| name | candlestick |
| description | Candlestick pattern recognition engine, pure pandas vectorized implementation of 15 classic candlestick patterns (5 single-candle + 5 double-candle + 4 triple-candle + 1 trend confirmation), generating a composite signal from bullish/bearish pattern scores. |
| category | strategy |
Candlestick Pattern Recognition
Purpose
Identifies 15 classic candlestick patterns and generates trading signals:
Single-Candle Patterns (5)
| Pattern | Signal | Description |
|---|
| Hammer | Bullish | Long lower shadow with a small body at the top |
| Inverted Hammer | Bullish | Long upper shadow with a small body at the bottom |
| Shooting Star | Bearish | Long upper shadow with a small body at the bottom (appears after an uptrend) |
| Doji | Neutral | Open and close are nearly equal |
| Spinning Top | Neutral | Small body with roughly equal upper and lower shadows |
Double-Candle Patterns (5)
| Pattern | Signal |
|---|
| Bullish Engulfing | Bullish |
| Bearish Engulfing | Bearish |
| Bullish Harami | Bullish |
| Bearish Harami | Bearish |
| Piercing Line | Bullish |
| Dark Cloud Cover | Bearish |
Triple-Candle Patterns (4)
| Pattern | Signal |
|---|
| Morning Star | Bullish |
| Evening Star | Bearish |
| Three White Soldiers | Bullish |
| Three Black Crows | Bearish |
Signal Logic
Bullish patterns score +1, bearish patterns score -1. Go long when the total score is > 0, go short when it is < 0, and stand aside when it equals 0.
Parameters
| Parameter | Default | Description |
|---|
| body_pct | 0.1 | Threshold for body-to-range ratio in a doji |
| shadow_ratio | 2.0 | Ratio of shadow length to body length |
Dependencies
pip install pandas numpy requests
Signal Convention
1 = long, -1 = short, 0 = stand aside
