FinancePy VS machine-learning-for-trading

Compare FinancePy vs machine-learning-for-trading and see what are their differences.


A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives. (by domokane)
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FinancePy machine-learning-for-trading
62 170
1,317 7,349
- -
8.3 4.0
2 days ago 23 days ago
Jupyter Notebook Jupyter Notebook
GNU General Public License v3.0 only -
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.


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

We haven't tracked posts mentioning FinancePy yet.
Tracking mentions began in Dec 2020.


Posts with mentions or reviews of machine-learning-for-trading. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-01.

What are some alternatives?

When comparing FinancePy and machine-learning-for-trading you can also consider the following projects:

DCF - Basic Discounted Cash Flow library written in Python. Automatically fetches relevant financial documents for chosen company and calculates DCF based on specified parameters.

SDV - Synthetic Data Generation for tabular, relational and time series data.

Mad-Money-Backtesting - Backtesting recommendations from Mad Money and "The Cramer Effect/Bounce"

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

zero-to-mastery-ml - All course materials for the Zero to Mastery Machine Learning and Data Science course.

documentation - This repository contains the documentation for the current Quantiacs project. Check it out at:

cryptocurrency-price-prediction - Cryptocurrency Price Prediction Using LSTM neural network

gs-quant - Python toolkit for quantitative finance

TTM - # TTM Stock squeeze detection based on bollinger + keltner channels. Detects which stocks are out after bollinger is inside keltner channel.

fraud-detection-handbook - Reproducible Machine Learning for Credit Card Fraud Detection - Practical Handbook

SynthDet - SynthDet - An end-to-end object detection pipeline using synthetic data

dcf-basic - Basic DCF model to quickly value public companies.