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library(ggplot2)
library(lubridate)
library(doParallel)
if(.Platform$OS.type == "unix"){
root.dir <- "/home/share/CorpCDOs"
}else{
root.dir <- "//WDSENTINEL/share/CorpCDOs"
}
hostname <- system("hostname", intern=TRUE)
if(hostname=="debian"){
registerDoParallel(4)
}else{
registerDoParallel(8)
}
source(file.path(root.dir, "code", "R", "serenitasdb.R"))
source(file.path(root.dir, "code", "R", "cds_functions_generic.R"))
source(file.path(root.dir, "code", "R", "yieldcurve.R"))
get.indexquotes <- function(index, series, tenors=c("3yr", "5yr", "7yr")){
arraystring1 <- paste0("Array[''", paste(tenors, collapse = "'', ''"), "'']::tenor[]")
arraystring2 <- paste0('"', paste(tenors, collapse='" float, "'), '" float')
sqlstr <- paste("select * from crosstab('select date, tenor, closeprice from index_quotes",
"where index=''%s''",
"and series=%s order by date, tenor', 'select unnest(%s)')",
"AS ct(date date, %s)")
stmt <- sprintf(sqlstr, index, series, arraystring1, arraystring2)
df <- dbGetQuery(serenitasdb, stmt)
return( df )
}
get.indexmaturity <- function(index, series){
sqlstr <- paste("select maturity, coupon/cast(10000 as float)as running, tenor",
"from index_maturity where index='%s'",
"and series=%s order by maturity")
stmt <- sprintf(sqlstr, index, series)
df <- dbGetQuery(serenitasdb, stmt)
return( df )
}
fastduration <- function(sc, cs, tradedate, maturities){
r <- rep(NA, length(maturities))
if(is.null(sc)){
return( r )
}
startdate <- tradedate+1
acc <- cdsAccrued(tradedate, 1)
for(i in seq_along(maturities)){
if(startdate>maturities[i]){
r[i] <- NA
}else{
r[i] <- couponleg(cs[cs$unadj.dates<=maturities[i],], sc,
startdate, accruedondefault=TRUE)-acc
}
}
return( r )
}
fasttheta <- function(sc, cs, recov, tradedate, maturities, quotes){
r <- rep(NA, length(maturities))
if(is.null(sc)){
return(r)
}
startdate <- tradedate+1
acc <- cdsAccrued(tradedate, 1)
newmaturities <- maturities+years(-1)
for(i in seq_along(newmaturities)){
## never extrapolate, and do not attempt to compute theta if within 1 year
if(startdate>newmaturities[i] || is.na(quotes[i])){
next
}else{
newcs <- cs[cs$unadj.dates<=newmaturities[i],]
upfront <- defaultleg(newcs, sc, recov, startdate) -
(couponleg(newcs, sc, startdate, accruedondefault=TRUE)-acc)*0.05
r[i] <- quotes[i]-upfront+0.05
}
}
return( r )
}
convertNA <- function(x){
if(is.na(x)){
return( "Null" )
}else{
return( x )
}
}
index <- 'HY'
tenors <- c("3yr", "5yr", "7yr")
recov <- 0.3
sqlstr <- paste("UPDATE index_quotes set duration=%s, theta=%s where date='%s' and index='%s'",
"and series=%s and tenor='%s'")
for(series in c(9, 10, 11, 13, 15, 17, 19, 21, 23)){
indexquotes <- get.indexquotes(index, series)
maturities <- get.indexmaturity(index, series)
maturities <- maturities[maturities$tenor %in% tenors,]
indexquotes <- indexquotes[indexquotes$date<=maturities$maturity[3],]
durations <- matrix(0, nrow(indexquotes), length(tenors))
thetas <- matrix(0, nrow(indexquotes), length(tenors))
maturity <- maturities[nrow(maturities), "maturity"]
durandthetas <- foreach(i = 1:nrow(indexquotes), .combine='rbind') %dopar% {
tradedate <- indexquotes[i, "date"]
exportYC(tradedate)
cs <- couponSchedule(IMMDate(tradedate, noadj=TRUE), maturity,"Q", "FIXED", 1,
0, tradedate, IMMDate(tradedate, "prev"))
quotes <- data.frame(upfront=(100-as.numeric(indexquotes[i,-1]))/100, maturities)
sc <- cdshazardrate(quotes, recov, tradedate, cs)
c(fastduration(sc, cs, tradedate, maturities$maturity),
fasttheta(sc, cs, recov, tradedate, maturities$maturity, quotes$upfront))
}
df.durations <- data.frame(date=indexquotes$date, durandthetas[,1:3])
df.thetas <- data.frame(date=indexquotes$date, durandthetas[,4:6])
colnames(df.durations) <- c("date", tenors)
colnames(df.thetas) <- c("date", tenors)
for(i in 1:nrow(df.durations)){
for(tenor in tenors){
stmt <- sprintf(sqlstr, convertNA(df.durations[i,tenor]), convertNA(df.thetas[i, tenor]),
df.durations[i,"date"], index, series, tenor)
dbSendQuery(serenitasdb, stmt)
}
}
## nice plot, now I'm just showing off
ggplot(df.durations, aes(x=date))+geom_line(aes(y=`3yr`, colour="3yr"))+
geom_line(aes(y=`5yr`, colour="5yr"))+
geom_line(aes(y=`7yr`, colour="7yr"))+ylab("duration")+labs(colour="tenor")
ggsave(filename=paste0("HY", series, " durations.png"))
## plot thetas
ggplot(df.thetas, aes(x=date))+geom_line(aes(y=`3yr`, colour="3yr"))+
geom_line(aes(y=`5yr`, colour="5yr"))+
geom_line(aes(y=`7yr`, colour="7yr"))+ylab("theta")+labs(colour="tenor")
ggsave(filename=paste0("HY", series, " thetas.png"))
}
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