{"repo":"whanyu1212/QuantRL-Lab","free":true,"listed":false,"github":"https://github.com/whanyu1212/QuantRL-Lab","clone":"git clone https://github.com/whanyu1212/QuantRL-Lab.git","description":"Reinforcement Learning Testbed for Quantitative Trading","language":"Python","stars":53,"topics":["algorithmic-trading","deep-reinforcement-learning","finance","fintech","pytorch","rl","stablebaselines3","stock-trading","testbed"],"license":"MIT","category":"trading","readme_excerpt":"QuantRL-Lab A Python testbed for Reinforcement Learning in finance. Emphasizes modularity via dependency injection of pluggable action, observation, and reward strategies — enabling rapid experimentation without rewriting environment code. For full API reference, guides, and examples see the documentation . --- Table of Contents - Installation - Motivation - Quick Start - Roadmap - Contributing - Contributors - Literature Review --- Installation Optional extras: Contributors : see CONTRIBUTING.md for the uv-based development setup. --- Motivation Most RL frameworks for finance hardcode action spaces, observation spaces, and reward functions into the environment. This makes experimentation slow — changing a reward function can require significant refactoring. QuantRL-Lab solves this with a strategy injection pattern: pass three pluggable objects at environment instantiation time and swap them freely without touching environment internals. --- Quick Start System Workflow Example --- Roadmap - Data sources : crypto and OANDA forex support - Environments : multi-stock environment (in progress) - Observable space : macroeconomic indicators integration - Hyperparameter tuning : expand Optuna search spaces and pruning strategies - Live trading : extended order types and position management for the Alpaca deployment client - Paper trading : end-to-end deployment boilerplate for running trained agents in paper trading mode --- Contributing 1. Fork the repository and create a feature b","default_branch":null,"files":null,"tree":[],"storefront":"/r/whanyu1212","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/whanyu1212/QuantRL-Lab/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}