FinRL VS FinanceOps

Compare FinRL vs FinanceOps and see what are their differences.

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FinRL FinanceOps
44 24
9,093 761
1.7% -
8.8 0.0
8 days ago about 2 years ago
Jupyter Notebook Jupyter Notebook
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

FinRL

Posts with mentions or reviews of FinRL. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-25.

FinanceOps

Posts with mentions or reviews of FinanceOps. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing FinRL and FinanceOps you can also consider the following projects:

tensortrade - An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.

fastquant - fastquant — Backtest and optimize your ML trading strategies with only 3 lines of code!

gym-anytrading - The most simple, flexible, and comprehensive OpenAI Gym trading environment (Approved by OpenAI Gym)

FinRL - Deep Reinforcement Learning Framework to Automate Trading in Quantitative Finance. NeurIPS 2020 & ICAIF 2021. 🔥 [Moved to: https://github.com/AI4Finance-Foundation/FinRL]

FinRL-Meta - FinRL­-Meta: Dynamic datasets and market environments for FinRL.

FinRL-Library - Deep Reinforcement Learning Framework to Automate Trading in Quantitative Finance. NeurIPS 2020 & ICAIF 2021. 🔥 [Moved to: https://github.com/AI4Finance-Foundation/FinRL]

python-training - Python training for business analysts and traders

Deep-Hedging

PyPortfolioOpt - Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity

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]

mlfinlab - MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.