# [R] Running the Loop

arun smartpink111 at yahoo.com
Wed Feb 5 01:29:19 CET 2014

```Hi Katherine,Not sure if this helps.  I was able to the result after making up some additional conditions into your function.

fun1 <- function(x){
lst1 <- lapply(seq(n-1),function(i){
with(x,if(maturity_period >D[i] & maturity_period <D[i+1]){
data.frame(N1=paste(curve,T[i],sep="_"),N2=paste(curve,T[i+1],sep="_"),PV1=mtm*root,PV2=(mtm)*(1-root))
}
else if(maturity_period < D[i]) {
data.frame(N1=paste(curve,T[i],sep="_"),N2=paste(curve,T[i],sep="_"),PV1=mtm,PV2=0)
}
else if(maturity_period >D[i+1]) {
data.frame(N1=paste(curve,T[i],sep="_"),N2=paste(curve,T[i],sep="_"),PV1=0,PV2=mtm)
}
)
}
)
dat2 <- cbind(id=x\$id,do.call(rbind,lst1))
indx <- with(dat2,PV1!=0 & PV2!=0)
dat2New<- if(!any(indx)){
dat2[1,]
}
else dat2[indx,]
colnames(dat2New)[-1] <-paste0(paste0("Risk_factor",rep(1:2,2)),rep(c("","_mtm"),each=2))
dat2New
}

ddply(dat,.(id),fun1)
#  id Risk_factor1 Risk_factor2 Risk_factor1_mtm Risk_factor2_mtm
#1  1       USD_1m       USD_1m             1000                0
#2  2       USD_3m       USD_6m             2000             8000
#3  3      USD_12m      USD_5yr            74000            26000

A.K.

On Tuesday, February 4, 2014 7:22 AM, Katherine Gobin <katherine_gobin at yahoo.com> wrote:
Dear R forum,

I have following data.frames

dat = data.frame(id = c(1:3), root = c(0.10, 0.20, 0.74), maturity_period = c(20, 155, 428), mtm = c(1000, 10000, 100000), curve = c("USD", "USD", "USD"))

> dat
id root maturity_period   mtm curve
1  1 0.10              20 1e+03   USD
2  2 0.20             155 1e+04   USD
3  3 0.74             428 1e+05   USD

standard_tenors = data.frame(T = c("1m", "3m", "6m", "12m", "5yr"), D = c(30, 91, 182, 365, 1825))

> standard_tenors
T    D
1  1m   30
2  3m   91
3  6m  182
4 12m  365
5 5yr 1825

# .................................................................................................................

library(plyr)

T = standard_tenors\$T

D = standard_tenors\$D
n = length(standard_tenors\$T)

mtm_split_function = function(maturity_period, curve, root, mtm)

{

for(i in 1:(n-1))
{
if (maturity_period < D[i])

{
N1 = paste(curve, T[i], sep ="_")
N2 = paste(curve, T[i], sep ="_")
PV1 = mtm
PV2 = 0
}else

if (maturity_period > D[i] & maturity_period < D[i+1])

{
N1 = paste(curve, T[i], sep ="_")
N2 = paste(curve, T[1+1], sep ="_")
PV1 = (mtm)*root
PV2 = (mtm)*(1-root)
}else

if (maturity_period > D[i+1])
{
N1 = paste(curve, T[i], sep ="_")
N2 = paste(curve, T[i], sep ="_")
PV1 = 0
PV2 = mtm
}

}

return(data.frame(Risk_factor1 = N1, Risk_factor2 = N2, Risk_factor1_mtm = PV1,
Risk_factor2_mtm = PV2))
}

# .....................................................................................................................

splitted_mtm <- ddply(.data = dat, .variables = "id",
.fun=function(x) mtm_split_function(maturity_period = x\$maturity_period, curve = x\$curve, root = x\$root, mtm = x\$mtm))

# OUTPUT I am getting

id Risk_factor1 Risk_factor2 Risk_factor1_mtm Risk_factor2_mtm
1  1      USD_12m      USD_12m             1000                0
2  2      USD_12m      USD_12m            10000                0
3  3      USD_12m       USD_3m            74000            26000

# My PROBLEM

However, My OUTPUT should be

id Risk_factor1 Risk_factor2 Risk_factor1_mtm Risk_factor2_mtm
1  1      USD_1m       USD_1m             1000                0
2  2      USD_3m       USD_6m             2000             8000
3  3      USD_12m      USD_5yr           74000            26000

Kindly guide

With warm regards

Katherine
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