MonteCarloSmiulation

import numpy as np
import matplotlib.pyplot as plt

# Initial portfolio value and return statistics
initial_investment = 10000  # Initial investment
mean_return = 0.15  # Average annual stock return
return_stddev = 0.18  # Standard deviation of annual stock return
num_years = 10  # Number of years for the simulation

# Monte Carlo simulation parameters
num_simulations = 1000  # Number of simulations

# Create an array to store investment returns for each simulation
portfolio_values = np.zeros((num_simulations, num_years + 1))

for i in range(num_simulations):
    # Simulate returns for each year
    annual_returns = np.random.normal(mean_return, return_stddev, num_years) + 1
    
    # Update portfolio value each year
    portfolio_values[i][0] = initial_investment
    for j in range(num_years):
        portfolio_values[i][j + 1] = portfolio_values[i][j] * annual_returns[j]

# Plot the final portfolio value for each simulation
for i in range(num_simulations):
    plt.plot(range(num_years + 1), portfolio_values[i])

# Plot the average results
mean_portfolio_values = np.mean(portfolio_values, axis=0)
plt.plot(range(num_years + 1), mean_portfolio_values, 'k-', linewidth=3, label='Average')

plt.title('Monte Carlo Simulation - Stock Portfolio')
plt.xlabel('Year')
plt.ylabel('Portfolio Value')
plt.legend()
plt.grid(True)
plt.show()