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Add stock-analysis (#124)
Co-authored-by: yjw <yjw@yjws-Mac-mini.local>
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@@ -100,6 +100,7 @@ And I count crypto as whole new category: [>> Click ME to Systematic Crypto](cry
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- [FinClaw](https://github.com/NeuZhou/finclaw)   | `Python` | - AI-native quantitative finance engine with genetic algorithm strategy evolution. 484 built-in factors, walk-forward validation, multi-market support (A-shares, US, crypto). Strategies evolve themselves via GA — no manual parameter tuning needed.
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- [OpenFinClaw](https://github.com/cryptoSUN2049/openFinclaw)   | `TypeScript` | - AI-native systematic trading framework. Natural language strategy generation, multi-market execution (US/HK/CN/Crypto), self-evolving strategy pipeline with community leaderboard. Built on OpenClaw (68K+ stars).
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- [StockKit](https://stockkit.net/) ([GitHub](https://github.com/kentmswood-ui/stockkit)) | `TypeScript` | - Free AI-powered stock research reports delivered daily. Wall Street-grade analysis for US, China & HK stocks using Claude Opus and multi-model AI engine. 20+ technical indicators, automated email delivery.
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- [stock-analysis](https://github.com/AdvancingTitans/stock-analysis)   | `Python` | - Evidence-driven market recap CLI for A/HK/US stocks and funds, producing Markdown reports and JSON Evidence Packs for AI agent workflows.
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- [oracle3](https://github.com/YichengYang-Ethan/oracle3)   | `Python` | - Autonomous trading agent for Kalshi, Polymarket, and Solana DFlow with Wang Transform pricing engine calibrated on 291,309 resolved contracts (λ̂ = 0.183), eight constraint-based arbitrage strategies, hierarchical MLE, model Greeks, and Kelly-sized execution. Backed by SSRN working paper.
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- [Eterna](https://github.com/EternaHybridExchange/eterna-ai)   | `MCP` | - Launch your own autonomous perp trading AI via Claude Code in 60 seconds. Hybrid exchange MCP with $10B+ aggregated liquidity across 500+ pairs — Claude executes your strategies 24/7. Endpoint: `https://mcp.eterna.exchange/mcp`
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- [Inalpha](https://github.com/mirror29/inalpha)   | `Python` `TypeScript` | - AI agent framework for quant research: agents pick the factors working now to time entries (time-series rank IC), write full Python strategies audited in sandboxes, and evolve them under multi-objective fitness. Every order passes machine approval — the LLM has no direct order path. Multi-market: crypto, US/CN/HK equities, global indices, FRED macro.
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