TradzQAI
A trading environment for reinforcement learning agents, supporting backtesting, live trading, and multiple RL algorithms.
What is TradzQAI?
TradzQAI is an open-source trading environment built for reinforcement learning (RL) agents, enabling backtesting and live trading in financial markets. It provides a framework to train RL algorithms like DDPG, DQN, and PPO on historical or real-time market data, helping developers create automated trading systems. The project supports customizable neural networks and integrates with APIs such as Coinbase Pro for live execution.
Quantitative developers, researchers, and data scientists working on algorithmic trading strategies using reinforcement learning. It is suited for those who need a flexible environment to prototype, backtest, and deploy RL-based trading agents.
TradzQAI offers a modular and extensible Python environment that combines multiple RL algorithms with practical trading features like live API integration and customizable networks. Unlike generic RL libraries, it is specifically tailored for financial markets, reducing the overhead of building trading infrastructure from scratch.
Overview
Trading environnement for RL agents, backtesting and training.
Use Cases
Best For
- Backtesting reinforcement learning trading strategies on historical market data
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