1 files changed, 6 insertions, 6 deletions
diff --git a/R/script_calibrate_tranches.R b/R/script_calibrate_tranches.R
index ab29feca..10e8f470 100644
--- a/R/script_calibrate_tranches.R
+++ b/R/script_calibrate_tranches.R
@@ -63,20 +63,20 @@ issuerweights <- rep(1/length(hy21portfolio), length(hy21portfolio))
 ## load tranche data
 K <- c(0, 0.15, 0.25, 0.35, 1)
 Kmodified <- adjust.attachments(K, hy21$loss, hy21$factor)
-markit.data <- read.csv(file.path(root.dir, "Scenarios", "Calibration",
+market.data <- read.csv(file.path(root.dir, "Scenarios", "Calibration",
                                   paste0("hy21_tranches_", tradedate, ".csv")))
 
-tranche.upf <- markit.data$Mid
+tranche.upf <- market.data$Mid
 tranche.running <- c(0.05, 0.05, 0.05, 0.05)
 # get the index ref
-hy21$indexref <- markit.data$bidRefPrice[1]/100
+hy21$indexref <- market.data$bidRefPrice[1]/100
 hy21portfolio.tweaked <- tweakcurves(hy21portfolio, hy21, tradedate)
 SurvProb <- SPmatrix(hy21portfolio.tweaked, hy21)
 
 Ngrid <- 2 * nrow(nondefaulted) + 1
 recov <- sapply(hy21portfolio.tweaked, attr, "recovery")
-cs <- couponSchedule(nextIMMDate(tradedate), hy21$maturity,"Q", "FIXED", 0.05, 0)
-
+cs <- couponSchedule(IMMDate(tradedate), hy21$maturity,"Q", "FIXED", 0.05, 0, tradedate, IMMDate(tradedate, "prev"))
+acc <- cdsAccrued(tradedate, 0.05)
 ##calibrate by modifying the factor distribution
 bottomup <- 1:3
 topdown <- 2:4
@@ -107,7 +107,7 @@ for(l in 1:150){
         R[,,t] <- t(lossdistCZ(p[,t], issuerweights, 1-S, Ngrid, 0, rho, Z))
     }
     for(i in 1:n.int){
-        result[,i] <- tranche.pvvec(Kmodified, L[i,,], R[i,,], cs)
+        result[,i] <- tranche.pvvec(Kmodified, L[i,,], R[i,,], cs) - acc
     }
     ## solve the optimization problem
     program <- KLfit(100*(result[bottomup,]+1), w, tranche.upf[bottomup])