FinRL_Podracer
Unverified ML strategy on Multi by AI4Finance-Foundation. BotFinder score 18 out of 100.
Cloud-native Financial Reinforcement Learning
Source: github
BotFinder analysis pending.
FinRL_Podracer
Podracer News: We are out of hands, please star it and let us know it is urgent to update this project. Thanks for your feedback. This project can be regarded as FinRL 2.0: intermediate-level framework for full-stack developers and professionals. It is built on ElegantRL and FinRL We maintain an elegant (lightweight, efficient and stable) FinRL lib, helping researchers and quant traders to develop algorithmic strategies easily. + Lightweight: The core codes are less than 800 lines and are based on PyTorch and NumPy. + Efficient: Its performance is comparable with Ray RLlib. + Stable: It is as stable as Stable Baseline 3. Design Principles + Be Pythonic: Quant traders, data scientists and machine learning engineers are familiar with the open source Python ecosystem: its programming model, and its tools, e.g., NumPy. + Put researchers and algorithmic traders first: Based on PyTorch, we support researchers to mannually control the execution of the codes, empowering them to improve the performance over automatical libraries. + Lean development of algorithmic strategies: It is better to h
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Alerts on changes: coming soon
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Open-source maintainer on GitHub.
Data-completeness & trust index (not a profitability rating)