nautechsystems

For anyone curious how it works: you write strategies in Python, the engine underneath is Rust, and the whole thing is open source nautechsystems/nautilus_trader

@NautilusTrader The best part of NautilusTrader: my backtest code and my live trading code are the same code. No rewrite between research and production. Rust core, Python on top, and it's open source. nautechsystems/nautilus_trader

nautechsystems/nautilus_trader: nautechsystems/nautilus_trader benim en ilginç bulduklarımdan biri Rust core + Python tarafı var ve event-driven çalışıyor özellikle: order book tick data multi venue execution latency realistic simulation tarafına indikçe klasik basit backtestlerden çok daha anlamlı hale geliyor aynı strategy kodunu backtest ve live tarafta kullanmayı hedefliyor

10 Open-Source Repos That Turn AI Agents Into a Wall Street Trading Desk Quant funds spend millions every year on proprietary terminals, research desks, and execution engines. These 10 open-source GitHub repositories—totaling over 329,000+ stars—replicate that entire institutional quantitative trading stack for $0. From multi-agent investment committees to sub-millisecond Rust execution engines, here is how each repository fits into the modern algorithmic trading stack: ⏱️ CHAPTERS: 0:00 - The $10M Wall Street Software Secret 0:23 - Layer 1: Data Ingestion & Multi-Agent Research (OpenBB & TradingAgents) 0:52 - Layer 2: Automated Factor Research & Alpha Discovery (qlib & RD-Agent) 1:23 - Layer 3: Derivatives Math & Zero-Shot Forecasting (gs-quant & Chronos) 1:52 - Layer 4: Institutional Risk & Portfolio Optimization (QuantLib & skfolio) 2:18 - Layer 5: High-Speed Backtesting & Live Execution (vectorbt & NautilusTrader) 2:46 - The Complete Open-Source Hedge Fund Architecture 🔗 FEATURED GITHUB REPOSITORIES (329k+ Stars): 1. OpenBB (75k★) — Open data platform for analysts, quants, and AI agents: OpenBB-finance/OpenBB 2. TradingAgents (118k★) — Multi-agent trading firm with analyst debates & risk sign-off: TauricResearch/TradingAgents 3. qlib (50k★) — Microsoft AI-oriented quant investment platform: microsoft/qlib 4. RD-Agent (15k★) — Microsoft autonomous AI factor researcher & backtester: microsoft/RD-Agent 5. gs-quant (14k★) — Goldman Sachs institutional quant & derivatives toolkit: goldmansachs/gs-quant 6. Chronos (6k★) — Amazon Science pretrained zero-shot time-series forecasting: amazon-science/chronos-forecasting 7. QuantLib (8k★) — Quantitative finance library for modeling, trading, & risk: lballabio/QuantLib 8. skfolio (3k★) — Scikit-learn portfolio optimization & factor models: skfolio/skfolio 9. vectorbt (10k★) — Lightning-fast vectorized matrix backtesting engine: polakowo/vectorbt 10. NautilusTrader (31k★) — Production-grade Rust-native event-driven execution engine: nautechsystems/nautilus_trader Subscribe to @RepoDrift for real open-source developer tools, AI workflows, and software breakdowns. #RepoDrift #QuantitativeFinance #OpenSource #AlgorithmicTrading #Python #RustLang #AIAgents #TradingBot #MachineLearning #GitHub #SoftwareEngineering

