'Transform code of two loops ("For") with lapply or sapply
I am learning how to code in R and I have written a piece of code that calculate the Net Present Value (NPV) of various assets at different points in time, given a data frame. For this, I am using two "for" loops and I find it very slow.
The first loop get the asset for which I need to calculate the NPV. The second loop get the Date from which the NPV will be calculated with the sub-function "npv_date"
I was wondering if I can get some assistance to convert it to use either the sapply or lapply or another function. Here is my working R code:
#Create the column NPV in the data frame
Ejemplo <- as.data.frame(Ejemplo %>% mutate(npv = -1))
for(j in unique(Ejemplo$Key)){
#Create subset per Asset by the Key
SubTable <- subset(Ejemplo, Ejemplo$Key==j)
for (i in unique(SubTable$KeyDate)){
#cal the function that calculate the NPV per date
Ejemplo <- npv_date(Tabla=Ejemplo, key=j, keyDate=i)
}
}
#function that calculate the npv per asset and date
npv_date <- function(Tabla, key, keyDate){
#create a subset only with the asset selected
subTable <- subset(Tabla, Tabla$Key==key)
#ger the flow that we need to calculate the NPV
flow <- unique(subTable [match(keyDate,subTable$KeyDate):length(subTable$Key), "Flow"]
#get the rate for the date on which we are going to calculate the NPV
#Question: i am using only one Rate, the rate corresponding to the month
#of calculation, but a vector of rates can be used
irr <- (subTable %>% filter(KeyDate == keyDate))$Rate
#calculate the NPV calling the sub-function dcf
npv <- sum(dcf(x=flow, r=irr))
#Assign the value to the corresponding row
Tabla[["npv"]][(Tabla[["KeyDate"]]==keyDate)&(Tabla[["Key"]]==key)] <- npv
return(Tabla)
}
dcf <- function(x, r, t0=FALSE){
# calculates discounted cash flows (DCF) given cash flow and discount rate
# x - cash flows vector
# r - vector or numeric value of discount rate(s), in decimals. Single values will be recycled
# t0 - cash flow starts in year 0, default is FALSE, i.e. discount rate in first period is zero. Will be ignored if r is a vector
if(length(r)==1){
r <- rep(r, length(x))
if(t0==TRUE){r[1]<-0}
}
x/cumprod(1+r)
}
I attach an example with twoo asset, where you can find the Date, Flow (Cah flow generated by the Asset A and B), Key (ID Asset), KeyDate (ID Asset + Date), Rate (cash flow discount rate to calculate NPV) columns and the npv column with the result of the Net Present Value executing the code with the two for
Ejemplo <- structure(list(Date = structure(c(24136, 24165, 24196, 24226,
24257, 24287, 24318, 24349, 24379, 24410, 24440, 24471, 24136,
24165, 24196, 24226, 24257, 24287, 24318, 24349, 24379, 24410,
24440, 24471, 24502, 24530, 24561, 24591, 24622, 24652, 24683,
24714, 24744, 24775, 24805, 24836, 24867, 24895, 24926, 24956,
24987, 25017, 25048, 25079, 25109, 25140, 25170, 25201, 25232,
25260, 25291, 25321, 25352, 25382, 25413, 25444, 25474, 25505,
25535, 25566, 25597, 25626, 25657, 25687, 25718, 25748, 25779,
25810, 25840, 25871, 25901, 25932, 25963, 25991, 26022, 26052,
26083, 26113, 26144, 26175, 26205, 26236, 26266, 26297, 26328,
26356, 26387, 26417, 26448, 26478, 26509, 26540, 26570, 26601,
26631, 26662, 26693, 26721, 26752, 26782, 26813, 26843, 26874,
26905, 26935, 26966, 26996, 27027, 27058, 27087, 27118, 27148,
27179, 27209, 27240, 27271, 27301, 27332, 27362, 27393, 27424,
27452, 27483, 27513, 27544, 27574, 27605, 27636, 27666, 27697,
27727, 27758, 27789, 27817, 27848, 27878, 27909, 27939, 27970,
28001, 28031, 28062, 28092, 28123, 28154, 28182, 28213, 28243,
28274, 28304, 28335, 28366, 28396, 28427, 28457, 28488, 28519,
28548, 28579, 28609, 28640, 28670, 28701, 28732, 28762, 28793,
