <- matrix(0, Ngrid, dim(distDR)[1])
+ for(t in 1:dim(distDR)[1]){
+ R[,t] <- sweep(distDR[t,,], 1, rowSums(distDR[t,,]), "/") %*% support
+ R[1,t] <- 0
+ if(t >= 2){
+ R[,t] <- pmax(R[,t], R[,t-1])
}
+ }
- ## compute scenariosd
- scenariosd <- matrix(0, n.scenarios, dim(distDR)[1])
- scenariosr <- matrix(0, n.scenarios, dim(distDR)[1])
- percentiles <- seq(0, 1, 1/n.scenarios)
- for(t in 1:dim(distDR)[1]){
- D <- rowSums(distDR[t,,])
- Dfun <- splinefun(c(0, cumsum(D)), c(0, support), "monoH.FC")
- Rfun <- approxfun(support, R[,t], rule=2)
- for(i in 1:n.scenarios){
- ## this is roughtly E(D|D is in ith percentile)
- ## using trapezoidal approximation
- scenariosd[i,t] <- 0.5 * (Dfun((i-1)*0.01)+Dfun(i*0.01))
- if(t>=2 && scenariosd[i,t] < scenariosd[i,t-1]){
- scenariosd[i,t] <- scenariosd[i,t-1]
- }
- scenariosr[i,t] <- Rfun(scenariosd[i,t])
- if(t>=2 && scenariosr[i,t] < scenariosr[i,t-1]){
- scenariosr[i,t] <- scenariosr[i,t-1]
- }
- }
+ ## compute scenariosd
+ scenariosd <- matrix(0, n.scenarios, dim(distDR)[1])
+ scenariosr <- matrix(0, n.scenarios, dim(distDR)[1])
+ percentiles <- seq(0, 1, 1/n.scenarios)
+ for(t in 1:dim(distDR)[1]){
+ D <- rowSums(distDR[t,,])
+ Dfun <- splinefun(c(0, cumsum(D)), c(0, support), "monoH.FC")
+ Rfun <- approxfun(support, R[,t], rule=2)
+ for(i in 1:n.scenarios){
+ ## this is roughtly E(D|D is in ith percentile)
+ ## using trapezoidal approximation
+ scenariosd[i,t] <- 0.5 * (Dfun((i-1)*0.01)+Dfun(i*0.01))
+ if(t>=2 && scenariosd[i,t] < scenariosd[i,t-1]){
+ scenariosd[i,t] <- scenariosd[i,t-1]
+ }
+ scenariosr[i,t] <- Rfun(scenariosd[i,t])
+ if(t>=2 && scenariosr[i,t] < scenariosr[i,t-1]){
+ scenariosr[i,t] <- scenariosr[i,t-1]
+ }
}
+ }
- ## we need to adjust the recovery because intex has some embedded amortization assumptions
- ## that we can't turn off (multiply by recov.adj)
- intexrecov <- matrix(0, n.scenarios, dim(distDR)[1])
- for(i in 1:dim(distDR)[1]){
- if(i==1){
- intexrecov[,i] <- recov.adj * (scenariosr[,i]/scenariosd[,1])
- }else{
- intexrecov[,i] <- recov.adj * (scenariosr[,i]-scenariosr[,i-1])/(scenariosd[,i]-scenariosd[,i-1])
- }
+ ## we need to adjust the recovery because intex has some embedded amortization assumptions
+ ## that we can't turn off (multiply by recov.adj)
+ intexrecov <- matrix(0, n.scenarios, dim(distDR)[1])
+ for(i in 1:dim(distDR)[1]){
+ if(i==1){
+ intexrecov[,i] <- recov.adj * (scenariosr[,i]/scenariosd[,1])
+ }else{
+ intexrecov[,i] <- recov.adj * (scenariosr[,i]-scenariosr[,i-1])/(scenariosd[,i]-scenariosd[,i-1])
}
-
- cdr <- cdrfromscenarios(scenariosd, deal.dates)
- ## linear approximation for monthly scenarios
- deal.data <- getdealdata(dealnames[j])
- deal.datesmonthly <- getdealschedule(deal.data, "1 month")
- deal.datesmonthlylagged <- getdealschedule(deal.data, "1 month", workdate, 92)
- cdrmonthly <- matrix(0, n.scenarios, length(deal.datesmonthly))
- recoverymonthly <- matrix(0, n.scenarios, length(deal.datesmonthly))
