Trading strategies on C#, Python and schema for StockSharp Designer
Production-quality multi-asset portfolio optimisation and rolling backtesting in Python
PyTorch research stack for ML multi-factor trading: 213 factors, bias correction, portfolio optimization, and vectorized backtesting.
Multi-agent macro trading bot: multi-factor stock scoring, momentum portfolio construction, backtesting vs SPY/Nasdaq, and live Alpaca execution.
Research-grade investment decision engine for AI agents: isolated multi-agent committee, auditable verdicts, backtests with lookahead protection, published negative results
Framework for quantitative strategies development, backtesting and live execution.
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Cluster-based portfolio allocation on an explicit, inspectable tree: hierarchical risk parity, Schur complementary allocation and hierarchical 1/N
ไธไธบ Claude Code ่ฎพ่ฎก็ Tushare Pro ้่ๆฐๆฎๆ่ฝๅ ๏ผๆฏๆ 220+ ไธชๆฅๅฃ๏ผ็จ่ช็ถ่ฏญ่จ่ทๅ A ่ก่กๆ ใ่ดขๅกๆฐๆฎใๅฎ่ง็ปๆต็ญ้่ๆฐๆฎใ
Autonomous LLM Trading Asterism โ research-only, evidence-first multi-agent opportunity discovery, audited Shadow expression, durable recovery, and a bilingual local operator console.
Python ๅผๆบ้ๅๆกๆถ๏ผ ่ฆ็โ็ ็ฉถใๅๆตใไบคๆโๅ จ็ๅฝๅจๆ๏ผๆๅปบไป้ถๅฐๅฎ็็ๅทฅไธ็บง้ๅ้ญ็ฏๅทฅไฝๆตใ
ๅบไบๆฒชๆทฑ300ๆๅ่ก็ๆบ่ฝ้่ก็ณป็ป๏ผ้่ฟๅค็ปดๅบฆ้ๅๆๆ ็ญ้ไผ่ดจ่ก็ฅจ๏ผ่ชๅจ็ๆ่ฏฆ็ปๅๆๆฅๅๅนถๅ้้ฎไปถ้็ฅใ