28823, 28854, 28885, 28913, 28944, 28974, 29005, 29035, 29066,
29097, 29127, 29158, 29188, 29219, 29250, 29278, 29309, 29339,
29370, 29400, 29431, 29462, 29492, 29523, 29553, 29584, 29615
), class = "Date"), Flow = c(626.61225, 626.61225, 626.61225,
626.61225, 626.61225, 626.61225, 626.61225, 626.61225, 626.61225,
626.61225, 626.61225, 147514.77225, 1172.37036865556, 1096.73357067778,
1172.37036865556, 1134.55196966667, 1172.37036865556, 1134.55196966667,
1172.37036865556, 1172.37036865556, 1134.55196966667, 1172.37036865556,
1134.55196966667, 1172.37036865556, 1172.37036865556, 1058.91517168889,
1172.37036865556, 1134.55196966667, 1172.37036865556, 1134.55196966667,
1172.37036865556, 1172.37036865556, 1134.55196966667, 1172.37036865556,
1134.55196966667, 1172.37036865556, 1172.37036865556, 1058.91517168889,
1172.37036865556, 1134.55196966667, 1172.37036865556, 1134.55196966667,
1172.37036865556, 1172.37036865556, 1134.55196966667, 1172.37036865556,
1134.55196966667, 1172.37036865556, 1172.37036865556, 1058.91517168889,
1172.37036865556, 1134.55196966667, 1172.37036865556, 1134.55196966667,
1172.37036865556, 1172.37036865556, 1134.55196966667, 1172.37036865556,
1134.55196966667, 1172.37036865556, 1172.37036865556, 1096.73357067778,
1172.37036865556, 1134.55196966667, 1172.37036865556, 1134.55196966667,
1172.37036865556, 1172.37036865556, 1134.55196966667, 1172.37036865556,
1134.55196966667, 1172.37036865556, 1172.37036865556, 1058.91517168889,
1172.37036865556, 1134.55196966667, 1172.37036865556, 1134.55196966667,
1172.37036865556, 1172.37036865556, 1134.55196966667, 1172.37036865556,
1134.55196966667, 1172.37036865556, 1172.37036865556, 1058.91517168889,
1172.37036865556, 1134.55196966667, 1172.37036865556, 1134.55196966667,
1172.37036865556, 1172.37036865556, 1134.55196966667, 1172.37036865556,
1134.55196966667, 1172.37036865556, 1172.37036865556, 1058.91517168889,
1172.37036865556, 1134.55196966667, 1172.37036865556, 1134.55196966667,
1172.37036865556, 1172.37036865556, 1134.55196966667, 1172.37036865556,
1134.55196966667, 1172.37036865556, 1172.37036865556, 1096.73357067778,
1172.37036865556, 1134.55196966667, 1172.37036865556, 1134.55196966667,
1172.37036865556, 1172.37036865556, 1134.55196966667, 1172.37036865556,
1134.55196966667, 1172.37036865556, 1172.37036865556, 1058.91517168889,
1172.37036865556, 1134.55196966667, 1172.37036865556, 1134.55196966667,
1172.37036865556, 1172.37036865556, 1134.55196966667, 1172.37036865556,
1134.55196966667, 1172.37036865556, 1172.37036865556, 1058.91517168889,
1172.37036865556, 1134.55196966667, 1172.37036865556, 1134.55196966667,
1172.37036865556, 1172.37036865556, 1134.55196966667, 1172.37036865556,
1134.55196966667, 1172.37036865556, 1172.37036865556, 1058.91517168889,
1172.37036865556, 1134.55196966667, 1172.37036865556, 1134.55196966667,
1172.37036865556, 1172.37036865556, 1134.55196966667, 1172.37036865556,
1134.55196966667, 1172.37036865556, 1172.37036865556, 1096.73357067778,
1172.37036865556, 1134.55196966667, 1172.37036865556, 1134.55196966667,
1172.37036865556, 1172.37036865556, 1134.55196966667, 1172.37036865556,
1134.55196966667, 1172.37036865556, 1172.37036865556, 1058.91517168889,
1172.37036865556, 1134.55196966667, 1172.37036865556, 1134.55196966667,
1172.37036865556, 1172.37036865556, 1134.55196966667, 1172.37036865556,
1134.55196966667, 1172.37036865556, 1172.37036865556, 1058.91517168889,
1172.37036865556, 1134.55196966667, 1172.37036865556, 1134.55196966667,
1172.37036865556, 1172.37036865556, 1134.55196966667, 1172.37036865556,
1134.55196966667, 1172.37036865556, 618216.771575733), Key = c("200015B",
"200015B", "200015B", "200015B", "200015B", "200015B", "200015B",
