def add_transaction(self, type_, asset, from_id, to_id, amount, interest, maturity, time_of_default):
from src.transaction import Transaction
transaction = Transaction()
transaction.this_transaction(type_, asset, from_id, to_id, amount, interest, maturity, time_of_default)
self.accounts.append(transaction)
del transaction # append() above does make a copy so we may delete for garbage collection
def add_transaction(self, type_, asset, from_id, to_id, amount, interest,
maturity, time_of_default, environment):
from src.transaction import Transaction
transaction = Transaction()
transaction.this_transaction(type_, asset, from_id, to_id, amount,
interest, maturity, time_of_default)
transaction.add_transaction(environment)
def make_deposits(self, environment, time):
for household in environment.households:
cash = 0.0 # total of cash available for the household
control_deposits = 0 # checking if the household already has deposits
# We calculate the available cash
for tranx in household.accounts:
if tranx.type_ == "cash":
cash = cash + tranx.amount
tranx.amount = 0
# And the number of existing deposits
if tranx.type_ == "deposits":
control_deposits = control_deposits + 1
# And move all available cash to deposits at the end of the step
# If there are no deposits we create one in a bank
# The bank is chosen randomly
if control_deposits == 0:
# We choose a bank randomly
random_bank = random.choice(environment.banks)
# Create a transaction
transaction = Transaction()
# Add the appropriate values to the transaction
transaction.this_transaction("deposits", "", household.identifier, random_bank,
amount, random_bank.interest_rate_deposits, 0, -1)
# And add the transaction to the books (do it through function/not manually)
transaction.add_transaction(environment)
# If there are previous deposits we expand them linearly
else:
for tranx in household.accounts:
if tranx.type_ == "deposits":
# We add the remaining cash to the existing deposits
# in equal proportions
# Perhaps this can be done proportionate with regards
# to the value of these deposits, but it's minor at this point
tranx.amount = tranx.amount + (cash/control_deposits)
logging.info(" deposits made on step: %s", time)
def endow_labour(self, environment, time):
# We make sure household get their labour endowment per step
for household in environment.households:
# First, we set a control variable that makes sure we have exactly
# one transaction with "manhours", though this should in general
# be the case, this should always run through the second if
check = 0
for tranx in household.accounts:
if tranx.type_ == "manhours":
check = check + 1 # We check how many transactions with manhours are there for the household
# If there are no "manhours" transactions then we create one and add it to the household's accounts
if check == 0:
# The amount is equal to the parameter read from the config of the household
amount = household.labour
# We create the transaction
transaction = Transaction()
# We add the appropriate values to the transaction
transaction.this_transaction("manhours", "",
household.identifier,
household.identifier, amount, 0,
0, -1)
# It's important to add the transaction using the method
# from Transaction class and not manually
transaction.add_transaction(environment)
else:
# If we have more than one "mahhours" transaction we raise an error
raise LookupError(
"Labour transactions for a household haven't been properly removed."
)
logging.info(" labour endowed on step: %s", time)
def endow_labour(self, environment, time):
# We make sure household get their labour endowment per step
for household in environment.households:
# First, we set a control variable that makes sure we have exactly
# one transaction with "manhours", though this should in general
# be the case, this should always run through the second if
check = 0
for tranx in household.accounts:
if tranx.type_ == "manhours":
check = check + 1 # We check how many transactions with manhours are there for the household
# If there are no "manhours" transactions then we create one and add it to the household's accounts
if check == 0:
# The amount is equal to the parameter read from the config of the household
amount = household.labour
# We create the transaction
transaction = Transaction()
# We add the appropriate values to the transaction
transaction.this_transaction("manhours", "", household.identifier, household.identifier, amount, 0, 0, -1)
# It's important to add the transaction using the method
# from Transaction class and not manually
transaction.add_transaction(environment)
else:
# If we have more than one "mahhours" transaction we raise an error
raise LookupError("Labour transactions for a household haven't been properly removed.")
logging.info(" labour endowed on step: %s", time)
def new_transaction(self, type_, asset, from_, to, amount, interest,
maturity, time_of_default):
from src.transaction import Transaction
transaction = Transaction()
transaction.this_transaction(type_, asset, from_, to, amount, interest,
maturity, time_of_default)
transaction.add_transaction(self)
def transfer_required_deposits(self):
transaction = Transaction()
value = round(float(self.r * self.get_account("D")), 4)
transaction.this_transaction("rD", self.identifier, -3, value, self.rb, 0, -1)
self.accounts.append(transaction)
return -1.0 * value
def add_transaction(self, type_, asset, from_id, to_id, amount, interest,
maturity, time_of_default):
from src.transaction import Transaction
transaction = Transaction()
transaction.this_transaction(type_, asset, from_id, to_id, amount,
interest, maturity, time_of_default)
self.accounts.append(transaction)
del transaction # append() above does make a copy so we may delete for garbage collection
def transaction__add_transaction(self, args):
import os
from src.bank import Bank
from src.household import Household
from src.firm import Firm
from src.environment import Environment
from src.transaction import Transaction
text = "This test checks transaction.add_transaction \n"
self.print_info(text)
#
# INITIALIZATION
#
environment_directory = str(args[0])
identifier = str(args[1])
log_directory = str(args[2])
# Configure logging parameters so we get output while the program runs
logging.basicConfig(format='%(asctime)s %(message)s', datefmt='%m/%d/%Y %H:%M:%S',
filename=log_directory + identifier + ".log", level=logging.INFO)
logging.info('START logging for test transaction__add_transaction in run: %s',
environment_directory + identifier + ".xml")
# Construct household filename
environment = Environment(environment_directory, identifier)
# generate a bank
bank = Bank()
bank.identifier = "test_bank"
environment.banks.append(bank)
# generate a firm
firm = Firm()
firm.identifier = "test_firm"
environment.firms.append(firm)
# generate a household
household = Household()
household.identifier = "test_household"
environment.households.append(household)
#
# TESTING
#
print("Creating a transaction")
transaction = Transaction()
print("Assigning values")
transaction.this_transaction("type", "asset", "test_household", "test_firm", 1, 2, 3, 4)
print("Adding the transaction to the books")
transaction.add_transaction(environment)