- scenariosrmonthly <- matrix(0, n.scenarios, length(deal.datesmonthly))
- scenariosdmonthly <- matrix(0, n.scenarios, length(deal.datesmonthly))
- for(i in 1:n.scenarios){
- cdrmonthly[i,] <- approx(deal.dates, cdr[i,], deal.datesmonthly, rule=2)$y
- recoverymonthly[i,] <- approx(deal.dates, intexrecov[i,], deal.datesmonthly, rule=2)$y
- scenariosrmonthly[i,] <- approx(deal.dates, scenariosr[i,], deal.datesmonthly, rule=2)$y
- scenariosdmonthly[i,] <- approx(deal.dates, scenariosd[i,], deal.datesmonthly, rule=2)$y
+ }
+
+ cdr <- cdrfromscenarios(scenariosd, deal.dates)
+ ## linear approximation for monthly scenarios
+ deal.data <- getdealdata(dealnames[j])
+ deal.datesmonthly <- getdealschedule(deal.data, "1 month")
+ deal.datesmonthlylagged <- getdealschedule(deal.data, "1 month", workdate, 92)
+ cdrmonthly <- matrix(0, n.scenarios, length(deal.datesmonthly))
+ recoverymonthly <- matrix(0, n.scenarios, length(deal.datesmonthly))
+ scenariosrmonthly <- matrix(0, n.scenarios, length(deal.datesmonthly))
+ scenariosdmonthly <- matrix(0, n.scenarios, length(deal.datesmonthly))
+ for(i in 1:n.scenarios){
+ cdrmonthly[i,] <- approx(deal.dates, cdr[i,], deal.datesmonthly, rule=2)$y
+ recoverymonthly[i,] <- approx(deal.dates, intexrecov[i,], deal.datesmonthly, rule=2)$y
+ scenariosrmonthly[i,] <- approx(deal.dates, scenariosr[i,], deal.datesmonthly, rule=2)$y
+ scenariosdmonthly[i,] <- approx(deal.dates, scenariosd[i,], deal.datesmonthly, rule=2)$y
+ }
+ recoverymonthly <- pmin(recoverymonthly,1)
+ ## compute reinvestment price
+ if(reinvflags[j]){
+ if(deal.data$"Reinv End Date" <= workdate){
+ ## we cap rolling maturity at the current weighted average maturity of the portfolio
+ rollingmaturity <- (crossprod(sapply(deal.portfolio$SC, creditcurve.maturity),
+ deal.portfolio$notional)/sum(deal.portfolio$notional)
+ - as.numeric(workdate))/365*12
+ }else{
+ rollingmaturity <- basecase.rollingmaturity
}
- recoverymonthly <- pmin(recoverymonthly,1)
- ## compute reinvestment price
- if(reinvflags[j]){
- DC <- DiscountCurve(L3m$params, L3m$tsQuotes, yearFrac(L3m$params$tradeDate, deal.datesmonthlylagged))
- df <- DC$discounts
- forwards <- DC$forwards
- reinvprices <- compute.reinvprices(df, forwards, cdrmonthly, recoverymonthly, reinvspread,
- reinvfixed, rollingmaturity, reinvlag)
+ DC <- DiscountCurve(L3m$params, L3m$tsQuotes, yearFrac(L3m$params$tradeDate, deal.datesmonthlylagged))
+ df <- DC$discounts
+ forwards <- DC$forwards
+ reinvprices <- compute.reinvprices(df, forwards, cdrmonthly, recoverymonthly, reinvspread,
+ reinvfixed, rollingmaturity, reinvlag)
- reinvassets <- convert.reinvtoperct(get.reinvassets(dealnames[j]))
- ## all amounts are in units of current collateral balance
- reinvdollar <- matrix(0, n.scenarios, length(deal.datesmonthly))
- maturingbalance <- matrix(0, n.scenarios, length(deal.datesmonthly))
