resistance
FinRL-Library
Our great sponsors
| resistance | FinRL-Library | |
|---|---|---|
| 1 | 202 | |
| 607 | 2,782 | |
| - | - | |
| 2.1 | 9.8 | |
| 8 months ago | over 2 years ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Creative Commons Zero v1.0 Universal | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
resistance
FinRL-Library
What are some alternatives?
pyfolio - Portfolio and risk analytics in Python
tensortrade - An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.
gs-quant - Python toolkit for quantitative finance
FinRL - FinRL: Financial Reinforcement Learning. 🔥
FinancePy - A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.
rl_lib - Series of deep reinforcement learning algorithms 🤖
Open-Risk-Manual-PdfBooks - Collection of PdfBooks extracted from the Open Risk Manual
FinRL - Deep Reinforcement Learning Framework to Automate Trading in Quantitative Finance. NeurIPS 2020 & ICAIF 2021. 🔥 [Moved to: https://github.com/AI4Finance-Foundation/FinRL]
oisru - Repository for the Open Information Security Risk Universe
Reinforcement-Learning - Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning
machine-learning-for-trading - Code for Machine Learning for Algorithmic Trading, 2nd edition.
Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020 - Deep Reinforcement Learning for Automated Stock Trading: An Ensemble Strategy. ICAIF 2020. Please star. [Moved to: https://github.com/AI4Finance-Foundation/Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020]