Production-grade Rust-native trading engine with deterministic event-driven architecture
- algorithmic-trading-engine
- trading-platform
- crypto-trading
- artificial-intelligence
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Production-grade Rust-native trading engine with deterministic event-driven architecture
Lean Algorithmic Trading Engine by QuantConnect (Python, C#)
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).
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.
TranslatedWonderTrader - a one-stop framework for quantitative research, development, and trading
FinRL-X: An AI-Native Modular Infrastructure for Quantitative Trading
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.
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
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.
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.
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.
Deterministic, dependency-free Chan-theory (缠论) structure engine + multi-market trading workstation (A-shares / HK / US / crypto) with teaching chart annotations and a mobile PWA.
Wisp CLI — Interactive trading platform for backtesting and live trading across spot, perpetual futures, options, and prediction markets
Simple, modern ETH backtesting project using Pandas/Numpy: data prep, MA signals, portfolio simulation, and result visualization.