print("The transaction:")
print(transaction)
print("The firm:")
print(environment.get_agent_by_id("test_firm"))
print("The household:")
print(environment.get_agent_by_id("test_household"))
def transfer_required_deposits(self):
from src.transaction import Transaction
transaction = Transaction()
value = round(float(self.parameters["r"]*self.get_account("D")), 4)
transaction.this_transaction("rD", self.identifier, -3, value, self.parameters["rb"], 0, -1)
self.accounts.append(transaction)
return -1.0*value
def transfer_excess_reserves(self):
availableVolume = self.Q
plannedVolume = self.gamma * (1.0 - self.lamb) * self.V
transactionVolume = round(min(plannedVolume, availableVolume), 4)
self.Q = round(self.Q - transactionVolume, 4)
if self.Q < 0.0:
logging.info("ERROR: Q negative in transfer_excess_reserves")
transaction = Transaction()
transaction.this_transaction("E", self.identifier, -3, transactionVolume, self.rb, 0, -1)
self.accounts.append(transaction)
del transaction
def transfer_excess_reserves(self):
from src.transaction import Transaction
availableVolume = self.parameters["Q"]
plannedVolume = self.parameters["gamma"]*(1.0-self.parameters["lamb"])*self.parameters["V"]
transactionVolume = round(min(plannedVolume, availableVolume), 4)
self.parameters["Q"] = round(self.parameters["Q"] - transactionVolume, 4)
if (self.parameters["Q"] < 0.0):
logging.info("ERROR: Q negative in transfer_excess_reserves")
transaction = Transaction()
transaction.this_transaction("E", self.identifier, -3, transactionVolume, self.parameters["rb"], 0, -1)
self.accounts.append(transaction)
del transaction
def initialize_standard_bank(self, bank, environment):
from src.transaction import Transaction
bank.identifier = "standard_bank_id"
# deposits - we get the first household from the list of households
# if there are no households it will be a blank which is fine for testing
amount = 250.0
transaction = Transaction()
transaction.this_transaction("deposits", "", environment.households[0].identifier, bank.identifier,
amount, bank.interest_rate_deposits, 0, -1)
# environment.households[0] is only for testing purposes DO NOT USE IN PRODUCTION
transaction.add_transaction(environment)
# money - cash and equivalents
amount = 100.0
transaction = Transaction()
transaction.this_transaction("cash", "", bank.identifier, bank.identifier,
amount, 0, 0, -1)
transaction.add_transaction(environment)
# loans - we get the first firm from the list of firms
# if there are no firms it will be a blank which is fine for testing
amount = 150.0
transaction = Transaction()
transaction.this_transaction("loans", "", bank.identifier, environment.firms[0].identifier,
amount, bank.interest_rate_loans, 0, -1)
# environment.firms[0] is only for testing purposes DO NOT USE IN PRODUCTION
transaction.add_transaction(environment)
def initialize_standard_household(self, household, environment):
from src.transaction import Transaction
household.identifier = "standard_household_id" # identifier
household.parameters["labour"] = 24.00 # labour to sell per step
household.parameters["propensity_to_save"] = 0.40 # propensity to save
# percentage of income household wants to save as deposits
# deposits - we get the first bank from the list of banks
# if there are no banks it will be a blank which is fine for testing
amount = 200.0
transaction = Transaction()
transaction.this_transaction("deposits", "", household.identifier, environment.banks[0].identifier,
amount, environment.banks[0].interest_rate_deposits, 0, -1)
# environment.banks[0] is only for testing purposes DO NOT USE IN PRODUCTION
transaction.add_transaction(environment)
# money - cash and equivalents
amount = 50.0
transaction = Transaction()
transaction.this_transaction("cash", "", household.identifier, household.identifier, amount, 0, 0, -1)
transaction.add_transaction(environment)
# manhours - labour to sell
amount = 250.0
transaction = Transaction()
transaction.this_transaction("manhours", "", household.identifier, household.identifier, amount, 0, 0, -1)
transaction.add_transaction(environment)
def initialize_standard_bank(self, bank, environment):
from src.transaction import Transaction
bank.identifier = "standard_bank_id"
# deposits - we get the first household from the list of households
# if there are no households it will be a blank which is fine for testing
amount = 250.0
transaction = Transaction()
transaction.this_transaction("deposits", "", environment.households[0:1][0], bank.identifier,
amount, bank.interest_rate_deposits, 0, -1)
# environment.households[0:1][0] is only for testing purposes DO NOT USE IN PRODUCTION
# what it does is is takes the first household in environment, but if there are no
# households (which happens in testing) it doesn't break down
bank.accounts.append(transaction)
# money - cash and equivalents
amount = 100.0
transaction = Transaction()
transaction.this_transaction("cash", "", bank.identifier, bank.identifier,
amount, 0, 0, -1)
bank.accounts.append(transaction)
# loans - we get the first firm from the list of firms
# if there are no firms it will be a blank which is fine for testing
amount = 150.0
transaction = Transaction()
transaction.this_transaction("loans", "", bank.identifier, environment.firms[0:1][0],
amount, bank.interest_rate_loans, 0, -1)
# environment.firms[0:1][0] is only for testing purposes DO NOT USE IN PRODUCTION
# what it does is is takes the first firm in environment, but if there are no
# firms (which happens in testing) it doesn't break down
bank.accounts.append(transaction)
def initialize_standard_bank(self, bank, environment):
from src.transaction import Transaction
bank.identifier = "standard_bank_id"
# deposits - we get the first household from the list of households
# if there are no households it will be a blank which is fine for testing
amount = 250.0
transaction = Transaction()
transaction.this_transaction("deposits", "",
environment.households[0].identifier,
bank.identifier, amount,
bank.interest_rate_deposits, 0, -1)
# environment.households[0] is only for testing purposes DO NOT USE IN PRODUCTION
transaction.add_transaction(environment)
# money - cash and equivalents
amount = 100.0
transaction = Transaction()
transaction.this_transaction("cash", "", bank.identifier,
bank.identifier, amount, 0, 0, -1)
transaction.add_transaction(environment)
# loans - we get the first firm from the list of firms
# if there are no firms it will be a blank which is fine for testing
amount = 150.0
transaction = Transaction()
transaction.this_transaction("loans", "", bank.identifier,
environment.firms[0].identifier, amount,
bank.interest_rate_loans, 0, -1)
# environment.firms[0] is only for testing purposes DO NOT USE IN PRODUCTION
transaction.add_transaction(environment)
def initialize_standard_firm(self, firm, environment):
from src.transaction import Transaction
firm.identifier = "standard_firm_id" # identifier
firm.parameters["productivity"] = 1.20 # how much goods do we get from 1 unit of labour
# loans - we get the first bank from the list of banks
# if there are no banks it will be a blank which is fine for testing
amount = 250.0
transaction = Transaction()
