Add aurumq-rl to Trading & Backtesting

[yupoet]

Entry

• aurumq-rl - `Python` - Reinforcement learning stock-selection framework for the China A-share market with multi-source factor input (alpha101 + main-force flow + hot-money seats + northbound + institutional + fundamentals), board-aware price limits, and ONNX CPU inference.

Why this fits

Placed in Trading & Backtesting right after FinRL-Library since both are RL-based for trading. AurumQ-RL focuses specifically on the China A-share market and provides:

• A-share-specific constraints (T+1, board-aware price limits — Main ±10% / STAR/ChiNext ±20% / BSE ±30% / ST ±5%)
• Multi-source factor recognition (12 prefix groups: alpha_/mf_/hm_/hk_/inst_/mg_/cyq_/senti_/sh_/fund_/ind_/mkt_)
• Offline GPU training (PPO/A2C/SAC via Stable-Baselines3) + CPU ONNX inference (~150ms per 5000-stock cross-section)
• 115 unit tests, MIT-licensed

Checklist

• Description ends with a period
• Single-language tag (`Python`)
• HTTPS GitHub URL
• Active project (just released v0.1.0)
• README with usage examples + quickstart
• CI (GitHub Actions) configured

Links

• Repo: https://github.com/yupoet/aurumq-rl
• Release: https://github.com/yupoet/aurumq-rl/releases/tag/v0.1.0
• License: MIT