QuantDinger: open-source AI trading OS with Jev built in
A 13k-star Apache-2.0 trading OS that ships Jev System One as its decision layer, with a six-step Claude Code workflow for wiring signals, risk checks and backtests.
IT'S F*CKING INSANE Everyone's still duct-taping Claude + Jev together by hand. Meanwhile there's an open-source repo that already did it. QuantDinger. 13,000 stars. Apache-2.0. Free. An AI trading OS with Jev built in 👇 ━━━━━━━━━━━━━━━ WHAT IT IS 🧠 an open-source "AI Trading OS" 📈 research, Python strategies, backtests 🤖 agent trading in one place ⚡ Jev System One integration out of the box The decision layer from my article? Already wired in. ━━━━━━━━━━━━━━━ WHY IT FITS THE SETUP PERFECTLY In the article above the split is simple: Claude builds. Jev decides. Code does the math. QuantDinger gives you the "code does the math" part: the strategy engine, the backtester, the research tools. So Claude doesn't start from an empty folder. It starts from a working trading OS. ━━━━━━━━━━━━━━━ HOW I'D USE IT 1/ clone it, open it in Claude Code 2/ let Claude read the codebase and map it into a CLAUDE.md 3/ point the Jev layer at your signal filters and risk checks 4/ write your strategy in Python, Claude writes the tests 5/ backtest with fees and slippage, walk-forward, sealed hold-out 6/ paper trade 2–4 weeks before a single real dollar ━━━━━━━━━━━━━━━ THE PART PEOPLE SKIP Pin the Jev version. Keep all questions in one file. Confidence < 0.5 → you decide, not the bot. API keys: trading ON, withdrawals OFF. Every rule from the article still applies. The repo just saves you weeks of building. ━━━━━━━━━━━━━━━ http://github.com/OpenByteInc/QuantDinger Read the article. Clone the repo. Build this weekend 🕷️
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