https://github.com/pymargot/margot

An algorithmic trading framework for pydata.
https://github.com/pymargot/margot

algorithmic-trading algorithmic-trading-engine feature-engineering pandas pandas-dataframe quant quantitative-finance systematic-trading systematic-trading-strategies timeseries trading trading-algorithms trading-bot trading-strategies

Last synced: 5 months ago
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An algorithmic trading framework for pydata.

• Host: GitHub
• URL: https://github.com/pymargot/margot
• Owner: pymargot
• License: apache-2.0
• Created: 2020-06-05T02:07:35.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2023-04-02T01:20:22.000Z (about 3 years ago)
• Last Synced: 2025-08-30T08:49:30.476Z (10 months ago)
• Topics: algorithmic-trading, algorithmic-trading-engine, feature-engineering, pandas, pandas-dataframe, quant, quantitative-finance, systematic-trading, systematic-trading-strategies, timeseries, trading, trading-algorithms, trading-bot, trading-strategies
• Language: Python
• Homepage: https://margot.readthedocs.io
• Size: 206 KB
• Stars: 15
• Watchers: 3
• Forks: 7
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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# What is margot?

Margot makes it super easy to backtest trading elgorithms. Firstly, Margot makes

it super easy tocreate neat and tidy Pandas dataframes for time-series analysis.

Margot manages data collection, caching, cleaning, feature generation,

management and persistence using a clean, declarative API. If you've

ever used Django you will find this approach similar to the Django ORM.

Margot also provides a simple framework for writing and backtesting systematic

trading algorithms.

Results from margot's trading algorithms can be analysed using pyfolio.

# Getting Started

    pip install margot

Next you need to make sure you have a couple of important environment variables

set::

    export ALPHAVANTAGE_API_KEY=YOUR_API_KEY

    export DATA_CACHE=PATH_TO_FOLDER_TO_STORE_HDF5_FILES

Once you've done that, try running the code in the [notebook](notebook.margot.data).

# Status

This is still an early stage software project, and should not be used for live

trading just yet.

# Documentation

The documentation is at [readthedocs](https://margot.readthedocs.io/en/latest/).

# Contributing

Feel free to make a pull request or chat about your idea first using [issues](https://github.com/atkinson/margot/issues).

Dependencies are kept to a minimum. Generally if there's a way to do something

in the standard library (or numpy / Pandas), let's do it that way rather than

add another library. 

# License

Margot is licensed for use under Apache 2.0. For details see [the License](https://github.com/atkinson/margot/blob/master/LICENSE).