1 files changed, 0 insertions, 92 deletions
diff --git a/R/script_calibrate_tranches.R b/R/script_calibrate_tranches.R
deleted file mode 100644
index 95a9082e..00000000
--- a/R/script_calibrate_tranches.R
+++ /dev/null
@@ -1,92 +0,0 @@
-#!/usr/bin/Rscript
-require(methods)
-library(lossdistrib)
-
-options(warn=2)
-args <- commandArgs(trailingOnly=TRUE)
-
-if(.Platform$OS.type == "unix"){
-  root.dir <- "/home/share/CorpCDOs"
-}else{
-  root.dir <- "//WDSENTINEL/share/CorpCDOs"
-}
-
-code.dir <- Sys.getenv("CODE_DIR")
-if(code.dir==""){
-    code.dir<-root.dir
-}
-source(file.path(code.dir, "code", "R", "yieldcurve.R"))
-source(file.path(code.dir, "code", "R", "optimization.R"))
-source(file.path(code.dir, "code", "R", "calibration.R"), chdir=TRUE)
-source(file.path(code.dir, "code", "R", "mlpdb.R"))
-
-##figure out the tradedate
-if(length(args) >= 1){
-  tradedate <- as.Date(args[1])
-}else{
-  tradedate <- addBusDay(Sys.Date(), -1)
-}
-
-exportYC(tradedate)
-## calibrate HY21
-## calibrate the single names curves
-n.int <- 250
-list2env(GHquad(n.int), envir=parent.frame())
-Ngrid <- 201
-index <- load.index("hy21", date=tradedate, "5yr", Z, w, Ngrid)
-index <- set.singlenamesdata(index, tradedate)
-index <- set.tranchedata(index, tradedate)
-
-## load tranche data
-n.credit <- length(index$portfolio)
-index$cs$coupons <- index$cs$coupons*0.05
-##calibrate by modifying the factor distribution
-bottomup <- 1:3
-topdown <- 2:4
-
-index$w.mod <- w
-p <- index$defaultprob
-rho <- rep(0.45, n.credit)
-result <- matrix(0, 4, n.int)
-err <- Inf
-errvec <- c()
-while(err >0.01){
-    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$Z)
-    }
-    for(i in 1:n.int){
-        result[,i] <- tranche.pvvec(index$K, L[,i,], R[,i,], index$cs)
-    }
-    ## solve the optimization problem
-    program <- KLfit(-result[bottomup,], w, index$tranche.quotes[bottomup])
-
-    err <- 0
-    for(i in 1:n.credit){
-        for(j in 1:ncol(p)){
-            err <- err + abs(crossprod(shockprob(p[i,j], rho[i], Z), program$weight) - index$defaultprob[i,j])
-        }
-    }
-    errvec <- c(errvec, err)
-
-    ## update the new probabilities
-    p <- MFupdate.probC(Z, program$weight, rho, index$defaultprob)
-
-    errvec <- c(errvec, err)
-    index$w.mod <- program$weight
-    cat(err,"\n")
-}
-
-dist <- MFdist(index)
-
-write.table(data.frame(Z=Z, w=index$w.mod),
-            file=file.path(root.dir, "Scenarios", "Calibration",
-            paste0("calibration-", tradedate, ".csv")),
-            col.names=T, row.names=F, sep=",")
-
-save(index, dist, file = file.path(root.dir, "Scenarios", "Calibration",
-                     paste0("marketdata-", tradedate, ".RData")), compress="xz")