"200015B", "200015B", "200015B", "200015B", "200015B", "200015A",
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"200015A", "200015A", "200015A", "200015A", "200015A", "200015A",
"200015A", "200015A", "200015A", "200015A", "200015A", "200015A",
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"200015A", "200015A", "200015A", "200015A", "200015A", "200015A",
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"200015A", "200015A", "200015A", "200015A", "200015A", "200015A",
"200015A", "200015A", "200015A", "200015A", "200015A", "200015A",
"200015A", "200015A", "200015A", "200015A", "200015A", "200015A",
"200015A", "200015A", "200015A", "200015A", "200015A", "200015A",
"200015A", "200015A", "200015A", "200015A", "200015A", "200015A",
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"200015A", "200015A", "200015A", "200015A", "200015A", "200015A"
), KeyDate = c("200015B2036-01-31", "200015B2036-02-29", "200015B2036-03-31",
"200015B2036-04-30", "200015B2036-05-31", "200015B2036-06-30",
"200015B2036-07-31", "200015B2036-08-31", "200015B2036-09-30",
"200015B2036-10-31", "200015B2036-11-30", "200015B2036-12-31",
"200015A2036-01-31", "200015A2036-02-29", "200015A2036-03-31",
"200015A2036-04-30", "200015A2036-05-31", "200015A2036-06-30",
"200015A2036-07-31", "200015A2036-08-31", "200015A2036-09-30",
"200015A2036-10-31", "200015A2036-11-30", "200015A2036-12-31",
"200015A2037-01-31", "200015A2037-02-28", "200015A2037-03-31",
"200015A2037-04-30", "200015A2037-05-31", "200015A2037-06-30",
"200015A2037-07-31", "200015A2037-08-31", "200015A2037-09-30",
"200015A2037-10-31", "200015A2037-11-30", "200015A2037-12-31",
"200015A2038-01-31", "200015A2038-02-28", "200015A2038-03-31",
"200015A2038-04-30", "200015A2038-05-31", "200015A2038-06-30",
"200015A2038-07-31", "200015A2038-08-31", "200015A2038-09-30",
"200015A2038-10-31", "200015A2038-11-30", "200015A2038-12-31",
"200015A2039-01-31", "200015A2039-02-28", "200015A2039-03-31",
"200015A2039-04-30", "200015A2039-05-31", "200015A2039-06-30",
"200015A2039-07-31", "200015A2039-08-31", "200015A2039-09-30",
"200015A2039-10-31", "200015A2039-11-30", "200015A2039-12-31",
"200015A2040-01-31", "200015A2040-02-29", "200015A2040-03-31",
"200015A2040-04-30", "200015A2040-05-31", "200015A2040-06-30",
"200015A2040-07-31", "200015A2040-08-31", "200015A2040-09-30",
"200015A2040-10-31", "200015A2040-11-30", "200015A2040-12-31",
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"200015A2041-07-31", "200015A2041-08-31", "200015A2041-09-30",
"200015A2041-10-31", "200015A2041-11-30", "200015A2041-12-31",
"200015A2042-01-31", "200015A2042-02-28", "200015A2042-03-31",
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"200015A2042-10-31", "200015A2042-11-30", "200015A2042-12-31",
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"200015A2050-10-31", "200015A2050-11-30", "200015A2050-12-31",
"200015A2051-01-31"), Rate = c(0.00145610800020436, 0.00145610800020436,
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0.00183862716675229, 0.00189991473897737, 0.00183862716675229,
0.00189991473897737, 0.00147090173340183), npv = c(151794.327418487,
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Here you have a web with an explanation about the Net present value:
Solution 1:[1]
This is still complicated. So far, I think this is the way it is supposed to be
df_Ejemplo %>%
group_by(Key) %>%
mutate(
npv = sum(dcf(x=Flow, Rate))
) ->
df_Ejemplo
> all.equal(df_Ejemplo$npv, Ejemplo$npv)
[1] "Mean relative difference: 0.003511715"
But it disagrees with the result.
Sources
This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.
Source: Stack Overflow
| Solution | Source |
|---|---|
| Solution 1 | Mossa |