- reinvdollar[,1] <- scenariosrmonthly[,1] + deal.data$"Principal Bal"/deal.data$"Curr Collat Bal"
- loanprices <- crossprod(reinvdollar[,1], reinvprices$loan[,1])/sum(reinvdollar[,1])
- bondprices <- c(crossprod(reinvdollar[,1], reinvprices$bond[,1])/sum(reinvdollar[,1]))
- maturingbalance[,min(1+rollingmaturity, length(deal.datesmonthly))] <-
- reinvdollar[,1]/crossprod(reinvassets, c(loanprices[1], bondprices[1]))
- reinvbalance <- matrix(0, n.scenarios, length(deal.datesmonthly))
- for(t in 2:dim(cdrmonthly)[2]){
- reinvdollar <- scenariosrmonthly[,t]-scenariosrmonthly[,t-1]+
- reinvbalance*cdrmonthly[,t]/100* recoverymonthly[,t]*yearFrac(deal.datesmonthly[t-1], deal.datesmonthly[t])
- if(t==(dim(cdrmonthly)[2]-1)){
- reinvbalance[,t] <- maturingbalance[,length(deal.datesmonthly)]
- }else if(t==dim(cdrmonthly)[2]){
- reinvbalance[,t] <- 0
- }else{
- reinvbalance[,t] <- rowSums(maturingbalance[,(t+1):length(deal.datesmonthly)])
- }
- reinvdollar[,t] <- scenariosrmonthly[,t] - scenariosrmonthly[,t-1] +
- reinvbalance[,t] * cdrmonthly[,t]/100 * recoverymonthly[,t] *
- yearFrac(deal.datesmonthly[t-1], deal.datesmonthly[t])
- loanprices <- c(loanprices, crossprod(reinvdollar[,t], reinvprices$loan[,t])/sum(reinvdollar[,t]))
- bondprices <- c(bondprices, crossprod(reinvdollar[,t], reinvprices$bond[,t])/sum(reinvdollar[,t]))
- maturingbalance[,min(t+rollingmaturity, length(deal.datesmonthly))] <-
- reinvdollar[,t]/crossprod(reinvassets, c(loanprices[t], bondprices[t]))
- maturingbalance[,min(t+rollingmaturity, length(deal.datesmonthly))] <-
- maturingbalance[,min(t+rollingmaturity, length(deal.datesmonthly))] +
- reinvdollar[,t]/loanprices[t]
- }
- }
- save.dir <- file.path(root.dir, "Scenarios", paste("Intex curves", workdate, sep="_"), "csv")
- if(!file.exists(save.dir)){
- dir.create(save.dir, recursive = T)
+ reinvassets <- convert.reinvtoperct(get.reinvassets(dealnames[j]))
+ ## all amounts are in units of current collateral balance
+ reinvdollar <- matrix(0, n.scenarios, length(deal.datesmonthly))
+ maturingbalance <- matrix(0, n.scenarios, length(deal.datesmonthly))
+ reinvdollar[,1] <- scenariosrmonthly[,1] + deal.data$"Principal Bal"/deal.data$"Curr Collat Bal"
+ loanprices <- crossprod(reinvdollar[,1], reinvprices$loan[,1])/sum(reinvdollar[,1])
+ bondprices <- c(crossprod(reinvdollar[,1], reinvprices$bond[,1])/sum(reinvdollar[,1]))
+ maturingbalance[,min(1+rollingmaturity, length(deal.datesmonthly))] <-
+ reinvdollar[,1]/crossprod(reinvassets, c(loanprices[1], bondprices[1]))
+ reinvbalance <- matrix(0, n.scenarios, length(deal.datesmonthly))
+ for(t in 2:dim(cdrmonthly)[2]){
+ reinvdollar <- scenariosrmonthly[,t]-scenariosrmonthly[,t-1] +
+ reinvbalance * cdrmonthly[,t]/100 * recoverymonthly[,t] *
+ yearFrac(deal.datesmonthly[t-1], deal.datesmonthly[t])
+ if(t==(dim(cdrmonthly)[2]-1)){
+ reinvbalance[,t] <- maturingbalance[,length(deal.datesmonthly)]
+ }else if(t==dim(cdrmonthly)[2]){
