774b1ed3d3
- Fix RSI calculation to handle NaN values when loss is 0 - Parallelize symbol scanning with ThreadPoolExecutor for better performance - Improve module import structure for Streamlit app compatibility - Move yfinance import to top of app.py per Python conventions |
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| README.md | ||
| __init__.py | ||
| app.py | ||
README.md
Momentum Dashboard
Real-time momentum analysis dashboard for TradingAgents.
Features
✅ 21 EMA Trend Filter - Long above, short below ✅ Bollinger Band Squeeze - Identify low-volatility consolidation ✅ Volume Momentum - Confirm breakouts ✅ RSI Indicator - Overbought/oversold signals ✅ Multi-timeframe - 1H/Daily/Weekly analysis ✅ Magnificent Seven + Custom watchlists
Quick Start
1. Install Dependencies
pip install streamlit plotly yfinance pandas numpy
2. Run Dashboard
cd tradingagents/dashboards/momentum
streamlit run app.py
3. CLI Scanner (No UI)
python -m tradingagents.dashboards.momentum
Signals
| Signal | Meaning |
|---|---|
| STRONG_BUY | Bullish trend + high strength |
| BUY | Moderate bullish |
| WATCH_FOR_BREAKOUT | Squeeze detected, potential move |
| HOLD | No clear signal |
| SELL | Moderate bearish |
| STRONG_SELL | Bearish trend + low strength |
Architecture
momentum/
├── __init__.py # Core scanner & indicators
├── app.py # Streamlit UI
└── README.md # This file
Integration
To integrate with TradingAgents main workflow:
from tradingagents.dashboards.momentum import MomentumScanner
scanner = MomentumScanner(["AAPL", "NVDA", "TSLA"])
signals = scanner.scan_all()
# Use signals in trading decisions
for signal in signals:
if signal["signal"] == "STRONG_BUY":
# Execute buy logic
pass
Future Enhancements
- Real-time WebSocket data (Polygon.io)
- Alert notifications (email/Telegram)
- Portfolio tracking
- Backtesting mode
- Multi-exchange support
Built for TradingAgents by OpenClaw Community