retriementplanner

🎯 Retirement Planner with Monte Carlo Simulation

A comprehensive retirement planning tool built with Streamlit that combines deterministic projections with Monte Carlo risk analysis. Perfect for financial planning, portfolio optimization, and retirement strategy development.

✨ Features

📊 Portfolio Configuration

• Set initial portfolio value and retirement timeline
• Configure withdrawal amounts and inflation rates
• Tax rate optimization for capital gains and income

📈 Scenario Analysis

• Basecase Scenario: Your expected retirement path
• Stress Test Scenario: Crisis impact analysis
• Custom Crisis: Define your own market shock scenarios
• Historical crisis templates (Dot-Com, 2008, COVID-19)

🎯 Asset Allocation

• 7 asset classes: Equities, Bonds, REITs, Precious Metals, Crypto, Real Estate, Cash
• Default allocations: 50% Equities, 40% Bonds, 5% Precious Metals, 5% Cash
• Expected returns, income, and volatility parameters
• Mean reversion settings for advanced modeling

🎲 Monte Carlo Simulation

• Thousands of simulations with random market returns
• Interactive charts with confidence intervals (5th, 10th, 25th, 50th, 75th, 90th, 95th percentiles)
• Risk analysis with depletion probability
• Portfolio floor visualization (configurable minimum values)
• Logarithmic scaling for better visualization

📊 Advanced Analytics

• Correlation matrix configuration for realistic asset relationships
• Volatility modeling with historical data
• Mean reversion parameters for sophisticated modeling
• Mobile-responsive design for accessibility

🚀 Quick Start

Installation

1. Clone the repository:

   git clone https://github.com/YOUR_USERNAME/retirement-planner.git
   cd retirement-planner
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Run the application:

   streamlit run retirement_planner.py
   

4. Open your browser to http://localhost:8501

Usage Workflow

1. 📊 Portfolio Configuration - Set your portfolio value and retirement timeline
2. 📈 Scenarios - Configure your basecase and stress test scenarios
3. 🎯 Asset Allocation - Set your portfolio weights and expected returns
4. 📊 Expected Returns - Calculate future portfolio value based on expected returns (no variation)
5. 🎲 Monte Carlo - Run simulations on thousands of potential paths into the future

Advanced Users: Experiment with parameters (correlations, volatilities, mean reversion) once familiar with the mechanics of this tool.

📱 Mobile-Friendly Design

• Responsive tabs with larger fonts and icons
• Touch-optimized interface for mobile devices
• Word wrapping for better readability
• Professional layout that works on all screen sizes

🎨 Visualization Features

Monte Carlo Charts

• Percentile lines showing confidence intervals
• Color-coded risk levels: Green (low risk) → Red (high risk)
• Interactive hover with detailed values
• Logarithmic scaling for exponential growth visualization

Risk Analysis

• 5th percentile focus: Your 1 in 20 worst-case scenario
• Depletion risk: Probability of running out of money
• Portfolio floor: Configurable minimum value display
• Stress testing: Crisis impact analysis

⚙️ Configuration Options

Monte Carlo Parameters

• Iterations: 100 to 50,000 simulations
• Portfolio floor: 0.1% to 50% of initial value
• Correlation matrix: Customizable asset relationships

Asset Classes

• Equities: Growth stocks and equity funds
• Bonds/CPF RA: Fixed income and CPF Retirement Account
• REITs: Real Estate Investment Trusts
• Precious Metals: Gold and other precious metals
• Crypto: Cryptocurrency investments
• Physical Real Estate: Property investments
• Cash/CPF OA: Cash and CPF Ordinary Account

📊 Sample Results

The tool provides comprehensive analysis including:

• Median portfolio values across time horizons
• Risk percentiles (5th, 25th, 50th, 75th, 95th)
• Depletion probabilities for different scenarios
• Crisis impact analysis with historical and custom scenarios

🛠️ Technical Details

Dependencies

• Streamlit: Web application framework
• NumPy: Numerical computations
• Pandas: Data manipulation
• Plotly: Interactive visualizations

Architecture

• Modular design with separate functions for calculations and visualization
• Session state management for user interactions
• Responsive CSS for mobile optimization
• Error handling with graceful fallbacks

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

👨‍💻 Author

Created by Wolfgang Seidl via Claude.ai

🙏 Acknowledgments

• Built with Streamlit
• Visualization powered by Plotly
• Financial modeling concepts from modern portfolio theory
• Monte Carlo methods for risk analysis

📞 Support

For questions, issues, or feature requests, please open an issue on GitHub.

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⚠️ Disclaimer: This tool is for educational and planning purposes only. It does not constitute financial advice. Always consult with a qualified financial advisor before making investment decisions.