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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.
The research engine that gives you an unfair advantage. Run thousands of trading ideas before others finish one.
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
Free open source crypto trading bot to automate AI, Grid, DCA and TradingView strategies on Binance, Hyperliquid and 15+ exchanges, with a simple interface.
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.
FinRL-X: An AI-Native Modular Infrastructure for Quantitative Trading
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.
Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.
📈 Personae is a repo of implements and environment of Deep Reinforcement Learning & Supervised Learning for Quantitative Trading.
Scalable, event-driven, deep-learning-friendly backtesting library
The repository host gives no description.
Predicting price trends in cryptomarkets using an lstm-RNN for the use of a trading bot
TranslatedMulti-market intelligent quantitative workbench (A-shares/Hong Kong stocks/US stocks) — secondary development based on shy3130/tickflow-stock-panel, adding multi-market support for Hong Kong and US stocks. Self-hosted stock screening + monitoring + backtesting. MIT.
Simple, modern ETH backtesting project using Pandas/Numpy: data prep, MA signals, portfolio simulation, and result visualization.