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Function for determining how long an optimal Debt Snowball will take to pay off. Takes only current principals and interest rates. Does not take minimum payments or account for compounding.
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loanData <- data.frame( | |
description = c( | |
'1-03 Direct Loan - Unsubsidized', | |
'1-02 Direct Loan - Subsidized', | |
'Direct Unsubsidized Stafford', | |
'Direct Unsubsidized Stafford', | |
'1-01 Direct Loan - Unsubsidized', | |
'Direct Unsubsidized Stafford', | |
'Direct Subsidized Stafford', | |
'Direct Unsubsidized Stafford', | |
'Direct Subsidized Stafford', | |
'Direct Subsidized Stafford', | |
'1-04 Direct Loan - Unsubsidized', | |
'Direct Unsubsidized Stafford', | |
'Federal Perkins Loan', | |
'Direct Grad PLUS', | |
'Direct Unsubsidized Stafford', | |
'Direct Unsubsidized Stafford' ), | |
token = c( | |
3, | |
2, | |
129, | |
126, | |
1, | |
124, | |
123, | |
130, | |
125, | |
128, | |
4, # | |
127, | |
0, | |
132, | |
133, | |
131 ), | |
group = c( | |
'navient', | |
'navient', | |
'stafford', | |
'stafford', | |
'navient', | |
'stafford', | |
'stafford', | |
'stafford', | |
'stafford', | |
'stafford', | |
'navient', | |
'stafford', | |
'perkins_loan', | |
'grad_plus', | |
'stafford', | |
'stafford' ), | |
principal = c( | |
0, # 3 | |
1047.14, # 2 | |
2035.85, # 129 | |
0, # 126 | |
0, # 1 | |
0, # 124 | |
5103.08, # 123 | |
5072.45, # 130 | |
5190.13, # 125 | |
5213.86, # 128 | |
4724.67, # 4 | |
0, # 127 | |
3234.80, # 0 | |
0, # 132 | |
20284.95, # 133 | |
6731.86 # 131 | |
), | |
rate = c( | |
0.06550, | |
0.03150, | |
0.03610, | |
0.06550, | |
0.06550, | |
0.06550, | |
0.03150, | |
0.03610, | |
0.03150, | |
0.03610, | |
0.03610, | |
0.06550, | |
0.05000, | |
0.06960, | |
0.05590, | |
0.05960 ) ) | |
loanData <- loanData[order(-loanData$rate,-loanData$principal),] | |
debtSnowball <- function( loanData, monthlyPayment, | |
iterations = Inf, daysInMonth = 30, startingMonth = 1, | |
monthlyPaymentCushion = 1 ) | |
{ | |
paidAmounts <- list( interest = 0, originalPrincipal = loanData$principal, | |
principal = 0, total = 0, payments = integer( nrow(loanData) ), | |
years = integer( nrow(loanData) ), allocation = list() ) | |
# loanData <- loanData[order(loanData$principal),] | |
while ( sum( loanData$principal ) > 0 && sum( paidAmounts$payments ) < iterations ) | |
{ | |
# Calculate daily interest | |
loanData$dailyInterest <- with( loanData, principal * rate / 365.242199 ) | |
# Calculate monthly interest | |
loanData$monthlyInterest <- with( loanData, dailyInterest * daysInMonth ) | |
# Calculate total balance | |
loanData$balance <- with( loanData, principal + monthlyInterest ) | |
# Calculate min payment | |
# Simplified to $1 more than the monthly interest | |
loanData$minPayment <- with( loanData, | |
ifelse( monthlyInterest + monthlyPaymentCushion > balance, | |
balance, monthlyInterest + monthlyPaymentCushion ) ) | |
# Sanity check | |
if ( sum( loanData$minPayment ) > monthlyPayment ) | |
stop( "Monthly payment must be greater than all minimum payments" ) | |
# Initialize ACTUAL payments | |
loanData$actualPayment <- sapply( rownames(loanData), function( l ) | |
{ | |
min( loanData[l,c('balance','minPayment')] ) | |
} ) | |
# Calculate Sum of Actual Payments to be applied | |
calculateSAP <- function() { SAP <<- sum( loanData$actualPayment ) } | |
calculateSAP() | |
# Calculate ACTUAL payment | |
for ( l in 1:nrow(loanData) ) | |
{ | |
if ( loanData[l,'balance'] > 0 ) | |
{ | |
loanData[l,'actualPayment'] <- min( loanData[l,'balance'], | |
loanData[l,'actualPayment'] + (monthlyPayment - SAP) ) | |
calculateSAP() | |
# Allocate the rest of the monthly budget | |
if ( SAP <= 0 ) | |
break | |
} | |
} | |
# APPLY the payment and update totals | |
paidAmounts$interest <- round( paidAmounts$interest + loanData$monthlyInterest, 2 ) | |
paidAmounts$principal <- round( paidAmounts$principal + | |
( loanData$actualPayment - loanData$monthlyInterest ), 2 ) | |
paidAmounts$total <- round( paidAmounts$total + loanData$actualPayment, 2 ) | |
snowballLoan <- min( which( loanData$principal > 0 ) ) | |
paidAmounts$payments[snowballLoan] <- paidAmounts$payments[snowballLoan] + 1 | |
paidAmounts$years[snowballLoan] <- round( | |
paidAmounts$payments[snowballLoan] * daysInMonth / 365, 2 ) | |
paidAmounts$allocation[[sum(paidAmounts$payments)]] <- loanData | |
loanData$principal <- with( loanData, (principal + monthlyInterest) - actualPayment ) | |
} | |
return( paidAmounts ) | |
} | |
dS <- function( data = loanData, ... ) | |
{ | |
test <<- debtSnowball( loanData = data, ... ) | |
test.1 <<- test$allocation[[1]] | |
output <- as.data.frame( test[-length(test)] ) | |
output <- rbind( output, sapply( test[-length(test)], sum ) ) | |
rownames(output)[nrow(output)] <- "Totals" | |
return( output ) | |
} | |
dS( monthlyPayment = 1062.78, monthlyPaymentCushion = 0 ) | |
aggregate( . ~ group, test.1, sum ) | |
test.1[test.1$group == 'navient',] | |
sapply( test.1[-(1:3)], sum ) | |
sum(test.1[test.1$group %in% c('grad_plus','stafford'),'actualPayment']) |
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Debt Snowball Pseudocode
data = loan balances, interest rates
Create a function that iterates through
monthly payments with inputs:
and outputs:
If combined minimum payments >
monthly payment amount, throw error
While balances on any loans > 0:
{
if remaining balance == 0:
quit loop
else if remaining balance greater than 0:
if remaining balance less than min payment:
actual payment = remaining balance
else actual payment = min payment
else ignore
actual payments to be applied (SAP)
if remaining balance == 0:
next
else: set actual payment to
previous actual payment +
total monthly payment - SAP
actual monthly payment
}
return all of our values