Alpha Forge — an agentic AI operating system for systematic trading.
面向 A 股本地数据的 AI 因子研究工作台：因子生成、存储、注册、评估与报告。
A complete toolkit for quantitative research and development of options trading strategies.
The Quant's Compiler: From Alpha Idea to Production in Minutes
Exhaustive research on Polymarket prediction market inefficiencies — past exploits, academic foundations, live mispricings, trading strategies, and future alpha. 100+ sources across EN/KR/CN.
Nautilus_Trader_Jerry_fall_2023 is a customized verision of Nautilus trader by Zhuoran "Jerry" Li on Fall 2023
Automated alpha research pipeline for WorldQuant BRAIN — built for the IQC 2026
Cross-sectional Transformer and FFN for stock return prediction and alpha generation. Implements GKX (2020) NN5 replication and MSRR loss (Kelly et al. 2025) for direct portfolio Sharpe optimization. Avg SDF Sharpe 2.05, significant alpha (t=5.34) unexplained by FF5+Momentum.
9 天的散戶量化失敗記錄 — 從 +211% 年化到認輸買 0050 的誠實報告
A closed-loop alpha research system for WorldQuant Brain.
端到端、可复现的 A 股量化研究平台：因子挖掘 → 防过拟合 → Barra 风险模型 → AI Agent 智能挖掘 → 组合优化与归因 → 模拟交易 → 成果展示 Dashboard。全链路可审计、可复现。
A股量化Alpha研究: 多因子选股 + LightGBM非线性因子挖掘, Walk-forward验证, 自动交叉验证检查
A PyTorch research pipeline for cross-sectional stock return forecasting with grouped factors and stock-wise attention.
Alpha factor autopsy and production-readiness validation for quantitative strategies
A quantitative research framework for evaluating alpha signal quality, robustness, and decay.
Fail-closed Codex/Claude Code skill for crypto quant alpha research - Stage 0, falsification, provider concordance, promotion gates
Bias-aware, reproducible daily-frequency multi-factor alpha research platform with PIT controls, segmented IC validation, and institutional robustness workflow.
MCP Server for WorldQuant Brain alpha factor mining — 世坤 Brain 回测因子 MCP 服务
A modular Python framework for researching and backtesting multi-factor equity strategies using classical factors (Value, Momentum, Size), Fama–MacBeth regressions, IC/IR analysis, and long–short portfolio evaluation.
* Calculates technical and custom alpha factors * Trains ML models to predict short-term returns * Evaluates predictive power (IC, precision, Sharpe ratio) * Visualises insights
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