This repository showcases a Minimum Viable Product (MVP) of a stock trading agent built using Reinforcement Learning (RL). The agent observes market data, executes trades, and learns to optimize its strategy over time.
Screencast.from.2025-05-06.09-43-04.mp4
-
Data is King: Clean, structured, and voluminous data is critical for training effective trading agents.
-
Team Effort: Professional trading systems require collaboration between data engineers, quant researchers, and RL experts.
-
Iterative Process: Building an MVP is just the start—real-world systems use ensemble methods and extensive simulations.
Happy trading! 🚀