transaction.this_transaction(
"loans",
"",
environment.banks[0].identifier,
firm.identifier,
amount,
environment.banks[0].interest_rate_loans,
0,
-1,
)
# environment.banks[0] is only for testing purposes DO NOT USE IN PRODUCTION
transaction.add_transaction(environment)
# money - cash and equivalents
amount = 200.0
transaction = Transaction()
transaction.this_transaction("cash", "", firm.identifier, firm.identifier, amount, 0, 0, -1)
transaction.add_transaction(environment)
# goods - unique production
amount = 50.0
transaction = Transaction()
transaction.this_transaction("goods", "", firm.identifier, firm.identifier, amount, 0, 0, -1)
transaction.add_transaction(environment)
def initialize_standard_household(self, household, environment):
from src.transaction import Transaction
household.identifier = "standard_household_id" # identifier
household.parameters["labour"] = 24.00 # labour to sell per step
household.parameters["propensity_to_save"] = 0.40 # propensity to save
# percentage of income household wants to save as deposits
# deposits - we get the first bank from the list of banks
# if there are no banks it will be a blank which is fine for testing
amount = 200.0
transaction = Transaction()
transaction.this_transaction(
"deposits", "", household.identifier, environment.banks[0:1][0],
amount, environment.banks[0:1][0].interest_rate_deposits, 0, -1)
# environment.banks[0:1][0] is only for testing purposes DO NOT USE IN PRODUCTION
# what it does is is takes the first bank in environment, but if there are no
# banks (which happens in testing) it doesn't break down
household.accounts.append(transaction)
# money - cash and equivalents
amount = 50.0
transaction = Transaction()
transaction.this_transaction("cash", "", household.identifier,
household.identifier, amount, 0, 0, -1)
household.accounts.append(transaction)
# manhours - labour to sell
amount = 250.0
transaction = Transaction()
transaction.this_transaction("manhours", "", household.identifier,
household.identifier, amount, 0, 0, -1)
household.accounts.append(transaction)
def initialize_standard_firm(self, firm, environment):
from src.transaction import Transaction
firm.identifier = "standard_firm_id" # identifier
firm.parameters[
"productivity"] = 1.20 # how much goods do we get from 1 unit of labour
# loans - we get the first bank from the list of banks
# if there are no banks it will be a blank which is fine for testing
amount = 250.0
transaction = Transaction()
transaction.this_transaction(
"loans", "", environment.banks[0:1][0], firm.identifier, amount,
environment.banks[0:1][0].interest_rate_loans, 0, -1)
# environment.banks[0:1][0] is only for testing purposes DO NOT USE IN PRODUCTION
# what it does is is takes the first bank in environment, but if there are no
# banks (which happens in testing) it doesn't break down
firm.accounts.append(transaction)
# money - cash and equivalents
amount = 200.0
transaction = Transaction()
transaction.this_transaction("cash", "", firm.identifier,
firm.identifier, amount, 0, 0, -1)
firm.accounts.append(transaction)
# goods - unique production
amount = 50.0
transaction = Transaction()
transaction.this_transaction("goods", "", firm.identifier,
firm.identifier, amount, 0, 0, -1)
firm.accounts.append(transaction)
def produce(self, environment, time):
# We take all the labour and turn it into goods
for firm in environment.firms: # We do it for every firm
production_factors = 0 # Here, we count how much labour the firm has
for tranx in firm.accounts:
if tranx.type_ == "manhours":
# We move the labour to production as a production factor
# First, we move it to production factors used below
# Then we will remove it from the books
production_factors = production_factors + tranx.amount
# Amount produced is labour * productivity in this simple model
amount = production_factors * firm.productivity
# Create a transaction
transaction = Transaction()
# Add the appropriate values to the transaction
transaction.this_transaction("goods", "", firm.identifier,
firm.identifier, amount, 0, 0, -1)
# And add the transaction to the books (do it through function/not manually)
transaction.add_transaction(environment)
# Finally, we remove all the labour that was used in production
# from the books of the firms
self.remove_labour_firms(environment, time)
logging.info(" goods produced on step: %s", time)
def produce(self, environment, time):
# We take all the labour and turn it into goods
for firm in environment.firms: # We do it for every firm
production_factors = 0 # Here, we count how much labour the firm has
for tranx in firm.accounts:
if tranx.type_ == "manhours":
# We move the labour to production as a production factor
# First, we move it to production factors used below
# Then we will remove it from the books
production_factors = production_factors + tranx.amount
# Amount produced is labour * productivity in this simple model
amount = production_factors * firm.productivity
# Create a transaction
transaction = Transaction()
# Add the appropriate values to the transaction
transaction.this_transaction("goods", "", firm.identifier, firm.identifier,
amount, 0, 0, -1)
# And add the transaction to the books (do it through function/not manually)
transaction.add_transaction(environment)
# Finally, we remove all the labour that was used in production
# from the books of the firms
self.remove_labour_firms(environment, time)
logging.info(" goods produced on step: %s", time)
def transaction__this_transaction(self, args):
import os
from src.bank import Bank
from src.household import Household
from src.firm import Firm
from src.environment import Environment
from src.transaction import Transaction
text = "This test checks transaction.this_transaction \n"
self.print_info(text)
#
# INITIALIZATION
#
environment_directory = str(args[0])
identifier = str(args[1])
log_directory = str(args[2])
# Configure logging parameters so we get output while the program runs
logging.basicConfig(format='%(asctime)s %(message)s', datefmt='%m/%d/%Y %H:%M:%S',
filename=log_directory + identifier + ".log", level=logging.INFO)
logging.info('START logging for test transaction__this_transaction in run: %s',
environment_directory + identifier + ".xml")
# Construct household filename
environment = Environment(environment_directory, identifier)
#
# TESTING
#
print("Creating a transaction")
transaction = Transaction()
print("Assigning values")
transaction.this_transaction("type", "asset", "from", "to", 1, 2, 3, 4)
print("The transaction:")
print(transaction)
def make_deposits(self, environment, time):
for household in environment.households:
cash = 0.0 # total of cash available for the household
control_deposits = 0 # checking if the household already has deposits
# We calculate the available cash
for tranx in household.accounts:
if tranx.type_ == "cash":
cash = cash + tranx.amount
tranx.amount = 0
# And the number of existing deposits
if tranx.type_ == "deposits":
control_deposits = control_deposits + 1
# And move all available cash to deposits at the end of the step
# If there are no deposits we create one in a bank
# The bank is chosen randomly
if control_deposits == 0:
