simulation.py

investment_money = float(input()) #k
remaining_life = int(input()) #n
withdraw_money = 0.09*investment_money #w
my_mean = float(input())/100
my_std = float(input())/100
import numpy as np
loss_time = 0
CALCULATIONS = 10000
for i in range(CALCULATIONS):
    x = np.random.normal(loc=my_mean, scale=my_std, size=remaining_life)
    current_investment_money = investment_money
    for i in range(remaining_life):
        current_investment_money = current_investment_money - withdraw_money
        if current_investment_money > 0:
            current_investment_money *= (1+x[i])/(1+2.73/100)
        else: 
            loss_time = loss_time + 1
            break
print(loss_time*100/CALCULATIONS)