def main():
# Test case: Test the ABS model with a single process and 1500 loans on pro rata mode
# Assets are from 'Loans.csv'
# Liabilities:
# tranches.addTranche('StandardTranche', '0.8', '0.05', '1')
# tranches.addTranche('StandardTranche', '0.2', '0.08', '2')
# Run the Waterfall 1 time to get a CSV output of the transactions
# on 'liabilities_prorata_1500loans.csv'
###############################################
# Set logging level
logging.getLogger().setLevel(logging.DEBUG)
###############################################
loans1500 = LoanPool(
loansImportCSV('MA4176_31418DUA8_COLLAT_ISSUANCE.csv'))
tranches = StructuredSecurities(loans1500.totalPrincipal())
tranches.addTranche('StandardTranche', '0.5', '0.02500', '1')
tranches.addTranche('StandardTranche', '0.5', '0.03125', '2')
print(f'Pro Rata mode:')
tranches.setMode('Pro Rata')
ledger, tranchesMetrics = simulateWaterfall(loans1500, tranches, 1)
spvExportCSV(ledger, 'liabilities_prorata_FannieMaeData.csv')
for tranche in tranches.tranches:
print(f'{tranche}\n'
f' IRR = {tranche.r}\n'
f' DIRR = {tranche.dirr}\n'
f' DIRR(letter) = {tranche.dirrLetter}\n'
f' AL = {tranche.al}')
def main():
# Test case: Test the ABS model with a single process and 1500 loans on sequential mode
# Assets are from 'Loans.csv'
# Liabilities:
# tranches.addTranche('StandardTranche', '0.8', '0.05', '1')
# tranches.addTranche('StandardTranche', '0.2', '0.08', '2')
# Run the Waterfall 1 time to get a CSV output of the transactions
# on 'liabilities_sequential_1500loans.csv'
###############################################
# Set logging level
logging.getLogger().setLevel(logging.DEBUG)
###############################################
loans1500 = LoanPool(loansImportCSV('Loans.csv'))
tranches = StructuredSecurities(loans1500.totalPrincipal())
tranches.addTranche('StandardTranche', '0.8', '0.05', '1')
tranches.addTranche('StandardTranche', '0.2', '0.08', '2')
tranches.setMode('Sequential')
ledger, tranchesMetrics = simulateWaterfall(loans1500, tranches, 1)
spvExportCSV(ledger, 'liabilities_sequential_1500loans.csv')
for tranche in tranches.tranches:
print(f'{tranche}\n'
f' IRR = {tranche.r}\n'
f' DIRR = {tranche.dirr}\n'
f' DIRR(letter) = {tranche.dirrLetter}\n'
f' AL = {tranche.al}')
def main():
# Test case: Test the ABS model with Monte Carlo on 1500 loans, on multiprocessing, sequential mode
# Assets are from Loans.csv
# Liabilities: originally start with these below tranches
# tranches.addTranche('StandardTranche', '0.8', '0.05', '1')
# tranches.addTranche('StandardTranche', '0.2', '0.08', '2')
# Optimize tranches' rates based on a yield curve to get diff = 50 bps or less.
# Print optimized rate on screen and run the Waterfall 1 time to get a CSV output of the transactions
# on 'liabilities_sequential_montecarlo_multiprocessing_1500loans.csv'
###############################################
# Set logging level
logging.getLogger().setLevel(logging.DEBUG)
random.seed(1)
###############################################
loansFannie = LoanPool(
loansImportCSV('MA4176_31418DUA8_COLLAT_ISSUANCE.csv'))
tranches = StructuredSecurities(loansFannie.totalPrincipal())
tranches.addTranche('StandardTranche', '0.5', '0.02500', '1')
tranches.addTranche('StandardTranche', '0.5', '0.03125', '2')
tranches.setMode('Sequential')
newTrancheRate = runMonte(loansFannie, tranches, 0.005, 2000, 20)
print(f'My new tranche rate is = {newTrancheRate}')
# Run the Waterfall once to generate CSV output of transactions.
tranches = StructuredSecurities(loansFannie.totalPrincipal())
tranches.addTranche('StandardTranche', '0.5', newTrancheRate[0], '1')
tranches.addTranche('StandardTranche', '0.5', newTrancheRate[1], '2')
tranches.setMode('Sequential')
ledger, tranchesMetrics = simulateWaterfall(loansFannie, tranches, 1)
spvExportCSV(
ledger,
'liabilities_sequential_montecarlo_multiprocessing_FannieMae.csv')
for tranche in tranches.tranches:
print(f'{tranche}\n'
f' IRR = {tranche.r}\n'
f' DIRR = {tranche.dirr}\n'
f' DIRR(letter) = {tranche.dirrLetter}\n'
f' AL = {tranche.al}')
def main():
# Test case: Test the ABS model with Monte Carlo on 1500 loans on single process, pro rata mode
# Assets are from Loans.csv
# Liabilities: originally start with these below tranches
# tranches.addTranche('StandardTranche', '0.8', '0.05', '1')
# tranches.addTranche('StandardTranche', '0.2', '0.08', '2')
# nsim = 10
# numProcesses = 1
# Optimize tranches' rates based on a yield curve to get diff = 1000 bps or less.
# Print optimized rate on screen and run the Waterfall 1 time to get a CSV output of the transactions
# on 'liabilities_prorata_montecarlo_singleprocess_1500loans.csv'
###############################################
# Set logging level
logging.getLogger().setLevel(logging.DEBUG)
###############################################
loans1500 = LoanPool(loansImportCSV('Loans.csv'))
tranches = StructuredSecurities(loans1500.totalPrincipal())
tranches.addTranche('StandardTranche', '0.8', '0.05', '1')
tranches.addTranche('StandardTranche', '0.2', '0.08', '2')
tranches.setMode('Pro Rata')
newTrancheRate = runMonte(loans1500, tranches, 0.1, 10, 1)
print(f'My new tranche rate is = {newTrancheRate}')
# Run the Waterfall once to generate CSV output of transactions.
tranches = StructuredSecurities(loans1500.totalPrincipal())
tranches.addTranche('StandardTranche', '0.8', newTrancheRate[0], '1')
tranches.addTranche('StandardTranche', '0.2', newTrancheRate[1], '2')
tranches.setMode('Pro Rata')
ledger, tranchesMetrics = simulateWaterfall(loans1500, tranches, 1)
spvExportCSV(ledger, 'liabilities_prorata_montecarlo_singleprocess_1500loans.csv')
for tranche in tranches.tranches:
print(f'{tranche}\n'
f' IRR = {tranche.r}\n'
f' DIRR = {tranche.dirr}\n'
f' DIRR(letter) = {tranche.dirrLetter}\n'
f' AL = {tranche.al}')