# We choose a bank randomly
random_bank = random.choice(environment.banks)
# Create a transaction
transaction = Transaction()
# Add the appropriate values to the transaction
transaction.this_transaction(
"deposits", "", household.identifier, random_bank, amount,
random_bank.interest_rate_deposits, 0, -1)
# And add the transaction to the books (do it through function/not manually)
transaction.add_transaction(environment)
# If there are previous deposits we expand them linearly
else:
for tranx in household.accounts:
if tranx.type_ == "deposits":
# We add the remaining cash to the existing deposits
# in equal proportions
# Perhaps this can be done proportionate with regards
# to the value of these deposits, but it's minor at this point
tranx.amount = tranx.amount + (cash / control_deposits)
logging.info(" deposits made on step: %s", time)
def initialize_standard_bank(self, bank, environment):
from src.transaction import Transaction
bank.identifier = "standard_bank_id"
# deposits - we get the first household from the list of households
# if there are no households it will be a blank which is fine for testing
amount = 250.0
transaction = Transaction()
transaction.this_transaction("deposits", "",
environment.households[0:1][0],
bank.identifier, amount,
bank.interest_rate_deposits, 0, -1)
# environment.households[0:1][0] is only for testing purposes DO NOT USE IN PRODUCTION
# what it does is is takes the first household in environment, but if there are no
# households (which happens in testing) it doesn't break down
bank.accounts.append(transaction)
# money - cash and equivalents
amount = 100.0
transaction = Transaction()
transaction.this_transaction("cash", "", bank.identifier,
bank.identifier, amount, 0, 0, -1)
bank.accounts.append(transaction)
# loans - we get the first firm from the list of firms
# if there are no firms it will be a blank which is fine for testing
amount = 150.0
transaction = Transaction()
transaction.this_transaction("loans", "", bank.identifier,
environment.firms[0:1][0], amount,
bank.interest_rate_loans, 0, -1)
# environment.firms[0:1][0] is only for testing purposes DO NOT USE IN PRODUCTION
# what it does is is takes the first firm in environment, but if there are no
# firms (which happens in testing) it doesn't break down
bank.accounts.append(transaction)
def initialize_standard_bank(self):
self.identifier = "0" # identifier
self.rb = 0.02 # refinancing costs of the bank -> tbd in environment
self.rd = 0.01 # interest rate on deposits
self.r = 0.05 # required reserve rate -> tbd in environment
self.pReal = 0.9 # probability of credit success
self.rhoReal = 0.03 # interest charged on risky investment
self.xi = 1.0 # scaling parameter in CRRA
self.theta = 1.5 # risk aversion parameter of bank
self.gamma = 0.8 # fraction of interbank loans in overall volume
assetNumber = 6.0 # number of assets available to bank
numBanks = 3.0 # number of banks in the economy
# first, calculate number of transactions for investments
numTransactions = int(round(assetNumber / numBanks))
#
# ASSETS
#
# finally, put them on the transaction stack
for i in range(numTransactions):
transaction = Transaction()
value = 100.0
maturity = 50.0
timeOfDefault = -1
transaction.this_transaction("I", self.identifier, -2, value, self.rhoReal, maturity, timeOfDefault)
self.accounts.append(transaction)
del transaction
# excess reserves
value = 90.0
transaction = Transaction()
transaction.this_transaction("E", self.identifier, -3, value, self.rb, 0, -1)
self.accounts.append(transaction)
del transaction
# required deposits to the central bank
value = 10.0
transaction = Transaction()
transaction.this_transaction("rD", self.identifier, -3, value, self.rb, 0, -1)
self.accounts.append(transaction)
del transaction
#
# LIABILITIES
#
# banking capital
value = 30.0
transaction = Transaction()
transaction.this_transaction("BC", self.identifier, self.identifier, value, 0.0, 0, -1)
self.accounts.append(transaction)
del transaction
# deposits
value = 260.0
transaction = Transaction()
transaction.this_transaction("D", -1, self.identifier, value, self.rd, 0, -1)
self.accounts.append(transaction)
del transaction
# central bank loans
value = 10.0
transaction = Transaction()
transaction.this_transaction("LC", -3, self.identifier, value, self.rb, 0, -1)
self.accounts.append(transaction)
del transaction
def consume(self, environment, time):
# We want the consumption to be done in random pairs
# So we need to randomise the households and the firms
# We start with the households and create a list of order integers
# the size of the number of households
itrange_hh = list(range(0, int(environment.num_households)))
# Then we shuffle the list
random.shuffle(itrange_hh)
# And use it to loop over the households randomly
for h in itrange_hh:
# Since we don't loop directly over households
# We assign the correct household in this run over the loop
household = environment.households[h]
wealth = 0.0 # total of deposits and cash available for the household
cash = 0.0 # total of cash available for the household
# We calculate the above two values
for tranx in household.accounts:
# We add all deposits and all cash to the wealth
if tranx.type_ == "deposits" or tranx.type_ == "cash":
wealth = wealth + tranx.amount
# But only cash to the available cash
if tranx.type_ == "cash":
cash = cash + tranx.amount
# We consume the percentage of wealth determined by
# the propensity to save, cash first
to_consume = wealth * (1 - household.propensity_to_save)
# Now we randomise firms and create a list of order integers
# the size of the number of households
itrange = list(range(0, int(environment.num_firms)))
# Then we shuffle the list
random.shuffle(itrange)
# For each firm in random order
for i in itrange:
# For every transaction on that firm's books
# We make a proxy for the cash that firm should obtain
# for whatever good they've sold to the household
firm = environment.firms[i]
firm_cash = 0.0
for tranx in firm.accounts:
# If the transaction contains goods
if tranx.type_ == "goods":
# We go through the household's accounts
for tranx_h in household.accounts:
# And look for cash
if tranx_h.type_ == "cash":
# We can buy for minimum of the cash and goods
# in question
amount_proxy = min(tranx.amount,
tranx_h.amount, to_consume)
# And remove the appropriate amount of cash
tranx_h.amount = tranx_h.amount - amount_proxy
# Lower the amount household wants to consume
to_consume = to_consume - amount_proxy
# And remove the goods from firm's account
tranx.amount = tranx.amount - amount_proxy
# And we note the cash to be added to the firm
firm_cash = firm_cash + amount_proxy
for tranx_h in household.accounts:
# And look for deposits
if tranx_h.type_ == "deposits":
# We can buy for minimum of the deposits and goods
# in question
amount_proxy = min(tranx.amount,
tranx_h.amount, to_consume)
# And remove the appropriate amount of deposits
tranx_h.amount = tranx_h.amount - amount_proxy
# Lower the amount household wants to consume
to_consume = to_consume - amount_proxy
# And remove the goods from firm's account
tranx.amount = tranx.amount - amount_proxy
# And we note the cash to be added to the firm
firm_cash = firm_cash + amount_proxy
