regulatory-knowledge

Document compliance requirements for multi-market trading strategies across A-share, Hong Kong, US equities, and crypto.

Updated Apr 9, 2026

Search Tags:#backtesting #regulatory-compliance #market-rules #trading-regulations #cross-market-strategy #tax-impact

Ready to run

npx skills add https://github.com/JacobHsu/vibe-trading-agent --skill regulatory-knowledge-jacobhsu

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: regulatory-knowledge
Source: https://github.com/JacobHsu/vibe-trading-agent/tree/main/agent/src/skills/regulatory-knowledge
Command: npx skills add https://github.com/JacobHsu/vibe-trading-agent --skill regulatory-knowledge-jacobhsu

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Trading strategies spanning A-shares, Hong Kong, U.S. equities, and crypto suffer from hidden regulatory mismatches that wreck backtests and expose live executions to compliance risk. This Skill organizes those market rules so you can model them correctly and avoid invalid assumptions.

Core Features & Use Cases

Comprehensive rule summaries: Details on A-share limit rules, T+1 constraints, margin and shorting costs, Hong Kong T+0/doangka, U.S. PDT/LULD, and crypto regulatory trends.
Operational checklists: Compliance matrices, cost breakdowns, and holiday/time differences help you validate cross-market strategies before deployment.
Use Case: Compare 600519.SH and 0700.HK in a pair trade and estimate execution limits, shorting feasibility, and tax impacts across jurisdictions.

Quick Start

Ask regulatory-knowledge to assess A-share and Hong Kong rule differences for a pair trade.

Frequently Asked Questions about regulatory-knowledge

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

FAQPage Schema

How do I document regulatory compliance rules for cross-market trading strategies?▼

Document regulatory compliance rules for cross-market trading by applying organized matrices of A-share T+1 limits, Hong Kong T+0 rules, U.S. PDT constraints, and crypto regulations to validate strategies before deployment.

What market regulations should I model for A-share, Hong Kong, US, and crypto backtests?▼

Model market regulations for A-share, Hong Kong, US, and crypto backtests by incorporating jurisdiction-specific limit rules, T+N settlement cycles, shorting feasibility, borrowing fees, and tax impacts into your simulations.

How do I handle T+1 settlement and shorting cost differences in a cross-market pair trade backtest?▼

Handle T+1 settlement and shorting cost differences in cross-market pair trade backtests by applying compliance matrices and cost breakdowns that estimate execution limits and margin fees across jurisdictions.

Can I use regulatory compliance checklists to validate crypto and US equities trading constraints?▼

You can use regulatory compliance checklists to validate crypto and US equities trading constraints by mapping U.S. LULD rules, PDT requirements, and crypto regulatory trends against holiday schedules and time differences.

Why does my multi-market backtest fail when ignoring jurisdiction tax impacts and limit rules?▼

Your multi-market backtest fails when ignoring jurisdiction tax impacts and limit rules because hidden regulatory mismatches wreck simulations and expose live executions to invalid cost assumptions across A-shares, Hong Kong, U.S., and crypto markets.