New altcoin code made by chatgpt based on Cambridge equation
# Pseudocode for calculating Md and managing the money supply
def calculate_V(transaction_data, money_supply):
total_transaction_value = sum([tx['value'] for tx in transaction_data])
average_money_supply = sum(money_supply) / len(money_supply)
V = total_transaction_value / average_money_supply
return V
def calculate_P(transaction_data):
total_transaction_value = sum([tx['value'] for tx in transaction_data])
num_transactions = len(transaction_data)
P = total_transaction_value / num_transactions
return P
def calculate_Y(transaction_data, period_length):
total_income = sum([tx['value'] for tx in transaction_data])
Y = total_income / period_length
return Y
def distribute_new_coins(users, new_coins):
coins_per_user = new_coins / len(users)
for user in users:
user['balance'] += coins_per_user
def apply_negative_interest(users, interest_rate):
for user in users:
user['balance'] *= (1 - interest_rate)
def adjust_money_supply(transaction_data, money_supply, users, period_length):
V = calculate_V(transaction_data, money_supply)
P = calculate_P(transaction_data)
Y = calculate_Y(transaction_data, period_length)
k = 1 / V
Md = k * P * Y
current_money_supply = sum([user['balance'] for user in users])
if Md > current_money_supply:
new_coins = Md - current_money_supply
distribute_new_coins(users, new_coins)
elif Md < current_money_supply:
excess_coins = current_money_supply - Md
interest_rate = excess_coins / current_money_supply
apply_negative_interest(users, interest_rate)
# Sample data and function call
transaction_data = [...] # Transaction data from the blockchain
money_supply = [...] # Money supply at different times
users = [...] # List of users with their balances
period_length = 30 # Period length in days or months
adjust_money_supply(transaction_data, money_supply, users, period_length)
Topic: New altcoin code made by chatgpt based on Cambridge equation (Read 23 times)
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