QuantDinger

272 posts

QuantDinger

@QuantDinger_EN

AI-driven, local-first quantitative trading platform for research, backtesting and live execution. Python-native, privacy-first, open source. 中文频道：@Dingerquant

New York, USA Inscrit le Temmuz 2024

148 Abonnements143 Abonnés

QuantDinger@QuantDinger_EN·2h

AI trading agents are getting a lot of attention. But there is one problem I keep seeing: Most projects stop at “analysis”. They simulate analysts, researchers, debates, and trading opinions. That’s useful. But real quant work does not end with an opinion. It needs: Idea → Strategy → Backtest → Risk Rules → Execution → Monitoring → Review That’s the direction we’re building with QuantDinger. Not just an AI that talks about the market. A self-hosted AI quant workflow that helps turn trading ideas into testable and executable systems. GitHub: github.com/brokermr810/Qu…

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QuantDinger@QuantDinger_EN·3h

Most people use AI to generate trading strategies the wrong way. They ask: “Write me a profitable BTC strategy.” AI gives them code. Then they paste it somewhere, run it once, and call it a failure. But strategy building is not a one-step prompt. A real workflow looks like this: Idea → Code → Backtest → Risk Rules → Optimization → Paper Trading → Live Execution → Review That’s the part we’re building with QuantDinger. Not just “AI writes code.” An open-source workflow where AI helps you research, generate, test, optimize, and execute strategies. Repo: github.com/brokermr810/Qu…

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QuantDinger@QuantDinger_EN·3h

I don’t want AI to simply say “BUY” or “SELL”. That’s not useful enough for trading. What I want is: • Why this signal exists • What timeframe supports it • Where the risk is • What invalidates the idea • How it can be turned into a testable strategy This is the direction we’re exploring in QuantDinger: AI analysis should not replace traders. It should help traders structure ideas, test assumptions, and improve decisions. Open source repo: github.com/brokermr810/Qu…

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QuantDinger@QuantDinger_EN·3h

Most quant trading tools stop at one step. Some help you write strategies. Some help you backtest. Some help you connect to exchanges. But the real workflow is much bigger: Research → Strategy → Backtest → Optimize → Live Trading → Monitor That’s why we built QuantDinger. An open-source AI-native quant trading platform designed to bring the full trading workflow into one system. What it supports: • AI market analysis • Python strategy development • Multi-market backtesting • Live trading execution • Multi-exchange connectivity • Portfolio & position tracking • Alerts, reports, and automation • Self-hosted deployment The goal is simple: Turn trading ideas into testable, executable, and continuously improvable strategies. Open source repo: github.com/brokermr810/Qu… If you’re building trading systems, quant tools, AI agents, or automation workflows, I’d love your feedback. #OpenSource #QuantTrading #AI #Python #CryptoTrading #TradingBots #FinTech

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QuantDinger retweeté

凡森 | AI 工具與開源@soveryaitw·23 Nis

📍 專案： github.com/brokermr810/Qu…

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AI Hustle Kit@AIHustleKit·3 Mar

type your strategy in plain English. AI writes the Python, backtests it, deploys live. 7 agents debate every trade. Binance, OKX, IBKR, MT5. keys never leave your server. docker-compose up in 2 min. github.com/brokermr810/Qu… #AI #Trading #OpenSource

