Developing a custom function of loops for forecasting any loan - r

Question

Dear all,
I have written a simple function that takes inputs of a typical loan and forecasts the loan until the end of the Term, and saves all data as Time Series in a dataframe.
Inputs: R (interest rate), start (start of the loan), CMP (monthly payment), Term (how long is the loan contract), Bal0 (as default loan amount), frequency (how often is interest calculated, if 365 then daily), and months (how many months in a year).
Typical behaviour of a loan is as follows: Take out a loan, Bal0 = £1000 on start= 2022.01.20 with interest of R = 10%, CMP= £100, Term= 1 year. Daily Interest (R/365) will start counting on the following day (2022.01.21) until end of Term, calculated on previous day's closing balance.
After a precise calendar month on the 2022.02.20, the Loan Balance of £1000 will get added the cumulative daily interest over the calendar month and get the monthly payment deducted. Such that on that day the Closing Balance = £1000 + (the sum of all interests over the past month= sum(Closing_Balance*R/365)=) £0.2739 - the monthly payment (CMP) £100=
1000+0.2739-100= £900.27.
Then the daily interest starts counting on now the lower balance of £900.27. Until, again, in a precise calendar month, 2022.03.20. the same will happen: Closing Balance = £900.27 + (sum of all interests)-£100.
#Loading all packages.#
library(zoo)
library(lubridate)
library(timetk)
#Importing Data.#
data<- structure(list(Key = c(281575989162.667, 281576178390.667, 281576180153.333,
281576278448, 281576311669.333, 281576312741.333, 281576399669.333, 281576403989.333,
281576418453.333, 281576513364, 281576518421.333, 281576520128, 294909322496, 294909511724,
294909513486.667, 294909611781.333, 294909645002.667, 294909646074.667, 294909733002.667, 294909737322.667,
294909751786.667, 294909846697.333, 294909851754.667, 294909853461.333), start = structure(c(1637539200, 1637539200,
1637539200, 1637539200, 1637539200, 1637539200, 1637539200, 1637539200, 1637539200, 1637539200, 1637539200, 1637539200,
1637539200, 1637539200, 1637539200, 1637539200, 1637539200, 1637539200, 1637539200, 1637539200, 1637539200, 1637539200, 1637539200,
1637539200), class = c("POSIXct", "POSIXt"), tzone = "UTC"), CMP = c(94.32, 117.7, 246.5, 94.32, 117.7, 246.5, 94.32, 117.7, 246.5, 94.32,
117.7, 246.5, 94.32, 117.7, 246.5, 94.32, 117.7, 246.5, 94.32, 117.7, 246.5, 94.32, 117.7, 246.5), R = c(0.23497, 0.21294, 0.1485, 0.23497, 0.21294, 0.1485,
0.23497, 0.21294, 0.1485, 0.23497, 0.21294, 0.1485, 0.23497, 0.21294, 0.1485, 0.23497, 0.21294, 0.1485, 0.23497, 0.21294, 0.1485, 0.23497, 0.21294, 0.1485),
Term = c(12, 18, 36, 12, 18, 36, 12, 18, 36, 12, 18, 36, 12, 18, 36, 12, 18, 36, 12, 18, 36, 12, 18, 36), Bal0 = c(1000, 1800, 7126, 1000, 1800, 7126, 1000,
1800, 7126, 1000, 1800, 7126, 1000, 1800, 7126, 1000, 1800, 7126, 1000, 1800, 7126, 1000, 1800, 7126)), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, -24L))
#Writing loan amortization function.#
loan_amort <- function (R, start, CMP, Term, Bal0, frequency = 365,months = 12) {
answer = df() #Save all answers in a dataframe#
periods = Term * frequency #How many interest counting periods we have#
daily_interest = R / frequency #Daily interest for each loan#
nmonths = Term * months #For how many months loan x is for#
#For each day, function calculates the closing_balance. For the first day, closing_balance = original loan amount. Monthly_CMP is applied only after one calendar month after the start of the loan for all remaining months, and the monthly_interest is the sum of all interests each single day in that calendar month.#
for (p in 1:periods) {
closing_balance = (opening_balance – monthly_CMP + monthly_interest)
if (Date == start) {
opening_balance = Bal0
} else {
opening_balance = lag(closing_balance)
}
}
#The monthly_CMP is CMP, but gets applied only once per calendar month after start.#
for(m in 1:nmonths){
if (Date == (ymd(start) %m+% months(m)) {
monthly_CMP = CMP
} else {
monthly_CMP = 0
}
#The monthly_interest is the sum of all daily interests (lag(closing_balance) * R/365, but gets applied only once per calendar month after start.#
if (Date == (ymd(start) %m+% months(m)) {
monthly_interest = summarise_by_time(interest, .by = "month", .type = "round")
} else {
monthly_interest = 0
}
}
#If the Date is a calendar month away from start, apply the sum of all daily interests that are calculated on each days' closing_balance. If it's not a calendar month away, keep calculating the interest, but the monthly_interests remains 0 until that monthly settlement date.#
interest = daily_interest * lag(closing_balance)
#Then save closing_balance as a zooreg timeseries, where we are saving the closing_balance starting on the start date of the loan and it's saved in daily frequency.#
closing_balance = zooreg(closing_balance, start, frequency = frequency)
}
#Save all columns to a dataframe with all of these aspects#
answer$closing_balance = closing_balance
answer$opening_balance = opening_balance
answer$monthly_CMP = monthly_CMP
answer$monthly_interest = monthly_interest
answer$interest = interest
return(answer)
}
Could anyone help me out with this function, please? The output says it cannot find any of my variables in the function, including: Date, unexpected errors "m in 1:nmonths", object CMP not found, error in recognising loops on "for (p in 1:periods)", daily_interest not found, closing_balance not found, opening_balance not found, object "answer" not found, interest not found.
Hence, would anyone have better ideas on how to specify this function or write loops and saving output as a timeseries (in my case zooreg), or is it better to completely rewrite the whole script?
Any advice would be very appreciated,
thank you.