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Author: HummdG

stock_price_simulations/apple_stock_price_sim.py

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+import numpy as np
+import matplotlib.pyplot as plt
+import yfinance as yf
+
+def get_stock_prices(ticker, start_date, end_date):
+    stock_data = yf.download(ticker, start=start_date, end=end_date)
+    return stock_data['Close'].values
+
+def monte_carlo_simulation(starting_prices, num_simulations, num_days, returns_std):
+    simulations = np.zeros((num_simulations, num_days))
+    simulations[:, 0] = starting_prices
+
+    for i in range(1, num_days):
+        daily_returns = np.random.normal(0, returns_std, num_simulations)
+        simulations[:, i] = simulations[:, i - 1] * (1 + daily_returns)
+
+    return simulations
+
+# Set parameters
+ticker = 'AAPL'  # Apple stock symbol
+start_date = '2022-01-01'
+end_date = '2023-01-01'
+historical_prices = get_stock_prices(ticker, start_date, end_date)
+
+num_simulations = 100  # Number of simulations
+num_days = 250  # Number of trading days in a year
+
+starting_prices = historical_prices[-num_simulations:]  # Use the last prices for the initial simulations
+returns_std = np.std(np.diff(np.log(historical_prices)))  # Use historical daily log returns standard deviation
+
+# Run the simulation
+simulations = monte_carlo_simulation(starting_prices, num_simulations, num_days, returns_std)
+
+# Plot the results
+plt.figure(figsize=(10, 6))
+
+# Plot simulations
+for i in range(num_simulations):
+    plt.plot(simulations[i, :], color='blue', alpha=0.1)
+
+# Highlight actual stock prices in a different color
+plt.plot(historical_prices, color='red', label='Actual Stock Price')
+
+plt.title('Monte Carlo Simulation of Daily Stock Prices for AAPL')
+plt.xlabel('Days')
+plt.ylabel('Stock Price')
+plt.legend()
+plt.show()