git clone https://github.com/yourusername/elliott-wave-analyzer.git
cd elliott-wave-analyzer
pip install -r requirements.txt
python examples/detect_impulse.py --symbol BTCUSDT --interval 1h --lookback 500
Example output:
Wave Count (Detected): Wave 1: 2025-02-10 08:00 | 48200 → 49500 (2.7%) Wave 2: 2025-02-11 14:00 | 49500 → 48750 (-1.5%) Wave 3: 2025-02-13 22:00 | 48750 → 52300 (7.3%) Wave 4: 2025-02-15 06:00 | 52300 → 51500 (-1.5%) Wave 5: 2025-02-17 18:00 | 51500 → 53800 (4.5%)
✅ Valid impulse wave found. Fibonacci: Wave 3 = 1.618 x Wave 1elliott wave github
Technical Analysis Repositories:
Large repositories like ta-lib (Technical Analysis Library) or specific trading bot repositories often contain Elliott Wave modules. git clone https://github
Visualization Tools:
Many repositories focus on the drawing aspect rather than the detection. These use mplfinance or plotly to allow users to overlay wave annotations on candlestick charts programmatically. Example output: Wave Count (Detected): Wave 1: 2025-02-10
Most repositories start with a ZigZag indicator. This smooths out noise by ignoring minor price movements below a specific threshold (e.g., 3%).
Best for: Crypto and forex backtesting. Ewmine is a heavier, research-oriented framework that scans multiple timeframes to propose the most probable wave count. It employs a genetic algorithm to fit historical data to ideal Elliott structures.