Open-Source Trading Algorithms
Objective catalog of 42 algorithms across 11 GitHub repositories — no ratings, no recommendations. Facts only.
Explore how algorithms connect across libraries and strategy types
Gradient boosting, neural networks, transformers for price prediction
RL agents (PPO, A2C, SAC, DDPG) for autonomous trading decisions
Spread-based liquidity provision strategies for CEX and DEX
Channel and band breakout strategies for trend initiation
Moving average crossover and trend-following momentum strategies
Cross-exchange and spot-perpetual arbitrage strategies
Alpha factor libraries and signal-based portfolio strategies
DCA and contrarian reversion strategies
Crypto trading bot framework with FreqAI ML extension supporting multiple machine learning and deep learning models.
AI-oriented quantitative investment platform from Microsoft Research for stock market prediction and portfolio optimization.
Deep reinforcement learning framework for quantitative finance, providing RL environments and agents for stock, crypto, and forex trading.
Open-source crypto market making and arbitrage bot with support for 40+ exchanges and DEX protocols.
Python-based open-source quantitative trading framework popular in Asia, supporting futures, stocks, options, and forex.
Open-source crypto trading bot with Web UI, supporting grid trading, DCA, and configurable technical analysis strategies.
Educational multi-agent AI system simulating famous investors (Buffett, Munger, Burry) as LLM-powered trading agents. Not for production use.