Markowitz Portfolio Theory Examples

Practical implementation of Modern Portfolio Theory for cryptocurrency portfolios using Python.

📚 Overview

This repository contains progressive examples demonstrating Markowitz Portfolio Theory concepts, from basic portfolio calculations to advanced optimization strategies.

🚀 Quick Start

Installation

# Clone the repository
git clone https://github.com/suenot/markowitz.git
cd markowitz

# Install dependencies
pip install -r requirements.txt

Run Examples

# Run all examples
python run_all_examples.py

# Or run individual examples
python 01_basic_portfolio_math.py
python 02_efficient_frontier.py
python 03_portfolio_optimization.py
python 04_multi_asset_portfolio.py
python 05_advanced_strategies.py

📂 Examples Structure

Level 1: Basic Portfolio Math (01_basic_portfolio_math.py)

• Portfolio return and volatility calculations
• Risk-return trade-offs
• Value at Risk (VaR) analysis
• Correlation analysis

Level 2: Efficient Frontier (02_efficient_frontier.py)

• Monte Carlo simulation of random portfolios
• Efficient frontier visualization
• Special portfolios identification (max Sharpe, min volatility)
• Portfolio concentration analysis

Level 3: Portfolio Optimization (03_portfolio_optimization.py)

• Mathematical optimization using scipy
• Maximum Sharpe ratio portfolio
• Minimum volatility portfolio
• Target return optimization
• Sensitivity analysis

Level 4: Multi-Asset Portfolio (04_multi_asset_portfolio.py)

• Real crypto portfolio with 8+ assets
• Comprehensive backtesting
• Out-of-sample performance validation
• Risk decomposition analysis
• Multiple optimization strategies comparison

Level 5: Advanced Strategies (05_advanced_strategies.py)

• Black-Litterman model
• Hierarchical Risk Parity (HRP)
• Risk Parity optimization
• Maximum Diversification
• Practical rebalancing with transaction costs

📊 Output Files

Each example generates visualization files:

• 01_basic_portfolio_analysis.png - Basic metrics and distributions
• 02_efficient_frontier.png - Efficient frontier visualization
• 03_portfolio_optimization.png - Optimization results
• 04_multi_asset_portfolio.png - Multi-asset analysis and backtesting
• 05_advanced_strategies.png - Advanced strategies comparison

🔧 Requirements

• Python 3.8+
• numpy
• pandas
• matplotlib
• seaborn
• scipy
• yfinance

📖 Documentation

See the accompanying articles for detailed explanations:

• English - Comprehensive tutorial
• Russian - Русская версия
• Chinese - 中文版

⚠️ Disclaimer

This is for educational purposes only. Not financial advice. Cryptocurrency investments are highly risky. Always do your own research.

📝 License

MIT License - see LICENSE file for details.

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.