Simulation of individual vs Shared portfolio

gistfile.py

import random
import matplotlib.pyplot as plt

# Adjusted simulation settings
trading_days = 30  # Half a year
individual_portfolios = [1000, 1000, 1000, 1000]
shared_portfolio = 1000
win_rate = 0.75  # 50% win rate

# New risk-reward settings
loss_amount = -0.0014  # -0.14%
win_amount = 0.0113  # 1.13%

individual_returns = [[portfolio] for portfolio in individual_portfolios]
shared_returns = [shared_portfolio]

for _ in range(trading_days):
    for i in range(4):
        outcome = random.choices([win_amount, loss_amount], weights=[win_rate, 1 - win_rate])[0]
        individual_portfolios[i] *= (1 + outcome)
        individual_returns[i].append(individual_portfolios[i])
    
    for _ in range(4):
        outcome = random.choices([win_amount, loss_amount], weights=[win_rate, 1 - win_rate])[0]
        shared_portfolio *= (1 + outcome)
    shared_returns.append(shared_portfolio)

# Preparing the RR and win rate details for the legend
info_text = f"RR: {win_amount*100}% / {round(loss_amount*100, 4)}%, Win Rate: {win_rate*100}%"

# Plotting and adding the RR and win rate details to the legend
plt.figure(figsize=(14, 8))
for i, returns in enumerate(individual_returns):
    plt.plot(returns, linestyle='--', label=f'Bot {i+1}')
plt.plot(shared_returns, color='black', linewidth=2, label='Shared Portfolio')

# Including the info text in the legend by adding it to an invisible line
plt.plot([], [], ' ', label=info_text)

plt.xlabel('Trading Days')
plt.ylabel('Portfolio Value ($)')
plt.title('Portfolio Growth Over Half a Year with Adjusted Risk-Reward')
plt.legend(loc='upper left')
plt.show()