FinancePy VS gs-quant

Compare FinancePy vs gs-quant and see what are their differences.

FinancePy

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)
risk Pricing risk-management asset-allocation Finance Valuation Python derivatives-pricing numba bonds Students fixed-income Derivatives Investment Currency credit
Source Code
financepy.com
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gs-quant

Python toolkit for quantitative finance (by goldmansachs)
gs-quant goldman-sachs risk-management trading-strategies Derivatives
Source Code
developer.gs.com
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FinancePy gs-quant
97 96
1,898 2,456
- 4.6%
8.8 7.9
27 days ago 8 days ago
Jupyter Notebook Jupyter Notebook
GNU General Public License v3.0 only Apache License 2.0
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.

FinancePy

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

gs-quant

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

What are some alternatives?

When comparing FinancePy and gs-quant 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.

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

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

machine-learning-for-trading - Code for Machine Learning for Algorithmic Trading, 2nd edition.

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

resistance - Pre-crisis Risk Management for Personal Finance

alphalens - Performance analysis of predictive (alpha) stock factors

notebooks - Implement, demonstrate, reproduce and extend the results of the Risk articles 'Differential Machine Learning' (2020) and 'PCA with a Difference' (2021) by Huge and Savine, and cover implementation details left out from the papers.

ruby-cff - A Ruby library for manipulating CITATION.cff files.

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

okama - Investment portfolio and stocks analyzing tools for Python with free historical data

FinancePy vs DCF gs-quant vs fastquant FinancePy vs PyPortfolioOpt gs-quant vs machine-learning-for-trading FinancePy vs dcf-basic gs-quant vs resistance FinancePy vs alphalens gs-quant vs notebooks FinancePy vs ruby-cff gs-quant vs Mad-Money-Backtesting FinancePy vs okama FinancePy vs resistance