us-equities

AI agent skill for scanning and validating event-driven arbitrage opportunities in US equities

Content-addressed, replay-verifiable snapshots of free US-listed equity data sources.

US-equity quantitative research, backtest and paper-trading system (codename Plutus).

Local-first, explainable US equity crowding-risk monitor | 本地优先的美股拥挤风险雷达

미국주식 팩터 엔진 + ETF 전술배분 검증 — point-in-time·생존편향 보정 데이터 위에서 워크포워드를 Deflated Sharpe·PBO 로 게이팅. 채택만이 아니라 기각도 함께 공개 · US equity factor engine with walk-forward validation

Local-first US-equity quant research workspace — Qlib + LightGBM DoubleEnsemble, factor library, and walk-forward backtesting with a React dashboard.

Versioned single-factor research across A-shares, US equities, US ETFs and digital assets.

A Claude Code harness that turns Claude into a disciplined Minervini SEPA momentum-stock analyst for US equities — deterministic evidence, model judgment.

US-equity quant research that lives inside your AI assistant (Claude/Codex via MCP): explainable ratings, key levels & daily briefs from one command. CLI + MCP, bilingual EN / 中文.

Open-source (MIT) raw data collection pipeline for US equity research. Personal, non-commercial. Sources: SEC EDGAR, Alpha Vantage. Code and docs only — no data committed.

美股投研局：GPT-6 Astra / Codex 专用的机构级美股研究 Skill Stack，覆盖财报、同业、DCF、反向 DCF 与 point-in-time 证据纪律。

MCP server for US-equity research over SEC EDGAR, Finnhub, and yfinance. Five tools including a deterministic aggregator that flags insider-buy/sell × volume-spike co-occurrence.

A Python research framework that tests whether stock factor models really explain market behavior, or just look accurate because of hidden proxy effects.

👋 프로필 README — 퇴근 후 만드는 오픈소스 퀀트 스택 소개 (한국어·English) · Profile README: open-source quant stack overview

Reproduction of the Opening Range Breakout (ORB) strategy on the full U.S. stock universe.

Quill - Deterministic, risk-governed multi-agent trading engine for US equities. A strategy swarm proposes orders; an independent risk guardian has final say. Paper mode by default, gated live Robinhood MCP execution.

Isolated Pi profile package for bottom-up research on US-listed companies, bundling five research skills, selected Pi resources, and bootstrap tooling.

Local-first Python service for end-of-day U.S. equity screening, SEC offering alerts, email digests, and reproducible point-in-time backtesting.

Automation for tracking holdings and share-count changes in selected US-market ETFs over time, with persistent history and Discord alerts.

Schema-controlled Python research system for equity factor research, synthetic validation, portfolio accounting, backtesting, and empirical-data readiness.