🚀 💸 Easily build, backtest and deploy your algo in just a few lines of code. Trade stocks, cryptos, and forex across exchanges w/ one package.
- cryptocurrency
- bot-framework
- investment
- bots
Repository Index
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Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
- high-frequency-trading
- limit-order-book
- python
- machine-learning
Framework for quantitative trading. Complete framework for development, backtesting, and deploying automated trading algorithms and trading bots.
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.
Agentic AI Hedge Fund OS (AIMM)
- trade-bot
- trade
- multiagent-systems
- agentic-trading
High-performance technical analysis indicators and backtesting framework in Go. Zero dependencies. ✨ See how! 👀
- indicators
- technical-analysis
- stock-analysis
- stock-market
The modern cryptocurrency trading bot framework written in Go.
- trading
- trading-bot
- cryptocurrency
- binance
📈 Personae is a repo of implements and environment of Deep Reinforcement Learning & Supervised Learning for Quantitative Trading.
- reinforcement-learning
- supervised-learning
- stock-data
- trading
Scalable, event-driven, deep-learning-friendly backtesting library
- reinforcement-learning
- deep-reinforcement-learning
- gym-environment
- openai-gym
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.
Trady is a handy library for computing technical indicators, and it targets to be an automated trading system that provides stock data feeding, indicator computing, strategy building and automatic trading. It is built based on .NET Standard 2.0.
- strategy
- technical
- analysis
- stock
Say It Simply, Test It Properly. Agent-powered strategy research with independent ledger checks and reproducible reports.
Every day, millions of traders around the world are trying to make money by trading stocks. These days, physical traders are also being replaced by automated trading robots. Algorithmic trading market has experienced significant growth rate and large number of firms are using it. I have tried to build a Deep Q-learning reinforcement agent model to do automated stock trading.
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.
Replay recorded launches offline, count every fee, keep notes on each token.
- axiom
- desktop
- offline
- rust
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.
- black-scholes
- chainlink
- crypto
- hft
TranslatedLow-code quant backtesting for China A-shares
- a-shares
- backtesting
- backtrader
- china-stock
AI-powered SDK featuring algorithmic trading, backtesting, deployment on 100+ exchanges, and multiple optimization engines.
Simple, modern ETH backtesting project using Pandas/Numpy: data prep, MA signals, portfolio simulation, and result visualization.
- algorithmic-trading
- cryptocurrency
- ethereum
- moving-average