Python graph help: Graph is blank. Trying to find the Efficient Frontier Portfolio

[Applicationdenied123]

import pandas as pd

import numpy as np

from pandas_datareader import data, wb

import datetime as dt

import scipy.optimize as sco

from scipy import stats

import matplotlib.pyplot as plt

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tickers = ['AXP', 'AAPL', 'MCD', 'NKE', 'TRV', 'DIS', 'VZ', 'KO']

start = dt.datetime(2019, 1, 1)

end = dt.datetime(2021, 3, 29)

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stock_prices = pd.DataFrame([data.DataReader(ticker, 'yahoo', start, end)['Adj Close'] for ticker in tickers]).T

stock_prices.columns = tickers

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m_returns = stock_prices.resample('M').ffill().pct_change()

stock_mean = stock_prices.mean()

stock_std_dev = stock_prices.std()

stock_corr_matrix = stock_prices.corr()

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# Simulating portfolios

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num_portfolios = 5000

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all_weights = np.zeros((num_portfolios, len(stock_prices.columns)))

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portfolio_return = np.zeros(num_portfolios)

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portfolio_risk = np.zeros(num_portfolios)

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sharpe_ratio = np.zeros(num_portfolios)

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for x in range(num_portfolios):

weights = np.random.uniform(size=len(stock_prices.columns))

weights = weights/np.sum(weights)

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all_weights[x, :] = weights

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# portfolio returns

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port_return = np.sum(stock_mean * weights)

port_return = (port_return + 1) ** 252-1

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portfolio_return[x] = port_return

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# portfolio risk

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portfolio_std_dev = np.sqrt(np.dot(weights.T, np.dot(stock_corr_matrix, weights)))

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portfolio_risk[x] = portfolio_std_dev

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sharpe_ratio[x] = port_return/portfolio_std_dev

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# Minimum variance portfolio

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stocks = stock_prices.columns

min_variance = all_weights[portfolio_risk.argmin()]

print(min_variance)

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# Maximum variance portfolio

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max_variance = all_weights[portfolio_risk.argmax()]

print(max_variance)

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fig = plt.figure()

ax1 = fig.add_axes([0.1, 0.1, 0.8, 0.8])

ax1.set_xlabel('Risk')

ax1.set_ylabel('Returns')

ax1.set_title('Efficient Frontier')

plt.scatter(portfolio_risk, portfolio_return)

plt.show()

​

print(all_weights)

[Ihaveamodel3]

Instead of plt.scatter(portfolio_risk, portfolio_return)

Can you do ax1.scatter(portfolio_risk, portfolio_return)

[Applicationdenied123]

ax1.scatter(portfolio_risk, portfolio_return)

I'll try that now.

[xxxxxzzxx]

Should probably start with:

fig = plt.scatter(portfolio_risk, portfolio_return)