# Add cash for sold items to the firm
cash_number = 0
# We calculate how many cash account the firm has
for tranx in firm.accounts:
if tranx.type_ == "cash":
cash_number = cash_number + 1
# If the firm doesn't have any cash accounts we create a new one
if cash_number == 0:
# Create a transaction
transaction = Transaction()
# Add the appropriate values to the transaction
transaction.this_transaction("cash", "", firm.identifier,
firm.identifier, firm_cash, 0,
0, -1)
# And add the transaction to the books (do it through function/not manually)
transaction.add_transaction(environment)
# If the firm has previous cash transactions we add the cash from sales proportionately
else:
# We find all cash transactions
for tranx in firm.accounts:
if tranx.type_ == "cash":
# And add the sales proceeds proportionately
tranx.amount = tranx.amount + (firm_cash /
cash_number)
# The sales above may have rendered some transactions worthless
# So we need to purge all accounts to make sure everything is in order
transaction = Transaction()
transaction.purge_accounts(environment)
# Finally, we remove the goods which weren't sold from firms' accounts
# As they are perishable
self.remove_goods_firms(environment, time)
logging.info(" goods consumed on step: %s", time)
def transfer_investments(self, environment):
from random import Random
from src.transaction import Transaction
random = Random()
currentVolume = 0.0
optimalVolume = 0.0
plannedVolume = 0.0
availableVolume = 0.0
transactionVolume = 0.0
transaction = Transaction()
# calculate the optimal investment volume and compare to current volume
self.calculate_optimal_investment_volume(environment)
optimalVolume = round(float(self.parameters["gamma"]*self.parameters["lamb"]*self.parameters["V"]), 4)
currentVolume = round(self.get_account("I"), 4)
# add new transactions of average size
plannedVolume = currentVolume + optimalVolume
availableVolume = self.parameters["lamb"]*self.parameters["Q"] # we can only spend a fraction of the available Q
transactionVolume = min(plannedVolume, availableVolume)
while ((transactionVolume >= self.parameters["averageTransactionSize"]) and (self.parameters["averageTransactionSize"] > 0.0)):
transactionVolume = round(transactionVolume - self.parameters["averageTransactionSize"], 5) # reduce remaining transactionVolume
self.parameters["Q"] = self.parameters["Q"] - self.parameters["averageTransactionSize"] # reduce available liquidity
# account for different maturities of investments
maturity = int(round(random.random()*environment.static_parameters["firmLoanMaturity"], 1)) # this is done very roughly and implies loans are up to 3 years
# and determine whether the loan will default
if (random.random() >= environment.static_parameters["successProbabilityFirms"]):
# the loan defaults: determine timeOfDefault
timeOfDefault = int(round(random.random()*maturity))
else:
timeOfDefault = -1
# and add transaction to the stack
transaction = Transaction()
transaction.this_transaction("I", self.identifier, -2, self.parameters["averageTransactionSize"], self.parameters["rhoReal"], maturity, timeOfDefault)
self.accounts.append(transaction)
del transaction
transactionVolume = round(transactionVolume, 5)
# finally, add the remaining transaction to the stack if the transactionVolume was positive in the first place
if (transactionVolume > 0.0):
self.parameters["Q"] = round(self.parameters["Q"] - transactionVolume, 4)
# account for different maturities of investments
maturity = int(round(random.random()*environment.static_parameters["firmLoanMaturity"], 1)) # this is done very roughly and implies loans are up to 3 years
# and determine whether the loan will default
if (random.random() >= environment.static_parameters["successProbabilityFirms"]):
# the loan defaults: determine timeOfDefault
timeOfDefault = int(round(random.random()*maturity))
else:
timeOfDefault = -1
transaction = Transaction()
transaction.this_transaction("I", self.identifier, -2, transactionVolume, self.parameters["rhoReal"], maturity, timeOfDefault)
self.accounts.append(transaction)
del transaction
def sell_labour(self, environment, time):
# We want the sell to be done in random pairs
# So we need to randomise the households and the firms
# We start with the firms and create a list of order integers
# the size of the number of firms
itrange = list(range(0, int(environment.num_firms)))
# Then we shuffle the list
random.shuffle(itrange)
# And use it to loop over the firms randomly
for i in itrange:
# Since we don't loop directly over firms
# We assign the correct firm in this run over the loop
firm = environment.firms[i]
# We calculate the amount of cash firm has to buy labour
to_buy = 0.0
# We go through the firm's transactions
for tranx in firm.accounts:
# If we find cash transaction
if tranx.type_ == "cash":
# We add the cash to the amount of labour the firm
# wants to buy, we assume 1 unit of labour costs 1 unit of cash
to_buy = to_buy + tranx.amount
# Now we randomise households and create a list of order integers
# the size of the number of households
itrange_hh = list(range(0, int(environment.num_households)))
# Then we shuffle the list
random.shuffle(itrange_hh)
# For each household in random order
for h in itrange_hh:
# Since we don't loop directly over households
# We assign the correct household in this run over the loop
household = environment.households[h]
household_cash = 0.0
# We go through household's accounts
for tranx in household.accounts:
# And find transactions with labour
if tranx.type_ == "manhours":
# We will sell them for cash
# So we look through firm's accounts
for tranx_f in firm.accounts:
# And find cash transactions
if tranx_f.type_ == "cash":
# We can only buy the lowest amount from the cash the firm
# has, the labour the household has, and however many units
# they want to buy
amount_proxy = min(tranx.amount,
tranx_f.amount, to_buy)
# Then we remove the appropriate amount of cash from the firm
tranx_f.amount = tranx_f.amount - amount_proxy
# Lower the amount firm wants to buy
to_buy = to_buy - amount_proxy
# And remove the goods from household's account
tranx.amount = tranx.amount - amount_proxy
# And we note the cash to be added to the household
household_cash = household_cash + amount_proxy
# Create a transaction
transaction = Transaction()
# Add the appropriate values to the transaction
transaction.this_transaction(
"manhours", "", firm.identifier,
firm.identifier, amount_proxy, 0, 0, -1)
# And add the transaction to the books (do it through function/not manually)
transaction.add_transaction(environment)
# Add cash for sold items to the household
cash_number = 0
# We calculate how many cash account the household has
for tranx in household.accounts:
if tranx.type_ == "cash":
cash_number = cash_number + 1
# If there are no cash transactions on the household's books
# We create a new one and put the proceeds there
if cash_number == 0:
# Create a transaction
transaction = Transaction()
# Add the appropriate values to the transaction
transaction.this_transaction("cash", "",
household.identifier,
household.identifier,
household_cash, 0, 0, -1)
