EquiFlex Pro is a next-generation, institutional-grade long-short equity and options trading system that leverages advanced Greek-based strategies, AI/ML techniques, and comprehensive risk management.
- Equity Long-Short: Multi-factor models with momentum, value, quality, and volatility factors
- Greek-Based Options: Delta hedging, gamma scalping, theta harvesting, vega management
- Complex Spreads: Iron condors, butterflies, straddles, and calendar spreads
- AI/ML Enhanced: Deep learning models for signal generation and market forecasting
- Real-Time Greeks Monitoring: Portfolio-level delta, gamma, theta, vega, rho tracking
- VaR and Stress Testing: Monte Carlo simulations and scenario analysis
- Dynamic Hedging: Automated position adjustments based on Greek exposures
- Regulatory Compliance: Built-in trade surveillance and reporting
- Microservices Architecture: Scalable, cloud-native design
- Multi-Broker Support: Interactive Brokers, Alpaca, and others
- Real-Time Data: High-frequency market data ingestion and processing
- Production Ready: Comprehensive logging, monitoring, and alerting
- Python 3.9+
- PostgreSQL 12+
- Redis 6+
- Docker & Docker Compose (recommended)
# Clone the repository
git clone https://github.com/bhanukaranwal/EquiFlexPro.git
cd EquiFlexPro
# Run setup script
chmod +x scripts/setup.sh
./scripts/setup.sh
# Configure environment
cp .env.example .env
# Edit .env with your API keys and configuration
# Start services
docker-compose up -d
# Access the dashboard
open http://localhost:8000# Create virtual environment
python3 -m venv venv
source venv/bin/activate
# Install dependencies
pip install -r requirements.txt
pip install -e .
# Setup database
python scripts/init_database.py
# Start trading engine
python -m src.core.engine
# Start API server (in another terminal)
python -m src.api.appThe web dashboard provides real-time monitoring of:
- Portfolio performance and Greek exposures
- Strategy status and performance metrics
- Risk metrics and limit monitoring
- Live order book and trade execution
- Market data and options chains
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ Web Dashboard │ │ REST API │ │ Trading Engine │
│ (React/JS) │◄──►│ (FastAPI) │◄──►│ (AsyncIO) │
└─────────────────┘ └─────────────────┘ └─────────────────┘
│ │
┌─────────────────┐ ┌─────────────────┐
│ Data Layer │ │ Strategy Layer │
│ (PostgreSQL) │ │ (Modular) │
└─────────────────┘ └─────────────────┘
│ │
┌─────────────────┐ ┌─────────────────┐
│ Risk Manager │ │ Execution Layer│
│ (Real-time) │ │ (Multi-Broker)│
└─────────────────┘ └─────────────────┘
- LSTM Networks: Price and volatility forecasting
- Random Forest: Factor-based equity signals
- Gradient Boosting: Multi-timeframe momentum detection
- Reinforcement Learning: Dynamic portfolio optimization
- VaR Calculation: Historical simulation and Monte Carlo
- Correlation Models: Dynamic correlation tracking
- Regime Detection: Market state identification
- Stress Testing: Scenario-based risk assessment
# Example: Multi-Factor Long-Short
strategy = EquityLongShortStrategy({
'allocation': 0.4,
'factors': ['momentum', 'value', 'quality'],
'rebalance_frequency': 'daily',
'long_short_ratio': 1.0
})# Example: Delta-Neutral Strategy
strategy = DeltaNeutralStrategy({
'target_delta': 0.0,
'delta_tolerance': 5.0,
'rehedge_threshold': 10.0,
'underlying_universe': ['SPY', 'QQQ']
})strategies:
equity_long_short:
enabled: true
allocation: 0.4
parameters:
lookback_period: 252
factors: [momentum, value, quality]
delta_neutral:
enabled: true
allocation: 0.2
parameters:
target_delta: 0.0
delta_tolerance: 5.0risk:
max_drawdown: 0.15
max_position_size: 0.05
greek_limits:
max_delta: 100
max_gamma: 50
max_theta: -200
max_vega: 500# Run all tests
pytest
# Run specific test categories
pytest tests/test_greeks.py -v
pytest tests/test_strategies.py -v
pytest tests/test_risk.py -v
# Run with coverage
pytest --cov=src tests/
# Run integration tests
pytest tests/integration/ -v# Production deployment
./scripts/deploy.sh production
# Staging deployment
./scripts/deploy.sh staging# Apply Kubernetes manifests
kubectl apply -f infrastructure/kubernetes/
# Check deployment status
kubectl get pods -n equiflex- Prometheus: System and trading metrics
- Grafana: Real-time dashboards and visualizations
- ELK Stack: Centralized logging and analysis
- Custom Alerts: Email/Slack notifications for critical events
- Portfolio performance and drawdown
- Greek exposures and limits
- Order execution quality
- System latency and errors
- Risk limit breaches
- Encrypted Communication: mTLS between services
- Secret Management: Vault integration for API keys
- Authentication: JWT-based API authentication
- Audit Trail: Immutable trade and decision logging
- Role-Based Access: Granular permission system
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
- Follow PEP 8 style guidelines
- Add tests for new functionality
- Update documentation for API changes
- Use type hints throughout the codebase
This project is licensed under the APACHE 2.0 License - see the LICENSE file for details.
This software is for educational and research purposes only. Trading financial instruments involves substantial risk of loss. Past performance is not indicative of future results. The authors are not responsible for any financial losses incurred through the use of this software.
For support, please:
- Check the documentation
- Search existing issues
- Create a new issue with detailed information
- Join our Discord community
Built with ❤️ by the EquiFlex Pro Team
Empowering traders with institutional-grade technology