@unfinishedtrade Have you seen this nautechsystems/nautilus_trader

Stop Cloning Trading Repos. You Need 3. There are 51 trading repositories on GitHub with more than 5,000 stars. Every video tells you to try all of them. You need three — sorted by what they actually do, not by how many stars they have. THE THREE · READ THE MARKET — TauricResearch/TradingAgents (112,063 ★) — a panel of language models that argues about a ticker, then hands you a verdict. Pushed 3 days ago. · CONNECT TO AN EXCHANGE — ccxt/ccxt (44,465 ★) — one interface, a hundred exchanges. Everything else is built on top of it. Pushed today. · EXECUTE AND HOLD — freqtrade/freqtrade (55,625 ★) — backtests before it trades, and keeps a log of every fill. Pushed today. If freqtrade is too slow for you: nautechsystems/nautilus_trader (30,340 ★, Rust core). THE PART NOBODY SAYS Backtrader: 23,520 stars, last push 791 days ago. Zipline: 20,151 stars, last push 979 days ago. Both still appear on every "top 10 trading repos" list — because lists sort by stars, and stars are history, not maintenance. ━━━━━━━━━━━━━━━━━━━━ CHAPTERS 0:00 51 repos, 3 jobs 0:14 The pile, ranked by stars 0:34 #1 Read the market — TradingAgents 1:02 #2 Connect to an exchange — ccxt 1:28 #3 Execute and hold — freqtrade (+ Nautilus) 1:54 The two that are dead but still recommended 2:20 The whole stack ━━━━━━━━━━━━━━━━━━━━ METHOD · Source: GitHub REST API, snapshot 19 October 2026 · Filter: "trading", 5,000+ stars, not archived → 51 repositories · "Days since push" = snapshot date − last push date · Stars are cumulative and include forks-adjacent attention; they are not a quality score Links: TauricResearch/TradingAgents ccxt/ccxt freqtrade/freqtrade nautechsystems/nautilus_trader mementum/backtrader quantopian/zipline #GitHub #Trading #OpenSource #Quant

You Don't Need 10 Trading Repos. You Need 3. There are 51 trading repositories on GitHub with more than 5,000 stars. Every video tells you to try all of them. You need three — sorted by what they actually do, not by how many stars they have. THE THREE · READ THE MARKET — TauricResearch/TradingAgents (112,063 ★) — a panel of language models that argues about a ticker, then hands you a verdict. Pushed 3 days ago. · CONNECT TO AN EXCHANGE — ccxt/ccxt (44,465 ★) — one interface, a hundred exchanges. Everything else is built on top of it. Pushed today. · EXECUTE AND HOLD — freqtrade/freqtrade (55,625 ★) — backtests before it trades, and keeps a log of every fill. Pushed today. If freqtrade is too slow for you: nautechsystems/nautilus_trader (30,340 ★, Rust core). THE PART NOBODY SAYS Backtrader: 23,520 stars, last push 791 days ago. Zipline: 20,151 stars, last push 979 days ago. Both still appear on every "top 10 trading repos" list — because lists sort by stars, and stars are history, not maintenance. ━━━━━━━━━━━━━━━━━━━━ CHAPTERS 0:00 51 repos, 3 jobs 0:14 The pile, ranked by stars 0:34 #1 Read the market — TradingAgents 1:02 #2 Connect to an exchange — ccxt 1:28 #3 Execute and hold — freqtrade (+ Nautilus) 1:54 The two that are dead but still recommended 2:20 The whole stack ━━━━━━━━━━━━━━━━━━━━ METHOD · Source: GitHub REST API, snapshot 19 October 2026 · Filter: "trading", 5,000+ stars, not archived → 51 repositories · "Days since push" = snapshot date − last push date · Stars are cumulative and include forks-adjacent attention; they are not a quality score Links: TauricResearch/TradingAgents ccxt/ccxt freqtrade/freqtrade nautechsystems/nautilus_trader mementum/backtrader quantopian/zipline #GitHub #Trading #OpenSource #Quant

Here you go @SaylessMoon 🤖 NautilusTrader (free): nautechsystems/nautilus_trader Heads up: it can't connect to Tradovate, so it won't run on prop firms like Lucid or Apex. My prop firm setup: strategy in TradingView → alert → TradersPost → Tradovate → prop account. Are you trading crypto or futures? 👀

做量化的人通常先在 Python 里跑研究，再用 C++ 或 Rust 把策略重写一遍才敢上实盘。这个项目把这两步并成一套，Rust 内核扛事件驱动运行时，Python 负责写策略和调度，同一份代码直接推实盘。 nautechsystems/nautilus_trader t.co

Looking for good Execution Systems Dev Focus: Trading Infrastructure / Execution Systems Requirements 1.Programming & Systems - 熟悉 Rust ，精通 Python - 对编译原理、Data Warehouse 有自己的理解 2.Trading Pipeline Tooling 专注交易链路上的工具开发，包括： - data pipeline 、message bus 扩展 - risk control tools - execution algo - backtest 3.Framework - 了解 Nautilus Trader 框架 nautechsystems/nautilus_trader Compensation - Base Salary: $5,000 – $10,000 USD / month - Bonus: Project based bonus Office Location: Hong Kong / Remote Contact Email: profilesai@proton.me (请直接提交简历和个人 GitHub 数学，统计学专业优先考虑)