@XAMTO_AI: Guys, there's something I just have to tell you about. An open-source AI quantitative trading platform has quietly launched. Locally self-deployable, full-chain connectivity, covering crypto, US stocks, and forex — from analysis to live trading all in one — can you believe it? Two years ago, such a thing was either ridiculously expensive or simply non-existent. Now it's directly open-sourced on G…
Summary
Introducing QuantDinger, an open-source AI quantitative trading platform that supports local deployment, full-chain connectivity for crypto, US stocks, and forex, integrating AI analysis, strategy generation, backtesting, and live trading integration.
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QuantDinger
The open-source AI infrastructure layer for quant trading
Turn trading ideas into Python strategies, backtests, paper trading, and live execution — all in one self-hosted stack.
AI research → Strategy code → Backtest → Paper/Live execution → Monitoring
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SaaS · API Docs · Video Demo · Website · AWS Marketplace
From zero to running stack — charting, AI research, and strategy workflow in minutes.
Closed loop: AI research → Strategy code → Backtest → Paper/Live execution → Monitoring — market data in, audited orders out.
If QuantDinger is useful to you, a GitHub star helps the project a lot.
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Alpha-Dojo/DojoAgents is a full-market personal investment AI copilot framework that supports automated analysis and strategy backtesting for stocks, forex, and cryptocurrencies. It is fully open-source and aims to give retail investors access to institutional-grade quantitative tools.
@cevenif: Guys, a library literally exploded today—nearly 90k stars, called TradingAgents, a multi-agent trading framework. In plain English: a group of AIs work together to help you trade crypto and stocks. ① Some AIs specialize in monitoring market data ② Some AIs are responsible for strategy decisions ③ Some AIs specialize…
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@KKaWSB: Going the extra mile, folks — quantitative trading projects on GitHub have reached a whole new level. There are plenty of ready-to-use strategies you can practice with (here's a curated list). What Wall Street teams earn millions for is now given to you for free by these open-source projects, complete with tutorials.
A curated list of open-source quantitative trading projects on GitHub, including AI-powered platforms like Qlib and FinGPT, multi-agent frameworks, and backtesting tools, all with tutorials and ready-to-use strategies.
@KKaWSB: https://x.com/KKaWSB/status/2074289438474330306
This article details how to build a personal quantitative trading system using free AI open-source tools (such as OpenBB, Qlib, TradingAgents, etc.), covering five major modules: data, research, backtesting, risk control, and execution, and points out common pitfalls and discipline.
@XAMTO_AI: Still losing hair writing quantitative strategies? Vibe-Trading, a personal AI trading agent from the HKUDS team at HKU, lets you command AI using natural language! Just speak human language and it can help you: research markets + auto-generate strategies, one-click backtesting + output full reports, multi-agent team collaboration...
Vibe-Trading is a personal AI trading agent from the HKUDS team at HKU, supporting natural language generation of quantitative strategies, one-click backtesting, and multi-agent collaboration. It comes with an embedded library of 456 alpha factors and is open-sourced.