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QuantDinger retweeté

packet rat@packetrat_·21 Nis

Self-hosted AI quantitative trading platform github.com/brokermr810/Qu…

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区块链行情研究@qkl2058·5d

这周金融圈涨星最快的GitHub项目，整理了一下： 1. TradingAgents（+7.9K星）——UCLA和MIT搞的多智能体交易框架。里面有基本面分析师、情绪分析师、技术面分析师、风控师，还支持DeepSeek V4的思维模式。 2. FinceptTerminal（+4.3K星）——用C++20和Qt6写的开源版Bloomberg。内置37个AI智能体，风格分别是巴菲特、芒格、林奇、格雷厄姆那一套。支持16家券商实时交易，还自带MCP和AI量化标签页。 3. daily_stock_analysis（+2.3K星）——覆盖美股、A股、港股的LLM股票分析器。自动生成包含入场点、出场点的每日决策仪表盘，通过GitHub Actions推到微信、Telegram、Discord、邮箱。 4. Vibe-Trading（+1.9K星）——个人交易智能体。自然语言写策略、回测、导出到TradingView或MT5，一条pip install命令就能搭起你自己的AI交易台。 5. QuantDinger（+837星）——自托管的AI量化操作系统。能研究市场、生成Python策略、回测想法、跑实盘。支持加密货币、股票（通过IBKR）、外汇（通过MT5）。一个Docker Compose搞定，基础设施和数据都是你自己的。 6. TradingAgents-CN（+641星）——TradingAgents的中文版。针对A股市场、中文数据源和国产大模型做了完全本地化。 7. last30days-skill（+630星）——AI智能体技能，能研究过去30天里Reddit、X、YouTube、HN、Polymarket以及全网的任何话题，可以接入任何智能体框架。 8. qlib（+569星）——微软出的AI量化投资平台。端到端流程：数据到Alpha到投资组合到执行。目前圈内最严肃的开源量化基础设施。 9. scientific-agent-skills（+511星）——研究、科学、工程、分析、金融都能用的即用型智能体技能，可以接入任何智能体框架。覆盖生物信息学、化学信息学，现在还加上了Hugging Science。 10. OpenBB（+387星）——面向分析师、量化研究员和AI智能体的开源金融数据平台。股票、加密货币、期权、衍生品、固收，一个平台全集成。

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Bill The Investor@billtheinvestor·5d

本周金融领域增长最快的 GitHub 仓库： 1. TradingAgents (+7.9K ★) 来自 UCLA/MIT 的多智能体 LLM 交易框架。包含基本面分析师、情绪分析师、技术面分析师、风险管理师，支持 DeepSeek V4 思维模式。 2. FinceptTerminal (+4.3K ★) 基于 C++20 + Qt6 构建的开源 Bloomberg 替代方案。拥有 37 个巴菲特/芒格/林奇/格雷厄姆风格的 AI 智能体。支持 16 个券商集成的实时交易。内置 MCP + AI 量化标签页。 3. daily_stock_analysis (+2.3K ★) 面向美股、A 股和港股市场的 LLM 股票分析器。自动构建包含入场/出场水平的每日决策仪表盘。通过 GitHub Actions 推送到微信/Telegram/Discord/Email。 4. Vibe-Trading (+1.9K ★) 个人交易智能体。自然语言 - 策略 - 回测 - 导出至 TradingView/MT5。只需一个 pip install，即可拥有属于你自己的 AI 交易台。 5. QuantDinger (+837 ★) 自托管 AI 量化操作系统。研究市场、生成 Python 策略、回测想法、运行实盘交易。支持加密货币、通过 IBKR 交易股票、通过 MT5 交易外汇。一个 Docker Compose，你的基础设施，你的数据。 6. TradingAgents-CN (+641 ★) TradingAgents 的中文分支。针对 A 股市场、中文数据源和国产大模型进行了完全本地化。 7. last30days-skill (+630 ★) AI 智能体技能，可研究过去 30 天内 Reddit、X、YouTube、HN、Polymarket 及全网的任何话题。可接入任何智能体框架。 8. qlib (+569 ★) 微软推出的面向 AI 的量化投资平台。端到端流程：数据 - Alpha - 投资组合 - 执行。目前最严肃的开源量化基础设施。 9. scientific-agent-skills (+511 ★) 用于研究、科学、工程、分析和金融的即用型智能体技能。可接入任何智能体框架。涵盖生物信息学、化学信息学，以及现在的 Hugging Science。 10. OpenBB (+387 ★) 面向分析师、量化研究员和 AI 智能体的开源金融数据平台。在一个平台上集成股票、加密货币、期权、衍生品、固定收益。

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Joruno@wsl8297·2d

做量化交易研究最烦的就是工具链太碎：AI 分析一套、写策略一套、回测一套、实盘又一套，来回切换既耗时又容易出错。最近发现一个开源项目 QuantDinger，把 AI 研究、策略开发、回测到实盘执行全部收进一个平台里，而且支持完全自部署。你只要用一句话描述交易想法，AI 就能直接生成 Python 策略代码；改完立刻回测，结果满意就一键接入实盘，全流程不出平台、不用折腾各种工具。 GitHub：github.com/brokermr810/Qu… 它还覆盖加密货币、美股、外汇等多市场，并内置多用户管理与多渠道告警通知。核心数据、API 密钥、策略代码都保存在本地，Docker 一键部署即可。适合想搭建私有化交易平台，或希望用 AI 提升量化研究效率的同学上手体验。

