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Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.
Production-grade Rust-native trading engine with deterministic event-driven architecture
Translated[🔥updating ...] AI automated quantitative trading robot (fully local deployment) AI-powered Quantitative Investment Research Platform. 📃 online docs: https://ufund-me.github.io/Qbot ✨ :news: qbot-mini: https://github.com/Charmve/iQuant
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.
A extendable, replaceable Python algorithmic backtest && trading framework supporting multiple securities
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.
📈 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
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.
Say It Simply, Test It Properly. Agent-powered strategy research with independent ledger checks and reproducible reports.
Predicting price trends in cryptomarkets using an lstm-RNN for the use of a trading bot
Batch backtest, import and strategy params optimalization for Gekko Trading Bot. With one command you will run any number of backtests.
Real-time HFT bot for Polymarket crypto Up/Down markets combining CLOB order books, Chainlink feeds and multi-exchange prices with TWAP and Black-Scholes probability models; paper mode and backtests.
AI-powered SDK featuring algorithmic trading, backtesting, deployment on 100+ exchanges, and multiple optimization engines.
AI-Powered Quantitative Trading Engine — Evolve strategies with genetic algorithms
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.