1 files changed, 174 insertions, 174 deletions
diff --git a/R/build_scenarios.R b/R/build_scenarios.R
index a2c0c190..f5255836 100644
--- a/R/build_scenarios.R
+++ b/R/build_scenarios.R
@@ -1,174 +1,174 @@
-library(doParallel)
-library(yaml)
-
-hostname <- system("hostname", intern=TRUE)
-if(hostname=="debian"){
-    registerDoParallel(8)
-}else{
-    registerDoParallel(4)
-}
-
-args <- commandArgs(trailingOnly=TRUE)
-
-if(.Platform$OS.type == "unix"){
-    root.dir <- "/home/share/CorpCDOs"
-}else{
-    root.dir <- "//WDSENTINEL/share/CorpCDOs"
-}
-
-code.dir <- if(Sys.getenv("CODE_DIR")=="") root.dir else Sys.getenv("CODE_DIR")
-source(file.path(code.dir, "code", "R", "intex_deal_functions.R"), chdir=TRUE)
-source(file.path(code.dir, "code", "R", "yieldcurve.R"))
-source(file.path(code.dir, "code", "R", "serenitasdb.R"), chdir=TRUE)
-source(file.path(code.dir, "code", "R", "tranche_functions.R"))
-
-if(interactive()) {
-    tradedate <- as.Date("2016-02-25")
-    dealnames <- c("beto", "ozlmf5")
-    reinvflags <- c(TRUE, TRUE)
-}else{
-    tradedate <- as.Date(args[1])
-    if(length(args) >=2){
-        argslist <- strsplit(args[-1], ",")
-        dealnames <- unlist(lapply(argslist, function(x)x[1]))
-        reinvflags <- as.logical(unlist(lapply(argslist, function(x)x[2])))
-    }
-}
-
-calibration.date <- addBusDay(tradedate, -1)
-settledate <- addBusDay(tradedate, 3)
-calibration <- read.table(file.path(root.dir, "Scenarios", "Calibration",
-                                    paste0("calibration-", calibration.date,".csv")), sep=",", header=T)
-Z <- calibration$Z
-w <- calibration$w
-exportYC(calibration.date)
-
-Ngrid <- 201
-support <- seq(0, 1, length = Ngrid)
-n.scenarios <- 100
-recov.adj <- 1
-params <- yaml.load_file(file.path(root.dir, "code", "etc", "params.yml"))
-
-for(j in seq_along(dealnames)){
-  load(file.path(root.dir, "Scenarios", paste("Portfolios", tradedate, sep="_"),
-                 paste(dealnames[j], "RData", sep=".")))
-  if(is.na(deal.data$reinv_end_date)){
-    reinvflags[j] <- FALSE
-  }
-  dp <- A$DP
-  pp <- A$PP
-  dpmod <- MFupdate.prob(Z, w, deal.portfolio$beta, dp)
-  ppmod <- MFupdate.prob(-Z, w, deal.portfolio$beta, pp)
-  dist.joint <- MFlossdist.prepay.joint(w, Z, deal.portfolio$beta, dp, dpmod, pp, ppmod,
-                                        deal.weights, 1-S, Ngrid)
-  dist.joint <- pmax(dist.joint, 0)
-  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), "hyman")
-    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
-      if(i==1){
-          scenariosd[i,t] <- 0.5* Dfun(0.01)
-      }else{
-          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])
-    }
-  }
-  deal.dates <- getdealschedule(deal.data, "Quarterly")
-  deal.dates <- deal.dates[deal.dates>=settledate]
-  cdr <- cdrfromscenarios(scenariosd, deal.dates, tradedate)
-  ## linear approximation for monthly scenarios
-  deal.data <- getdealdata(dealnames[j], tradedate)
-  deal.datesmonthly <- getdealschedule(deal.data, "Monthly")
-  deal.datesmonthly <- deal.datesmonthly[deal.datesmonthly>=settledate]
-
-  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)$y
-  }
-  recoverymonthly <- pmin(recoverymonthly,1)
-  recoverymonthly[!is.finite(recoverymonthly)] <- 100
-
-  if(!is.na(deal.data$reinv_end_date) && deal.data$reinv_end_date <= tradedate){
-      ## we cap rolling maturity at the current weighted average maturity of the portfolio
-      rollingmaturity <- (crossprod(sapply(deal.portfolio$SC, creditcurve.maturity),
-                                    deal.portfolio$notional)/sum(deal.portfolio$notional)
-                          - as.numeric(tradedate))
-  }else{
-      rollingmaturity <- params$rollingmaturity
-  }
-
-  ## compute reinvestment price
-  cdrmonthly.dt <- data.table(date=deal.datesmonthly, t(cdrmonthly), key="date")
-  recoverymonthly.dt <- data.table(date=deal.datesmonthly, t(recoverymonthly), key="date")
-  if(reinvflags[j]){
-      reinvprices <- compute.reinvprices(dealnames[j], cdrmonthly.dt, recoverymonthly.dt,
-                                         params, rollingmaturity, tradedate)
-  }else{
-      reinvprices <- list()
-  }
-
-  save.dir <- file.path(root.dir, "Scenarios", paste("Intex curves", tradedate, sep="_"), "csv")
-  if(!file.exists(save.dir)){
-    dir.create(save.dir, recursive = T)
-  }
-
-  write.table(cdrmonthly,
-              file= file.path(save.dir, paste0(dealnames[j],"-cdr.csv")),
-              row.names=F, col.names=F, sep=",")
-  write.table(100 * recoverymonthly,
-              file=file.path(save.dir, paste0(dealnames[j],"-recovery.csv")),
-              row.names=F, col.names=F, sep=",", na="NaN")
-  write.table(reinvprices, file = file.path(save.dir, paste0(dealnames[j], "-reinvprices.csv")),
-              row.names=F, col.names=T, sep=",")
