skills.rest
GGwujun
GGwujunCOMMUNITY
Explore all skills by this author →
GitHub

candlestick

Score 15 classic candlestick patterns in OHLCV data with vectorized pandas logic.

Updated Jun 12, 2026
Search Tags:#pandas#technical-analysis#pattern-recognition#trading-signals#stock-market#candlestick#vectorized
One-click install
npx skills add https://github.com/GGwujun/SigmX --skill candlestick-ggwujun
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: candlestick
Source: https://github.com/GGwujun/SigmX/tree/main/agent/src/skills/candlestick
Command: npx skills add https://github.com/GGwujun/SigmX --skill candlestick-ggwujun

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, requests.

What problem does it solve?

Automates the recognition of 15 classic candlestick patterns and translates them into a single, actionable trading signal, reducing manual chart analysis.

Core Features & Use Cases

  • Recognizes 15 classic patterns (5 single-candle, 5 double-candle, 4 triple-candle, plus a trend-confirmation pattern) and scores them to produce a combined signal.
  • Vectorized implementation using pandas for fast, scalable signal generation across large OHLCV datasets.
  • Use Case: apply to stock or crypto OHLCV series to backtest or drive live trading decisions with clear long/short/neutral outputs.

Quick Start

Provide OHLCV data to generate signals for your symbols.

Frequently Asked Questions about candlestick

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I identify candlestick patterns in OHLCV stock data using pandas?▼

You can identify candlestick patterns in OHLCV data by running vectorized pandas logic that evaluates 15 classic patterns and outputs a per-row trading signal series of -1, 0, or 1 for long, neutral, or short positions.

Can I use vectorized pandas to generate trading signals from historical price data?▼

Yes, vectorized pandas can generate trading signals from historical price data by batch processing OHLCV series, scoring recognized candlestick patterns, and outputting a consensus signal of -1, 0, or 1 per row.

What's the best way to automate candlestick pattern recognition for backtesting?▼

Automating candlestick pattern recognition for backtesting is best handled by a vectorized pandas implementation that processes large OHLCV datasets and scores 15 classic patterns to produce a combined long/short/neutral signal.

Does this candlestick pattern recognition work with cryptocurrency OHLCV data?▼

Candlestick pattern recognition works with any asset class that provides open, high, low, close, and volume data, making it fully applicable to cryptocurrency OHLCV time series for signal generation.

How do I configure body and shadow thresholds for candlestick pattern detection?▼

You can configure candlestick pattern detection thresholds by adjusting the body_pct and shadow_ratio parameters, allowing you to fine-tune pattern sensitivity for your specific OHLCV dataset.

Are there limitations to using candlestick patterns as a standalone trading signal?▼

Candlestick patterns as a standalone trading signal are limited because they reflect historical price action without forecasting fundamental market shifts, so combining them with broader trend-confirmation analysis is recommended.

Related Skills

Explore More Finance & Accounting Skills→
philipcoller-777philipcoller-777

candlestick

Identify and score 15 candlestick patterns in OHLCV data to generate a composite buy/sell/neutral signal.

Community
Intermediate
charliedream1charliedream1
6.1k

seasonal

Generate calendar-based trading signals from OHLCV data with configurable month and weekday patterns.

Community
Intermediate
anbeimeanbeime
5.0k

stock-analysis

Analyze stocks with technical indicators and generate trading recommendations.

Community
Intermediate
hxhyyyhxhyyy

candlestick

Identify 15 classic candlestick patterns in OHLCV dataframes and generate trading signals.

Community
Intermediate