+ reinvbalance[,t] <- 0
+ }else{
+ reinvbalance[,t] <- rowSums(maturingbalance[,(t+1):length(deal.datesmonthly)])
+ }
+ reinvdollar[,t] <- scenariosrmonthly[,t] - scenariosrmonthly[,t-1] +
+ reinvbalance[,t] * cdrmonthly[,t]/100 * recoverymonthly[,t] *
+ yearFrac(deal.datesmonthly[t-1], deal.datesmonthly[t])
+ loanprices <- c(loanprices, crossprod(reinvdollar[,t], reinvprices$loan[,t])/sum(reinvdollar[,t]))
+ bondprices <- c(bondprices, crossprod(reinvdollar[,t], reinvprices$bond[,t])/sum(reinvdollar[,t]))
+ maturingbalance[,min(t+rollingmaturity, length(deal.datesmonthly))] <-
+ reinvdollar[,t]/crossprod(reinvassets, c(loanprices[t], bondprices[t]))
+ maturingbalance[,min(t+rollingmaturity, length(deal.datesmonthly))] <-
+ maturingbalance[,min(t+rollingmaturity, length(deal.datesmonthly))] +
+ reinvdollar[,t]/loanprices[t]
}
+ }
+
+ save.dir <- file.path(root.dir, "Scenarios", paste("Intex curves", workdate, sep="_"), "csv")
+ if(!file.exists(save.dir)){
+ dir.create(save.dir, recursive = T)
+ }
- write.table(cdrmonthly,
- file= file.path(save.dir, paste0(dealnames[j],"-cdr.csv")),
+ write.table(cdrmonthly,
+ file= file.path(save.dir, paste0(dealnames[j],"-cdr.csv")),
+ row.names=F, col.names=F, sep=",")
+ write.table(100 * recoverymonthly,
+ file=file.path(save.dir, paste0(dealnames[j],"-recovery.csv")),
+ row.names=F, col.names=F, sep=",")
+ if(reinvflags[j]){
+ write.table(100 * reinvprices$loan,
+ file = file.path(save.dir, paste0(dealnames[j], "-floatreinvprices.csv")),
row.names=F, col.names=F, sep=",")
- write.table(100 * recoverymonthly,
- file=file.path(save.dir, paste0(dealnames[j],"-recovery.csv")),
+ write.table(100 * reinvprices$bond,
+ file = file.path(save.dir, paste0(dealnames[j], "-fixedreinvprices.csv")),
row.names=F, col.names=F, sep=",")
- if(reinvflags[j]){
- write.table(100 * reinvprices$loan,
- file = file.path(save.dir, paste0(dealnames[j], "-floatreinvprices.csv")),
- row.names=F, col.names=F, sep=",")
- write.table(100 * reinvprices$bond,
- file = file.path(save.dir, paste0(dealnames[j], "-fixedreinvprices.csv")),
- row.names=F, col.names=F, sep=",")
- write.table(cbind(100 * loanprices, 100 * bondprices),
- file = file.path(save.dir, paste0(dealnames[j], "-reinvprices.csv")),
- row.names=F, col.names=F, sep=",")
- }
- save(scenariosd, scenariosr, dist.joint, file=file.path(save.dir, paste0(dealnames[j], ".RData")),
- compress="xz")
+ write.table(cbind(100 * loanprices, 100 * bondprices),
+ file = file.path(save.dir, paste0(dealnames[j], "-reinvprices.csv")),
+ row.names=F, col.names=F, sep=",")
+ cat(rollingmaturity, file=file.path(save.dir, paste0(dealnames[j], "-rollingmat")))
+ }
+ save(scenariosd, scenariosr, dist.joint, file=file.path(save.dir, paste0(dealnames[j], ".RData")),
+ compress="xz")
- cat("generated scenarios for:", dealnames[j], "\n")
+ cat("generated scenarios for:", dealnames[j], "\n")
}
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