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Python Algorithmic Trading Framework

Project description


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QuantWorks is an event driven algorithmic trading framework. It is a fork of PyAlgoTrade (see Motivation).

QuantWorks provides a Python API for strategy authoring, backtesting, paper trading, and of course live trading via the Broker interface.

To get started using QuantWorks, please take a look at the original PyAlgoTrade tutorial and the full documentation.

Main Features

  • Python 3 development
    • Python 2 support is NOT guaranteed in any capacity.
  • Event driven.
  • Supports Market, Limit, Stop and StopLimit orders.
  • Supports any type of time-series data in Pandas or CSV format (like Yahoo! Finance, Google Finance, Quandl and NinjaTrader), as well as database (i.e. sqlite).
  • Technical indicators and filters like SMA, WMA, EMA, RSI, Bollinger Bands, Hurst exponent and others.
  • Performance metrics like Sharpe ratio and drawdown analysis.
  • Event profiler.
  • TA-Lib integration.


QuantWorks is a fork of PyAlgoTrade by @gbeced. This project aims to be:

  • Modern: first-class Python 3 development (Python 2 is EOL as of 2020)
  • Extensible: as a framework, robust extension support is a must, and we encourage users of QuantWorks to give back by publishing their extensions (see Extensions)
  • Easy to Develop: state-of-the-art tooling (pytest, poetry, travis) and approachable design principles should make it easy for newcomers to contribute.
  • Open: as a fork of an Apache 2.0 license project, QuantWorks maintains the spirit of FOSS development. forthcoming


QuantWorks is developed and tested using 3.7 and depends on:

Developer ergonomics are provided by

  • poetry
  • pytest
  • tox
  • travis-ci


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