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library(RPostgreSQL)
library(RQuantLib)
if(.Platform$OS.type == "unix"){
root.dir <- "/home/share/CorpCDOs"
}else{
root.dir <- "//WDSENTINEL/share/CorpCDOs"
}
source(file.path(root.dir, "code", "R", "etdb.R"))
source(file.path(root.dir, "code", "R", "yieldcurve.R"))
source(file.path(root.dir, "code", "R", "cds_utils.R"))
workdate <- as.Date("2013-01-30")
MarkitData <- getMarkitIRData(as.Date(workdate))
L1m <- buildMarkitYC(MarkitData, dt = 1/12)
L2m <- buildMarkitYC(MarkitData, dt = 1/6)
L3m <- buildMarkitYC(MarkitData)
L6m <- buildMarkitYC(MarkitData, dt = 1/2)
L12m <- buildMarkitYC(MarkitData, dt = 1)
setEvaluationDate(as.Date(MarkitData$effectiveasof))
sanitize.column <- function(vec){
vec <- gsub(",", "", vec)
index <- grep("\\(", vec)
for(l in index){
vec[l] <- -as.numeric(substr(vec[l], 2, nchar(vec[l])-1))
}
return( as.numeric(vec) )
}
fields <- c("Cashflow", "Principal", "Interest")
tranches <- c("COLLAT_REINVEST", "COLLAT_INITIAL")
n.scenarios <- 100
cfdata <- list()
dealnames <- list.files(file.path(root.dir, "Scenarios", paste0("Prices_", workdate)), "*COLLAT_INITIAL-CF-Scen1*")
dealnames <- sapply(strsplit(dealnames, "-"), function(x) x[1])
dealnames <- tolower(unique(dealnames))
flag <- FALSE
for(dealname in dealnames){
cfdata[[dealname]] <- list()
r <- matrix(0, n.scenarios, 3)
colnames(r) <- fields
sqlstring <- sprintf("select marketvalue from latest_deal_model_numbers where dealname='%s'", dealname)
mv <- dbGetQuery(dbCon, sqlstring)$marketvalue
sqlstring <- sprintf("select \"Curr Collat Bal\" from latest_clo_universe where dealname='%s'", dealname)
currbal <- dbGetQuery(dbCon, sqlstring)$"Curr Collat Bal"
cfdata[[dealname]]$mv <- mv
cfdata[[dealname]]$currbal <- currbal
for(tranche in tranches){
for(i in 1:n.scenarios){
filename <- paste0(paste(toupper(dealname), tranche, "CF", paste0("Scen", i), sep="-"), ".txt")
data <- read.table(file.path(root.dir, "Scenarios", paste0("Prices_", workdate), filename),
sep="\t", header=T, skip =3, colClasses="character", comment.char="")
colnames(data) <- c("Date", "Cashflow", "Principal", "Interest")
data <- data[,1:4]
colnames(data) <- c("Date", "Cashflow", "Principal", "Interest")
data$Date <- as.Date(data$Date, "%b %d, %Y")
if(any(is.na(data$Date))){
sprintf("file: %s is messed up", filename)
flag <- TRUE
break
}
data <- data[data$Date >= Sys.Date(),]
if(i==1){
DC <- DiscountCurve(L3m$params, L3m$tsQuotes, yearFrac(L3m$params$tradeDate, data$Date))
}
pv <- c()
for(field in fields){
data[,field] <- sanitize.column(data[,field])
pv <- c(pv, crossprod(DC$discounts[1:length(data$Date)], data[,field]))
}
r[i,] <- pv
}
if(flag){
cfdata[[dealname]] <- NULL
flag <- FALSE
break
}else{
cfdata[[dealname]][[tranche]]<- r
}
}
}
r <- c()
for(dealname in dealnames){
r <- rbind(r, c(cfdata[[dealname]]$mv, cfdata[[dealname]]$currbal, apply(cfdata[[dealname]]$COLLAT_REINVEST, 2, mean)[1], apply(cfdata[[dealname]]$COLLAT_INITIAL, 2, mean)[1]))
}
colnames(r) <- c("mv", "currbal", "Reinvest", "Initial")
rownames(r) <- dealnames
flag <- FALSE
cusipdata <- list()
for(cusip in cusips){
r <- matrix(0, n.scenarios, 3)
colnames(r) <- fields
sqlstring <- sprintf("select curr_balance, spread from cusip_universe where cusip = '%s'", cusip)
indicdata <- dbGetQuery(dbCon, sqlstring)
cusipdata[[cusip]]$currbal <- indicdata$curr_balance
cusipdata[[cusip]]$spread <- indicdata$spread
for(i in 1:n.scenarios){
filename <- sprintf("%s-CF-Scen%s.txt", cusip, i)
if(length(list.files(file.path(root.dir, "Scenarios", paste0("Prices_", workdate)), filename))==0){
next
}
data <- read.table(file.path(root.dir, "Scenarios", paste0("Prices_", workdate), filename),
sep = "\t", header=T, colClasses="character", skip = 3, comment.char="")
data <- data[, 1:4]
colnames(data) <- c("Date", "Cashflow", "Principal", "Interest")
data$Date <- as.Date(data$Date, "%b %d, %Y")
if(any(is.na(data$Date))){
sprintf("file: %s is messed up", filename)
flag <- TRUE
break
}
data <- data[data$Date >= Sys.Date(),]
if(i==1){
DC <- DiscountCurve(L3m$params, L3m$tsQuotes, yearFrac(L3m$params$tradeDate, data$Date))
}
pv <- c()
for(field in fields){
data[,field] <- sanitize.column(data[,field])
pv <- c(pv, crossprod(DC$discounts[1:length(data$Date), data[,field]))
}
r[i,] <- pv
}
if(flag){
cusipsdata[[cusip]] <- NULL
flag <- FALSE
break
}else{
for(field in fields){
cusipdata[[cusip]][[field]] <- r[,field]
}
}
}
prices <- c()
duration <- c()
for(cusip in names(cusipdata)){
prices <- c(prices, mean(cusipdata[[cusip]]$Cashflow)/cusipdata[[cusip]]$currbal)
duration <- c(duration, mean(cusipdata[[cusip]]$Interest)/
(cusipdata[[cusip]]$currbal*cusipdata[[cusip]]$spread))
}
i <- 1
for(cusip in names(cusipdata)){
cat(cusip, prices[i], "\n")
i <- i+1
}
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