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.

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

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

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

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.

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

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

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

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

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.

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.

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

Lightweight research-only quantitative system with one Python package, one CLI, deterministic backtesting, and fail-closed market/data semantics.