Quant Sector Rotation Strategy 📈

A sophisticated quantitative trading strategy leveraging momentum and volatility signals for ETF sector rotation, enhanced with LLM-powered strategy analysis.

🚀 Try It Now!

Experience the strategy in action: Quant Sector Rotation App

🚀 Strategy Overview

This project implements a systematic sector rotation strategy using ETFs, combining momentum signals with intelligent risk management. The strategy employs a unique "Moving Average Energy" indicator for momentum measurement and incorporates VIX-based position sizing.

🎯 Key Features

• MA Energy Indicator: Proprietary momentum indicator using multiple timeframe moving averages, normalized by price volatility
• Dynamic Risk Management: VIX-based position sizing with adaptive thresholds
• LLM Strategy Review: AI-powered performance analysis and strategy behavior insights
• Interactive Dashboard: Real-time strategy monitoring and backtesting visualization

📊 Backtest Results (2010-2024)

• Annual Return: 18.5%
• Sharpe Ratio: 1.45
• Information Ratio: 0.82

🛠️ Technical Architecture

1. Signal Generation

   • Multi-timeframe MA Energy calculation
   • Cross-asset momentum comparison
   • Volatility normalization

2. Risk Management

   • VIX-based position sizing
   • Trailing stop implementation
   • Maximum drawdown control

3. Strategy Review

   • LLM-powered strategy behavior analysis
   • Historical context integration
   • Performance attribution

📦 Installation

git clone https://github.com/garroshub/Quant_Sector_Rotation_Strategy.git
cd Quant_Sector_Rotation_Strategy
pip install -r requirements.txt

🚀 Quick Start

streamlit run app.py

📊 Dashboard Features

1. Strategy Parameters

   • MA windows customization
   • Risk thresholds adjustment
   • Universe selection

2. Performance Analytics

   • Rolling window analysis
   • Risk metrics visualization
   • Position history tracking

3. AI Strategy Review

   • Strategy behavior analysis
   • Performance attribution
   • Improvement suggestions

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

📝 License

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

📧 Contact

GitHub: @garroshub

⭐ Star History

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Disclaimer: This strategy is for educational purposes only. Past performance does not guarantee future results. Always do your own research and consider your risk tolerance before trading.