stock-visualization

Stock chart visualization for Chinese markets with candlestick charts, technical indicators, and multi-chart layouts. Use when needing to visualize stock price patterns, display technical indicators, create comparison charts, or generate analysis reports for A-share stocks.

install

source · Clone the upstream repo

git clone https://github.com/shiyongxin/skills-quant-framework

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/shiyongxin/skills-quant-framework "$T" && mkdir -p ~/.claude/skills && cp -r "$T/.claude/skills" ~/.claude/skills/shiyongxin-skills-quant-framework-stock-visualization && rm -rf "$T"

manifest: .claude/skills/SKILL.md

source content

Stock Visualization

Comprehensive chart generation for Chinese stock analysis.

Quick Start

import sys
sys.path.append('F:/Users/shiyo/80.soft_dev/Stocks/.claude/skills')
from chart_visualizer import ChartVisualizer

visualizer = ChartVisualizer()
visualizer.plot_candlestick('600519', days=120, save_path='chart.png')

Chart Types

Candlestick Chart

visualizer.plot_candlestick(
    symbol='600519',
    days=120,
    show_ma=True,      # Show moving averages
    show_volume=True,  # Show volume
    save_path='candlestick.png'
)

MACD Chart

visualizer.plot_macd(
    symbol='600519',
    days=120,
    save_path='macd.png'
)

KDJ Chart

visualizer.plot_kdj(
    symbol='600519',
    days=120,
    save_path='kdj.png'
)

Combined Chart

visualizer.plot_combined(
    symbol='600519',
    days=120,
    indicators=['ma', 'macd', 'volume'],
    save_path='combined.png'
)

Multi-Stock Comparison

# Compare multiple stocks
symbols = ['600519', '000858', '002415']
visualizer.plot_comparison(
    symbols=symbols,
    days=120,
    normalize=True,    # Normalize to percentage
    save_path='comparison.png'
)

Equity Curve

# For backtest results
equity_data = backtest_result['equity_curve']
visualizer.plot_equity_curve(
    equity_data=equity_data,
    save_path='equity_curve.png'
)

Custom Styling

visualizer = ChartVisualizer(
    style='dark',        # 'dark' or 'light'
    figsize=(14, 8),
    dpi=100
)

See chart_types.md for all available chart options and styling.