# And add the transaction to the books (do it through function/not manually)
transaction.add_transaction(environment)
# If the household has previous cash transactions we add the cash from sales proportionately
else:
# We find all cash transactions
for tranx in household.accounts:
if tranx.type_ == "cash":
# And add the sales proceeds proportionately
tranx.amount = tranx.amount + (household_cash /
cash_number)
# The sales above may have rendered some transactions worthless
# So we need to purge all accounts to make sure everything is in order
transaction = Transaction()
transaction.purge_accounts(environment)
logging.info(" labour sold to firms on step: %s", time)
def initialize_transactions(self, environment):
from src.transaction import Transaction
from random import Random
random = Random()
value = 0.0
# first, calculate number of transactions for investments
numTransactions = int(round(self.parameters["assetNumber"] / self.parameters["numBanks"]))
if (numTransactions == 0): # we want some error message if there are two few assets in the economy
logging.info(" ERROR: number of assets in the economy has to be at least half the number of banks")
# now, calculate value of each transaction and note that the *product* of all individual transactions
# is supposed to have precision 4. Hence, each individual transaction should have precision 5
value = round(float(self.parameters["gamma"]*self.parameters["lamb"]*self.parameters["V"] / numTransactions), 5)
# finally, put them on the transaction stack
for i in range(numTransactions):
transaction = Transaction()
#
# account for different maturities
#
maturity = int(round(random.random()*environment.static_parameters["firmLoanMaturity"], 1)) # maturity is between 0 and firmLoanMaturity
# and determine whether the loan will default
if (random.random() >= environment.static_parameters["successProbabilityFirms"]): # TODO this is superfluous, we could get rid of this doubling
# the loan defaults: determine timeOfDefault
timeOfDefault = int(round(random.random()*maturity))
else:
timeOfDefault = -1
# then, generate the transaction, append it to the accounts, and delete it from memory
transaction.this_transaction("I", self.identifier, -2, value, self.parameters["rhoReal"], maturity, timeOfDefault)
self.accounts.append(transaction)
del transaction
# store averageTransactionSize
self.parameters["averageTransactionSize"] = value
# then, calculate excess reserves
value = round(float(self.parameters["gamma"]*(1.0-self.parameters["lamb"])*self.parameters["V"]), 4)
transaction = Transaction()
transaction.this_transaction("E", self.identifier, -3, value, self.parameters["rb"], 0, -1)
self.accounts.append(transaction)
del transaction
# on the liabilities side, banks are endowed with banking capital
# (see comments in get_initial_banking_capital() for further details)
value = round(float(self.get_initial_banking_capital(environment.static_parameters["requiredCapitalRatio"])), 4)
transaction = Transaction()
transaction.this_transaction("BC", self.identifier, self.identifier, value, 0.0, 0, -1)
self.accounts.append(transaction)
del transaction
# now, transfer deposits from households to banks
value = round(float(self.parameters["gamma"]*self.parameters["V"]-self.get_account("BC")), 4)
transaction = Transaction()
transaction.this_transaction("D", -1, self.identifier, value, self.parameters["rd"], 0, -1)
self.accounts.append(transaction)
del transaction
# as well as required deposits to the central bank
value = round(float(self.parameters["r"]*self.get_account("D")), 4)
transaction = Transaction()
transaction.this_transaction("rD", self.identifier, -3, value, self.parameters["rb"], 0, -1)
self.accounts.append(transaction)
del transaction
# finally, determine central bank loans
value = round(float(self.get_account("I") + self.get_account("E") + self.get_account("rD") - self.get_account("D") - self.get_account("BC")), 4)
transaction = Transaction()
transaction.this_transaction("LC", self.identifier, -3, value, self.parameters["rb"], 0, -1)
self.accounts.append(transaction)
del transaction
def add_transaction(self, type, fromID, toID, value, interest, maturity, timeOfDefault):
from src.transaction import Transaction
transaction = Transaction()
transaction.this_transaction(type, fromID, toID, value, interest, maturity, timeOfDefault)
self.accounts.append(transaction)
del transaction
def initialize_standard_bank(self):
from src.transaction import Transaction
self.parameters["identifier"] = "0" # identifier
self.parameters["V"] = 250.0 # planned optimal portfolio volume of the bank
self.parameters["lamb"] = 0.5 # planned optimal portfolio structure of the bank
self.parameters["rb"] = 0.02 # refinancing costs of the bank -> tbd in environment
self.parameters["rd"] = 0.01 # interest rate on deposits
self.parameters["r"] = 0.05 # required reserve rate -> tbd in environment
self.parameters["pReal"] = 0.9 # probability of credit success
self.parameters["rhoReal"] = 0.03 # interest charged on risky investment
self.parameters["xi"] = 1.0 # scaling parameter in CRRA
self.parameters["theta"] = 1.5 # risk aversion parameter of bank
self.parameters["gamma"] = 0.8 # fraction of interbank loans in overall volume
self.parameters["Q"] = 0.0 # the current liquidity position of the bank
# set 0.0 as standard, but after calculate_liquidity_demand we will return the indicated values
self.parameters["Ip"] = 0.0 # the planned optimal investment; (gamma * lamb * V) = (0.8 * 0.5 * 250.0) = 100.0
self.parameters["Ep"] = 0.0 # the planned excess reserves; (gamma * (1-lamb) * V) = (0.8 * 0.5 * 250.0) = 100.0
self.parameters["Lp"] = 0.0 # the planned interbank loans; Q - ((Ip-I) + (Ep-E)) = 90.0
self.parameters["assetNumber"] = 6.0 # number of assets available to bank
self.parameters["numBanks"] = 3.0 # number of banks in the economy
# first, calculate number of transactions for investments
numTransactions = int(round(self.parameters["assetNumber"] / self.parameters["numBanks"]))
#
# ASSETS
#
# finally, put them on the transaction stack
for i in range(numTransactions):
transaction = Transaction()
value = 100.0
maturity = 50.0
timeOfDefault = -1
transaction.this_transaction("I", self.identifier, -2, value, self.parameters["rhoReal"], maturity, timeOfDefault)
self.accounts.append(transaction)
del transaction
# excess reserves
value = 90.0
transaction = Transaction()
transaction.this_transaction("E", self.identifier, -3, value, self.parameters["rb"], 0, -1)
self.accounts.append(transaction)
del transaction
# required deposits to the central bank
value = 10.0
transaction = Transaction()
transaction.this_transaction("rD", self.identifier, -3, value, self.parameters["rb"], 0, -1)
self.accounts.append(transaction)
del transaction
#
# LIABILITIES
#
# banking capital
value = 40.0
transaction = Transaction()
transaction.this_transaction("BC", self.identifier, self.identifier, value, 0.0, 0, -1)
self.accounts.append(transaction)
del transaction
# deposits
value = 250.0
transaction = Transaction()
transaction.this_transaction("D", -1, self.identifier, value, self.parameters["rd"], 0, -1)
self.accounts.append(transaction)
del transaction
# central bank loans
value = 10.0
transaction = Transaction()