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Quant Science@quantscience_·1d

90% of algorithmic traders aren't using AI and Agents for live trading and research. So this guy open-sourced something to help (for free):

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QuantDinger@QuantDinger_EN·2d

We are absolutely thrilled that QuantDinger has been featured on this week's list of trending open-source finance projects! 🥳 A huge thank you to the blogger for the shout-out, and to everyone who follows quantitative trading tools. We are an AI-powered quantitative trading operating system designed with a primary focus on local, privacy-first operations—handling everything from strategy generation to live trading with just a single click. We invite all quantitative trading enthusiasts to give it a try! 👇

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CryptoGoos@cryptogoos·18 Nis

The fastest growing GitHub repos in finance this week. Bookmark them.

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QuantDinger@QuantDinger_EN·2d

Can’t believe we’re on the list two weeks running! Huge thanks for the shoutout. 🙏 If you’re a quant trader or developer, give QuantDinger a try, share it if it works for you, and let us know your feedback. A star on GitHub helps a ton with discovery, and we’ll keep building it out for the community!

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0xMarioNawfal@RoundtableSpace·4d

THIS GUY BUILT THE FASTEST GROWING GITHUB REPOS LIST. CHECK IT OUT AND BOOKMARK IT. x.com/i/status/20505…

wincy.eth@gusik4ever

the fastest growing GitHub repos in finance this week: 1. TradingAgents (+7.9K ★) multi-agent LLM trading framework from UCLA/MIT. fundamental analyst, sentiment analyst, technicals, risk manager with DeepSeek V4 thinking-mode support. 2. FinceptTerminal (+4.3K ★) open-source Bloomberg alternative built in C++20 + Qt6. 37 AI agents in Buffett/Munger/Lynch/Graham style. real-time trading with 16 broker integrations. internal MCP + AI quant tabs. 3. daily_stock_analysis (+2.3K ★) LLM stock analyzer for US, A-share and H-share markets. auto-builds a daily decision dashboard with entry/exit levels. pushes to WeChat/Telegram/Discord/Email via GitHub Actions. 4. Vibe-Trading (+1.9K ★) personal trading agent. natural language - strategy - backtest - export to TradingView/MT5. your own AI trading desk in one pip install. 5. QuantDinger (+837 ★) self-hosted AI quant OS. research markets, generate Python strategies, backtest ideas, run live trading. crypto, stocks via IBKR, forex via MT5. one Docker Compose, your infra, your data. 6. TradingAgents-CN (+641 ★) Chinese fork of TradingAgents. fully localized for A-share markets, Chinese data sources, and domestic LLMs. 7. last30days-skill (+630 ★) AI agent skill that researches any topic across Reddit, X, YouTube, HN, Polymarket and the web in the last 30 days. plug it into any agent. 8. qlib (+569 ★) Microsoft's AI-oriented quant investment platform. end-to-end: data - alpha - portfolio - execution. the most serious open-source quant infrastructure out there. 9. scientific-agent-skills (+511 ★) ready-to-use agent skills for research, science, engineering, analysis, and finance. plug into any agent framework. covers bioinformatics, cheminformatics, and now Hugging Science. 10. OpenBB (+387 ★) open-source financial data platform for analysts, quants, and AI agents. stocks, crypto, options, derivatives, fixed income шт one platform. integrates with AI agents via MCP.

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QuantDinger@QuantDinger_EN·2d

@qkl2058 连续两周上榜，太开心了！🚀 QuantDinger 还在持续优化，欢迎量化玩家试用、反馈，你的 Star 就是我们的动力！

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QuantDinger@QuantDinger_EN·2d

No way, two weeks in a row! Thank you so much for sharing this. 🙏 This project is all about helping the quant community, so if you’re a trader or dev, feel free to give it a spin, share it with your crew, and let us know your honest thoughts. And if it’s useful to you, a GitHub star would mean the world — it really helps others find it. We’re just getting started and will keep improving! Repo: github.com/brokermr810/Qu…

