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shadow-account

Extract profitability patterns from trade journals and generate cross-market backtest reports.

6.1k|1.2k|Updated Jun 9, 2022
Search Tags:#data-analytics#backtesting#report-generation#trading-analysis#multi-market#performance-attribution#shadow-account
One-click install
npx skills add https://github.com/charliedream1/ai_quant_trade --skill shadow-account
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: shadow-account
Source: https://github.com/charliedream1/ai_quant_trade/tree/main/a_%E5%85%A8%E7%BD%91%E4%BC%98%E7%A7%80%E8%B5%84%E6%BA%90/10_%E5%A4%A7%E6%A8%A1%E5%9E%8B/07_skill%E5%8C%85/vibe_trading_skills/shadow-account
Command: npx skills add https://github.com/charliedream1/ai_quant_trade --skill shadow-account

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Shadow Account helps you transform raw trading journals into clear profit patterns and actionable strategies across multiple markets, enabling data-driven decision making.

Core Features & Use Cases

  • Extract profitability patterns from user trade journals and derive 3-5 human-friendly rules.
  • Backtest rules across multiple markets (A-share, HK, US, and crypto) to measure performance and attribution.
  • Generate an 8-section PDF/HTML report that narrates insights and recommended actions for users.

Quick Start

Upload your trade journal, run analyze_shadow, and generate a cross-market backtest with attribution report.

Frequently Asked Questions about shadow-account

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

FAQPage Schema
How do I extract profit patterns from my trading journal for backtesting?▼

To extract profit patterns from a trading journal, upload your raw trade data to run an analysis that derives 3-5 actionable rules. These rules are then applied across multiple markets to measure performance and generate an attribution report.

Can I backtest trading strategies across both crypto and equities markets?▼

Yes, you can backtest trading strategies across multiple markets including China A-share, Hong Kong, US equities, and crypto. The system applies your extracted rules to these markets to measure performance and generate attribution insights.

What is performance attribution in cross-market backtesting?▼

Performance attribution in cross-market backtesting identifies which specific markets or rules drive your overall returns. It analyzes backtested data across multiple markets to pinpoint profitability patterns and narrates these insights in a detailed report.

How do I generate a PDF report from my trade journal analysis?▼

You generate a PDF report by uploading your trade journal and running the analysis to produce a cross-market backtest. The system automatically creates an 8-section deterministic HTML and PDF report with attribution for decision support.

Do I need any specific tools or dependencies to run trading analysis reports?▼

No specific dependencies are required to run trading analysis reports. You simply upload your trade journal data, and the system processes it internally to generate backtests and create the final HTML and PDF output.

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