fastquant
gs-quant
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| fastquant | gs-quant | |
|---|---|---|
| 2 | 71 | |
| 1,107 | 1,692 | |
| - | 2.6% | |
| 0.0 | 6.5 | |
| 3 months ago | 12 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | Apache License 2.0 |
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.
fastquant
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Backtesting in Python, recommendations please.
https://github.com/enzoampil/fastquant -sort of a wrapper for backtrader that makes it very easy to run backtests and design trade strategies.
gs-quant
We haven't tracked posts mentioning gs-quant yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
backtrader - Python Backtesting library for trading strategies
market-making-backtest - algo trading backtesting on BitMEX
StockSharp - Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options).
FinanceOps - Research in investment finance with Python Notebooks
FinancePy - A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.
ccxt - A JavaScript / Python / PHP cryptocurrency trading API with support for more than 100 bitcoin/altcoin exchanges
coda - Mina is a new cryptocurrency with a constant size blockchain, improving scaling while maintaining decentralization and security. [Moved to: https://github.com/MinaProtocol/mina]
Mad-Money-Backtesting - Backtesting recommendations from Mad Money and "The Cramer Effect/Bounce"
resistance - Pre-crisis Risk Management for Personal Finance
backtesting.py - :mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.
machine-learning-for-trading - Code for Machine Learning for Algorithmic Trading, 2nd edition.
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.