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Sinclair Ta@sinclairdta·2d

This week’s fastest-growing finance repos on GitHub tell a very clear story. It’s not about “AI in trading” anymore. It’s about *agents replacing the entire trading stack*. Look at the top projects: Multi-agent systems doing fundamental, sentiment, technicals, and risk in parallel. Terminals replacing Bloomberg with dozens of AI analysts modeled after Buffett and Munger. Self-hosted quant OS setups where research → strategy → backtest → execution all happen in one loop. This isn’t tooling. It’s *automation of the entire workflow*. What used to require a team—analysts, quants, traders, infra—is collapsing into a single system. And the design pattern is repeating everywhere: Agents + data + execution layer. That’s the new primitive. The interesting shift is not capability. It’s *abstraction*. Before, trading systems were built around: data pipelines → models → dashboards → human decisions Now it’s becoming: agents → decisions → execution → feedback The human is no longer in the critical path. Even more interesting: A lot of these tools are self-hosted. “Your infra. Your data. Your agents.” That’s a reaction to something deeper. In finance, edge = information + speed. If your agent runs on someone else’s system, you’re already late. So the stack is moving local. There’s also a cultural shift happening. You see forks like TradingAgents-CN adapting to local markets, data, and models. This space is fragmenting fast. Not one dominant system— but many localized, specialized agent stacks. But here’s the part most people miss: When everyone has access to similar agent capabilities… Alpha doesn’t come from *having AI*. It comes from: • better data • better constraints • better orchestration Same story, new layer. We’re watching trading evolve from: “Who has the best model?” to “Who has the best system of agents working together?” And once that clicks, the role of the human changes again. Not the one making trades. But the one designing the system that makes them. Image credit: @gusik4ever

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QuantDinger@QuantDinger_EN·2d

Wow, two weeks in a row on this list — seriously blown away by the support! 🙏 We built QuantDinger for the quant community, so we’d love for more traders and devs to check it out, pass it along if it helps, and let us know what you think. If you find it useful, dropping a star on GitHub would go a long way in helping more people find the tool. We’ll keep iterating and making it better for everyone! github.com/brokermr810/Qu…

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FHILY👑@Oluwaphilemon1·3d

Breaking News: THIS GUY BUILT THE FASTEST GROWING GITHUB REPOS LIST. CHECK IT OUT AND BOOKMARK IT.

wincy.eth@gusik4ever

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QuantDinger@QuantDinger_EN·2d

Hey there! I’ve been following your content for a while, and I really love how you always share such high-quality quant projects — they’ve been super helpful. Our team just open-sourced QuantDinger, an all-in-one quant platform that covers strategy development, backtesting, and live trading. We’ve spent a lot of time polishing the features and usability, and a lot of early users have said it’s way more practical than similar tools out there. I was wondering if you’d be interested in checking it out and maybe giving it a test run? If you think it’s a good fit for your audience, we’d be so grateful for a mention or share. As a small open-source project, your support would mean the world to us. GitHub: github.com/brokermr810/Qu… Either way, thanks so much for putting out such great content for the community! 🙏

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Nav Toor@heynavtoor·4d

10 free GitHub repos that anyone with $100 and a laptop can use to trade like a hedge fund in 2026. These are the same tools 300+ hedge funds quietly run on. Bookmark this. The list will save you years. 1. OpenBB A free Bloomberg Terminal. Stocks, options, futures, crypto, forex, all in one platform. The Bloomberg Terminal costs $25,000 a year. This costs $0. Repo → github.com/OpenBB-finance… 2. Lean (QuantConnect) The algorithmic trading engine 300+ real hedge funds use right now. Backtest on 25 years of data, deploy live to Interactive Brokers or Alpaca. Repo → github.com/QuantConnect/L… 3. qlib (Microsoft) Microsoft's full quant investment platform. The most serious open-source quant infrastructure ever shipped. Repo → github.com/microsoft/qlib 4. Backtrader The Python backtesting framework every quant learns first. Used in graduate finance programs around the world. Repo → github.com/mementum/backt… 5. TradingAgents A multi-agent LLM trading framework from UCLA and MIT. Autonomous AI agents acting as analyst, technician, and risk manager. Repo → github.com/TauricResearch… 6. Riskfolio-Lib The portfolio optimization library quants use to allocate capital. Mean-variance, Black-Litterman, CVaR, all in one place. Repo → github.com/dcajasn/Riskfo… 7. yfinance The free market data API every Python finance course starts with. Real-time and historical data on 100,000+ tickers. Repo → github.com/ranaroussi/yfi… 8. FinanceToolkit 150+ financial ratios, indicators, and valuation models in one library. Repo → github.com/JerBouma/Finan… 9. vectorbt The fastest backtesting engine in Python. Test thousands of strategies in seconds. Repo → github.com/polakowo/vecto… 10. TradingView Lightweight Charts The charting library powering real fintech apps in production. The reason your trading dashboard looks professional. Repo → github.com/tradingview/li… Here's the wildest part: A Bloomberg Terminal costs $25,000 a year. A junior hedge fund analyst costs $250,000. Goldman Sachs research costs millions. These 10 repos give a kid with $100 and a laptop access to most of what Wall Street pays for. A trading desk in 2010 cost $50,000 to set up. In 2026, the entire stack is free. The barrier between retail and Wall Street has never been lower. Save this before you forget. 100% free. 100% open source.

