Lean Algorithmic Trading Engine by QuantConnect (Python, C#)
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Lean Algorithmic Trading Engine by QuantConnect (Python, C#)
Translatedstock. Get stock data, calculate stock indicators, chip distribution, identify stock patterns, comprehensive stock selection, stock selection strategies, stock verification and backtesting, automatic stock trading, supports PC and mobile devices.
The most complete open-source, self-hosted Agentic Trading OS—AI research, Python strategies, factor discovery, backtesting, optimization, paper/live multi-asset execution, risk controls, monitoring, MCP, and multi-tenant SaaS in one auditable stack.
Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options).
🔎 📈 🐍 💰 Backtest trading strategies in Python.
Translated🦄🦄🦄AI-empowered stock analysis: an AI-powered stock analysis/stock selection tool. Fetches stock quotes, AI analysis of hot news, AI analysis of funds/financials, and push alerts for price rises and falls. Supports A-shares, Hong Kong stocks, and US stocks. Supports overall market/individual stock sentiment analysis, AI-assisted stock selection, and more. All data stays local. Supports platforms or models such as DeepSeek, OpenAI, Ollama, LMStudio, AnythingLLM, 硅基流动 (SiliconFlow), 火山方舟 (Volcano Ark), and 阿里云百炼 (Alibaba Cloud Bailian).
TranslatedTSP: a self-hosted, zero-maintenance quantitative workbench for A-shares covering "custom strategies + monitoring + backtesting" | LLM capabilities drive strategy customization + individual stock analysis + post-trade review | Freely connect third-party data sources and personalized extended data | Personal open-source project
11 Claude skills for day trading: scan thousands of charts, track breaking news, time every entry and exit, and replay every outcome before you risk a dollar.
A extendable, replaceable Python algorithmic backtest && trading framework supporting multiple securities
TranslatedQuantitative research - replication of brokerage financial engineering research reports
TranslatedStock AI Trader: 1-stop platform for learning, sim & live trading. Covers: stock basics, strategies, LLMs, factor mining, ML/DL/RL, graph nets, HFT, C++ deploy & JoinQuant code.
📈 Get real-time stocks from TradingView
MCP server for market analysis in AI assistants: screeners, multi-timeframe technical analysis, backtests and sentiment for crypto, stocks, forex and futures. 39 tools. Self-host free, or use the hosted version, TradingMCP.
Python toolkit for quantitative finance: stock analysis, technical indicators, strategy backtesting, portfolio optimization, and financial modeling.
modular quant framework.
FinRL-X: An AI-Native Modular Infrastructure for Quantitative Trading
An open-source, high-performance quantitative trading framework in C++/Python focused on strategy analysis and backtesting Trading model R&D · Ultra-fast engine · Efficient backtesting
Algorithmic Trading in Python with Machine Learning
TranslatedVibe-Research: A research workbench for China A-shares, US and HK stocks · watchlist and holdings, daily review, industry news, industry research, in-depth stock analysis, backtesting, research report library, 168 data endpoints. Supports Claude Code, Codex, WorkBuddy subscriptions or any model API.
A Java library for technical analysis.
Python trading framework with AI agents that actually place the trade. Backtest, paper and live trade on 12 brokers: stocks, options, futures, forex, crypto and prediction markets.
High-performance technical analysis indicators and backtesting framework in Go. Zero dependencies. ✨ See how! 👀
📈 Personae is a repo of implements and environment of Deep Reinforcement Learning & Supervised Learning for Quantitative Trading.
A light-weight deep reinforcement learning framework for portfolio management. This project explores the possibility of applying deep reinforcement learning algorithms to stock trading in a highly modular and scalable framework.