FinRL-X: An AI-Native Modular Infrastructure for Quantitative Trading
- deep-reinforcement-learning
- stock-trading
- a2c-algorithm
- ppo
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FinRL-X: An AI-Native Modular Infrastructure for Quantitative Trading
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
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.
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.
Trading environnement for RL agents, backtesting and training.