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QuantDinger@QuantDinger_EN·2d

Wow, two weeks in a row on this list — seriously blown away by the support! 🙏 We built QuantDinger for the quant community, so we’d love for more traders and devs to check it out, pass it along if it helps, and let us know what you think.If you find it useful, dropping a star on GitHub would go a long way in helping more people find the tool. We’ll keep iterating and making it better for everyone!Repo: github.com/brokermr810/Qu…

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Quant Science@quantscience_·2d

The fastest growing GitHub repos in finance this week: 1. TradingAgents (+7.9K ★) multi-agent LLM trading framework from UCLA/MIT. fundamental analyst, sentiment analyst, technicals, risk manager with DeepSeek V4 thinking-mode support. 2. FinceptTerminal (+4.3K ★) open-source Bloomberg alternative built in C++20 + Qt6. 37 AI agents in Buffett/Munger/Lynch/Graham style. real-time trading with 16 broker integrations. internal MCP + AI quant tabs. 3. daily_stock_analysis (+2.3K ★) LLM stock analyzer for US, A-share and H-share markets. auto-builds a daily decision dashboard with entry/exit levels. pushes to WeChat/Telegram/Discord/Email via GitHub Actions. 4. Vibe-Trading (+1.9K ★) personal trading agent. natural language - strategy - backtest - export to TradingView/MT5. your own AI trading desk in one pip install. 5. QuantDinger (+837 ★) self-hosted AI quant OS. research markets, generate Python strategies, backtest ideas, run live trading. crypto, stocks via IBKR, forex via MT5. one Docker Compose, your infra, your data. 6. TradingAgents-CN (+641 ★) Chinese fork of TradingAgents. fully localized for A-share markets, Chinese data sources, and domestic LLMs. 7. last30days-skill (+630 ★) AI agent skill that researches any topic across Reddit, X, YouTube, HN, Polymarket and the web in the last 30 days. plug it into any agent. 8. qlib (+569 ★) Microsoft's AI-oriented quant investment platform. end-to-end: data - alpha - portfolio - execution. the most serious open-source quant infrastructure out there. 9. scientific-agent-skills (+511 ★) ready-to-use agent skills for research, science, engineering, analysis, and finance. plug into any agent framework. covers bioinformatics, cheminformatics, and now Hugging Science. 10. OpenBB (+387 ★) open-source financial data platform for analysts, quants, and AI agents. stocks, crypto, options, derivatives, fixed income шт one platform. integrates with AI agents via MCP. 🚨Want to learn Algorithmic Trading Strategies (that actually work)? On May 14th, we are hosting a free workshop to help you get started with algorithmic trading with Python. Register here (500 seats): learn.quantscience.io/join

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QuantDinger@QuantDinger_EN·2d

QuantDinger Mobile is now OPEN SOURCE 🚀 Not just a UI demo. A real AI-powered quant trading mobile frontend. Built for: • AI market analysis • Multi-exchange trading • Strategy monitoring • Real-time positions • Quant workflow management Features: ⚡ Real-time trading dashboard 🤖 AI analysis workspace 📈 Market watchlists & indicators 🔐 API key management 💰 Exchange balance tracking 🌍 Multi-market support This is part of the QuantDinger ecosystem: An open-source AI quant trading platform designed for research, backtesting, automation, and live trading. 🌐 Official Site: m.quantdinger.com 🖥 Open Source Repo: github.com/brokermr810/Qu… We’re building the future of open-source quant trading. Contributors, traders, and builders are welcome. #opensource #trading #quant #crypto #AI #python #fintech #web3 #QuantDinger