-
-  configfile <- file.path(save.dir, paste0(dealnames[j], ".config"))
-  config <- list(rollingmat = as.integer(rollingmaturity/365*12),
-                 reinvflag = reinvflags[j])
-  cat(as.yaml(config), file = configfile)
-  save(scenariosd, scenariosr, dist.joint, file=file.path(save.dir, paste0(dealnames[j], ".RData")),
-       compress="xz")
-
-  cat("generated scenarios for:", dealnames[j], "\n")
-}
+library(doParallel)
+library(yaml)
+
+hostname <- system("hostname", intern=TRUE)
+if(hostname=="debian"){
+    registerDoParallel(8)
+}else{
+    registerDoParallel(4)
+}
+
+args <- commandArgs(trailingOnly=TRUE)
+
+if(.Platform$OS.type == "unix"){
+    root.dir <- "/home/share/CorpCDOs"
+}else{
+    root.dir <- "//WDSENTINEL/share/CorpCDOs"
+}
+
+code.dir <- if(Sys.getenv("CODE_DIR")=="") root.dir else Sys.getenv("CODE_DIR")
+source(file.path(code.dir, "code", "R", "intex_deal_functions.R"), chdir=TRUE)
+source(file.path(code.dir, "code", "R", "yieldcurve.R"))
+source(file.path(code.dir, "code", "R", "serenitasdb.R"), chdir=TRUE)
+source(file.path(code.dir, "code", "R", "tranche_functions.R"))
+
+if(interactive()) {
+    tradedate <- as.Date("2016-02-25")
+    dealnames <- c("beto", "ozlmf5")
+    reinvflags <- c(TRUE, TRUE)
+}else{
+    tradedate <- as.Date(args[1])
+    if(length(args) >=2){
+        argslist <- strsplit(args[-1], ",")
+        dealnames <- unlist(lapply(argslist, function(x)x[1]))
+        reinvflags <- as.logical(unlist(lapply(argslist, function(x)x[2])))
+    }
+}
+
+calibration.date <- addBusDay(tradedate, -1)
+settledate <- addBusDay(tradedate, 3)
+calibration <- read.table(file.path(root.dir, "Scenarios", "Calibration",
+                                    paste0("calibration-", calibration.date,".csv")), sep=",", header=T)
+Z <- calibration$Z
+w <- calibration$w
+exportYC(calibration.date)
+
+Ngrid <- 201
+support <- seq(0, 1, length = Ngrid)
+n.scenarios <- 100
+recov.adj <- 1
+params <- yaml.load_file(file.path(root.dir, "code", "etc", "params.yml"))
+
+for(j in seq_along(dealnames)){
+  load(file.path(root.dir, "Scenarios", paste("Portfolios", tradedate, sep="_"),
+                 paste(dealnames[j], "RData", sep=".")))
+  if(is.na(deal.data$reinv_end_date)){
+    reinvflags[j] <- FALSE
+  }
+  dp <- A$DP
+  pp <- A$PP
+  dpmod <- MFupdate.prob(Z, w, deal.portfolio$beta, dp)
+  ppmod <- MFupdate.prob(-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)
+  dist.joint <- pmax(dist.joint, 0)
+  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), "hyman")
+    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
+      if(i==1){
+          scenariosd[i,t] <- 0.5* Dfun(0.01)
+      }else{
+          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])
+    }
+  }
+  deal.dates <- getdealschedule(deal.data, "Quarterly")
+  deal.dates <- deal.dates[deal.dates>=settledate]
+  cdr <- cdrfromscenarios(scenariosd, deal.dates, tradedate)
+  ## linear approximation for monthly scenarios
+  deal.data <- getdealdata(dealnames[j], tradedate)
+  deal.datesmonthly <- getdealschedule(deal.data, "Monthly")
+  deal.datesmonthly <- deal.datesmonthly[deal.datesmonthly>=settledate]
+
+  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)
+  recoverymonthly[!is.finite(recoverymonthly)] <- 100
+
+  if(!is.na(deal.data$reinv_end_date) && deal.data$reinv_end_date <= tradedate){
+      ## 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$notional)
+                          - as.numeric(tradedate))
+  }else{
+      rollingmaturity <- params$rollingmaturity
+  }
+
+  ## compute reinvestment price
+  cdrmonthly.dt <- data.table(date=deal.datesmonthly, t(cdrmonthly), key="date")
+  recoverymonthly.dt <- data.table(date=deal.datesmonthly, t(recoverymonthly), key="date")
+  if(reinvflags[j]){
+      reinvprices <- compute.reinvprices(dealnames[j], cdrmonthly.dt, recoverymonthly.dt,
+                                         params, rollingmaturity, tradedate)
+  }else{
+      reinvprices <- list()
+  }
+
+  save.dir <- file.path(root.dir, "Scenarios", paste("Intex curves", tradedate, 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")),
+              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=",", na="NaN")
+  write.table(reinvprices, file = file.path(save.dir, paste0(dealnames[j], "-reinvprices.csv")),
+              row.names=F, col.names=T, sep=",")
+
+  configfile <- file.path(save.dir, paste0(dealnames[j], ".config"))
+  config <- list(rollingmat = as.integer(rollingmaturity/365*12),
+                 reinvflag = reinvflags[j])
+  cat(as.yaml(config), file = configfile)
+  save(scenariosd, scenariosr, dist.joint, file=file.path(save.dir, paste0(dealnames[j], ".RData")),
+       compress="xz")
+
+  cat("generated scenarios for:", dealnames[j], "\n")
+}