transaction.this_transaction("LC", -3, self.identifier, value, self.parameters["rb"], 0, -1)
self.accounts.append(transaction)
del transaction
def consume(self, environment, time):
# We want the consumption to be done in random pairs
# So we need to randomise the households and the firms
# We start with the households and create a list of order integers
# the size of the number of households
itrange_hh = list(range(0, int(environment.num_households)))
# Then we shuffle the list
random.shuffle(itrange_hh)
# And use it to loop over the households randomly
for h in itrange_hh:
# Since we don't loop directly over households
# We assign the correct household in this run over the loop
household = environment.households[h]
wealth = 0.0 # total of deposits and cash available for the household
cash = 0.0 # total of cash available for the household
# We calculate the above two values
for tranx in household.accounts:
# We add all deposits and all cash to the wealth
if tranx.type_ == "deposits" or tranx.type_ == "cash":
wealth = wealth + tranx.amount
# But only cash to the available cash
if tranx.type_ == "cash":
cash = cash + tranx.amount
# We consume the percentage of wealth determined by
# the propensity to save, cash first
to_consume = wealth * (1 - household.propensity_to_save)
# Now we randomise firms and create a list of order integers
# the size of the number of households
itrange = list(range(0, int(environment.num_firms)))
# Then we shuffle the list
random.shuffle(itrange)
# For each firm in random order
for i in itrange:
# For every transaction on that firm's books
# We make a proxy for the cash that firm should obtain
# for whatever good they've sold to the household
firm = environment.firms[i]
firm_cash = 0.0
for tranx in firm.accounts:
# If the transaction contains goods
if tranx.type_ == "goods":
# We go through the household's accounts
for tranx_h in household.accounts:
# And look for cash
if tranx_h.type_ == "cash":
# We can buy for minimum of the cash and goods
# in question
amount_proxy = min(tranx.amount, tranx_h.amount, to_consume)
# And remove the appropriate amount of cash
tranx_h.amount = tranx_h.amount - amount_proxy
# Lower the amount household wants to consume
to_consume = to_consume - amount_proxy
# And remove the goods from firm's account
tranx.amount = tranx.amount - amount_proxy
# And we note the cash to be added to the firm
firm_cash = firm_cash + amount_proxy
for tranx_h in household.accounts:
# And look for deposits
if tranx_h.type_ == "deposits":
# We can buy for minimum of the deposits and goods
# in question
amount_proxy = min(tranx.amount, tranx_h.amount, to_consume)
# And remove the appropriate amount of deposits
tranx_h.amount = tranx_h.amount - amount_proxy
# Lower the amount household wants to consume
to_consume = to_consume - amount_proxy
# And remove the goods from firm's account
tranx.amount = tranx.amount - amount_proxy
# And we note the cash to be added to the firm
firm_cash = firm_cash + amount_proxy
# Add cash for sold items to the firm
cash_number = 0
# We calculate how many cash account the firm has
for tranx in firm.accounts:
if tranx.type_ == "cash":
cash_number = cash_number + 1
# If the firm doesn't have any cash accounts we create a new one
if cash_number == 0:
# Create a transaction
transaction = Transaction()
# Add the appropriate values to the transaction
transaction.this_transaction("cash", "", firm.identifier, firm.identifier,
firm_cash, 0, 0, -1)
# And add the transaction to the books (do it through function/not manually)
transaction.add_transaction(environment)
# If the firm has previous cash transactions we add the cash from sales proportionately
else:
# We find all cash transactions
for tranx in firm.accounts:
if tranx.type_ == "cash":
# And add the sales proceeds proportionately
tranx.amount = tranx.amount + (firm_cash / cash_number)
# The sales above may have rendered some transactions worthless
# So we need to purge all accounts to make sure everything is in order
transaction = Transaction()
transaction.purge_accounts(environment)
# Finally, we remove the goods which weren't sold from firms' accounts
# As they are perishable
self.remove_goods_firms(environment, time)
logging.info(" goods consumed on step: %s", time)
def new_transaction(self, type_, asset, from_, to, amount, interest, maturity, time_of_default):
from src.transaction import Transaction
transaction = Transaction()
transaction.this_transaction(type_, asset, from_, to, amount, interest, maturity, time_of_default)
transaction.add_transaction(self)
def sell_labour(self, environment, time):
# We want the sell to be done in random pairs
# So we need to randomise the households and the firms
# We start with the firms and create a list of order integers
# the size of the number of firms
itrange = list(range(0, int(environment.num_firms)))
# Then we shuffle the list
random.shuffle(itrange)
# And use it to loop over the firms randomly
for i in itrange:
# Since we don't loop directly over firms
# We assign the correct firm in this run over the loop
firm = environment.firms[i]
# We calculate the amount of cash firm has to buy labour
to_buy = 0.0
# We go through the firm's transactions
for tranx in firm.accounts:
# If we find cash transaction
if tranx.type_ == "cash":
# We add the cash to the amount of labour the firm
# wants to buy, we assume 1 unit of labour costs 1 unit of cash
to_buy = to_buy + tranx.amount
# Now we randomise households and create a list of order integers
# the size of the number of households
itrange_hh = list(range(0, int(environment.num_households)))
# Then we shuffle the list
random.shuffle(itrange_hh)
# For each household in random order
for h in itrange_hh:
# Since we don't loop directly over households
# We assign the correct household in this run over the loop
household = environment.households[h]
household_cash = 0.0
# We go through household's accounts
for tranx in household.accounts:
# And find transactions with labour
if tranx.type_ == "manhours":
# We will sell them for cash
# So we look through firm's accounts
for tranx_f in firm.accounts:
# And find cash transactions
if tranx_f.type_ == "cash":
# We can only buy the lowest amount from the cash the firm
# has, the labour the household has, and however many units
# they want to buy
amount_proxy = min(tranx.amount, tranx_f.amount, to_buy)
# Then we remove the appropriate amount of cash from the firm
tranx_f.amount = tranx_f.amount - amount_proxy
# Lower the amount firm wants to buy
to_buy = to_buy - amount_proxy
# And remove the goods from household's account
tranx.amount = tranx.amount - amount_proxy
# And we note the cash to be added to the household
household_cash = household_cash + amount_proxy
# Create a transaction
transaction = Transaction()
# Add the appropriate values to the transaction
transaction.this_transaction("manhours", "", firm.identifier, firm.identifier,
amount_proxy, 0, 0, -1)
# And add the transaction to the books (do it through function/not manually)
transaction.add_transaction(environment)
# Add cash for sold items to the household
cash_number = 0
# We calculate how many cash account the household has
for tranx in household.accounts:
if tranx.type_ == "cash":
cash_number = cash_number + 1
# If there are no cash transactions on the household's books
# We create a new one and put the proceeds there
if cash_number == 0:
# Create a transaction
transaction = Transaction()
# Add the appropriate values to the transaction
transaction.this_transaction("cash", "", household.identifier, household.identifier,
household_cash, 0, 0, -1)
# And add the transaction to the books (do it through function/not manually)
transaction.add_transaction(environment)
# If the household has previous cash transactions we add the cash from sales proportionately
else:
# We find all cash transactions
for tranx in household.accounts:
if tranx.type_ == "cash":
# And add the sales proceeds proportionately
tranx.amount = tranx.amount + (household_cash / cash_number)
# The sales above may have rendered some transactions worthless
# So we need to purge all accounts to make sure everything is in order
transaction = Transaction()
transaction.purge_accounts(environment)
logging.info(" labour sold to firms on step: %s", time)
def transfer_investments(self, state):
currentVolume = 0.0
optimalVolume = 0.0
plannedVolume = 0.0
availableVolume = 0.0
transactionVolume = 0.0
transaction = Transaction()
# calculate the optimal investment volume and compare to current volume
self.calculate_optimal_investment_volume(state)
optimalVolume = round(float(self.gamma * self.lamb * self.V), 4)
currentVolume = round(self.get_account("I"), 4)
# add new transactions of average size
plannedVolume = optimalVolume - currentVolume
availableVolume = self.lamb * self.Q # we can only spend a fraction of the available Q
transactionVolume = min(plannedVolume, availableVolume)
while (transactionVolume >= self.averageTransactionSize) and (self.averageTransactionSize > 0.0):
transactionVolume = round(transactionVolume - self.averageTransactionSize,
5) # reduce remaining transactionVolume
self.Q = self.Q - self.averageTransactionSize # reduce available liquidity
# account for different maturities of investments
maturity = int(round(random.random() * state.firmLoanMaturity,
1)) # this is done very roughly and implies loans are up to 3 years
# and determine whether the loan will default
if random.random() >= state.successProbabilityFirms:
# the loan defaults: determine timeOfDefault
timeOfDefault = int(round(random.random() * maturity))
else:
timeOfDefault = -1
# and add transaction to the stack
transaction = Transaction()
transaction.this_transaction("I", self.identifier, -2, self.averageTransactionSize, self.rhoReal, maturity,
timeOfDefault)
self.accounts.append(transaction)
del transaction
transactionVolume = round(transactionVolume, 5)
# finally, add the remaining transaction to the stack if the transactionVolume was positive in the first place
if transactionVolume > 0.0:
self.Q = round(self.Q - transactionVolume, 4)
# account for different maturities of investments
maturity = int(round(random.random() * state.firmLoanMaturity,
1)) # this is done very roughly and implies loans are up to 3 years
# and determine whether the loan will default
if random.random() >= state.successProbabilityFirms:
# the loan defaults: determine timeOfDefault
timeOfDefault = int(round(random.random() * maturity))
else:
timeOfDefault = -1
transaction = Transaction()
transaction.this_transaction("I", self.identifier, -2, transactionVolume, self.rhoReal, maturity, timeOfDefault)
self.accounts.append(transaction)
del transaction
def add_transaction(self, type_, asset, from_id, to_id, amount, interest, maturity, time_of_default, environment):
from src.transaction import Transaction
transaction = Transaction()
transaction.this_transaction(type_, asset, from_id, to_id, amount, interest, maturity, time_of_default)
transaction.add_transaction(environment)
def initialize_transactions(self, state):
value = 0.0
# first, calculate number of transactions for investments
numTransactions = int(round(self.assetNumber / self.numBanks))
# print(numTransactions)
if numTransactions == 0: # we want some error message if there are two few assets in the economy
logging.info(" ERROR: number of assets in the economy has to be at least half the number of banks")
# now, calculate value of each transaction and note that the *product* of all individual transactions
# is supposed to have precision 4. Hence, each individual transaction should have precision 5
value = round(float(self.gamma * self.lamb * self.V / numTransactions), 5)
# finally, put them on the transaction stack
for i in range(numTransactions):
transaction = Transaction()
#
# account for different maturities
#
maturity = int(
round(random.random() * state.firmLoanMaturity, 1)) # maturity is between 0 and firmLoanMaturity
# and determine whether the loan will default
if (
random.random() >= state.successProbabilityFirms): # TODO this is superfluous, we could get rid of this doubling
# the loan defaults: determine timeOfDefault
timeOfDefault = int(round(random.random() * maturity))
else:
timeOfDefault = -1
# then, generate the transaction, append it to the accounts, and delete it from memory
transaction.this_transaction("I", self.identifier, -2, value, self.rhoReal, maturity, timeOfDefault)
self.accounts.append(transaction)
del transaction
# store averageTransactionSize
self.averageTransactionSize = value
# then, calculate excess reserves
value = round(float(self.gamma * (1.0 - self.lamb) * self.V), 4)
transaction = Transaction()
transaction.this_transaction("E", self.identifier, -3, value, self.rb, 0, -1)
self.accounts.append(transaction)
del transaction
# on the liabilities side, banks are endowed with banking capital
# (see comments in get_initial_banking_capital() for further details)
value = round(float(self.get_initial_banking_capital(state.requiredCapitalRatio)), 4)
transaction = Transaction()
transaction.this_transaction("BC", self.identifier, self.identifier, value, 0.0, 0, -1)
self.accounts.append(transaction)
del transaction
# now, transfer deposits from households to banks
value = round(float(self.gamma * self.V - self.get_account("BC")), 4)
transaction = Transaction()
transaction.this_transaction("D", -1, self.identifier, value, self.rd, 0, -1)
self.accounts.append(transaction)
del transaction
# as well as required deposits to the central bank
value = round(float(self.r * self.get_account("D")), 4)
transaction = Transaction()
transaction.this_transaction("rD", self.identifier, -3, value, self.rb, 0, -1)
self.accounts.append(transaction)
del transaction
# finally, determine central bank loans
value = round(float(self.get_account("I") + self.get_account("E") + self.get_account("rD") - self.get_account(
"D") - self.get_account("BC")), 4)
transaction = Transaction()
transaction.this_transaction("LC", self.identifier, -3, value, self.rb, 0, -1)
print(transaction.print_transaction())
self.accounts.append(transaction)
del transaction
def add_transaction(self, type_, fromID, toID, value, interest, maturity, timeOfDefault):
transaction = Transaction()
transaction.this_transaction(type_, fromID, toID, value, interest, maturity, timeOfDefault)
self.accounts.append(transaction)
del transaction