target_wealth = 12000000

current_wealth = 71873.20

lc_portfolio = Portfolio(start_stocks, lc)

annuity = 71873.20

age = Investor.start_age

while current_wealth < target_wealth:

lc_portfolio.adjust_portfolio(age)

rm = calc_rm(Year.rm_mean, Year.rm_deviation)

rf = calc_rm(Year.rf_mean, Year.rf_deviation)

stocks_value = current_wealth * lc_portfolio.stocks * (1 + rm)

fixed_value = current_wealth * lc_portfolio.fixed * (1 + rf)

current_wealth = stocks_value + fixed_value + annuity

age += 1

ages = []

for iteration in range(0, iterations):

ages.append(simulate(start_stocks, lc))

min_age = min(ages)

max_age = max(ages)

for pa in range(60, 66):

print('probability for age ', pa, ': ', calc_probability(ages, pa))

print('mean: ', mean(ages))

print('stdev: ', stdev(ages))

print('variance: ', variance(ages))

print('mode: ', mode(ages))

print('median: ', median(ages))

print('min age: ', min_age)

print('max age: ', max_age)

print('interval (max-min): ', max_age - min_age)

sns.distplot(ages, norm_hist=True, kde=False, bins=np.arange(min_age, max_age + 1))

# with open('ages100.txt', mode='wt', encoding='utf-8') as file:

# file.write('\n'.join((str(i) for i in set(ages))))

# sns.kdeplot(ages, shade=True)

# pyplot.hist(ages, density=True)

length = len(ages)

counter = 0

for a in ages:

if a <= age:

counter += 1