/LiuAlgoTrader

Framework for algorithmic trading

Primary LanguagePythonMIT LicenseMIT

LiuAlgoTrader

Build Status PyPI - Python Version Python 3 Updates Documentation Status Tested with Hypothesis Gitter Sourcery

Introduction

LiuAlgoTrader is a scalable, multi-process ML-ready framework for effective algorithmic trading. The framework simplify development, testing, deployment, analysis and training algo trading strategies. The framework automatically analyzes trading sessions, and the analysis may be used to train predictive models.

LiuAlgoTrader can run on a laptop and hedge-on-the-go, or run on a multi-core hosted Linux server and it will automatically optimize for best performance for either.

LiuAlgoTrader uses Alpaca.Markets brokerage APIs for trading, and can use either Alpaca or Polygon.io for stocks' data. The framework is evolving to support additional brokers and data-providers.

See LiuAlgoTrader in Action

LiuAlgoTrader comes equipped with powerful & user-friendly back-testing tool.

Watch a $4,000 Profit using LiuAlgoTrader out-of-the-box tools.

Quickstart

Prerequisite

Install & Configure

Step 1: To install LiuAlgoTrader just type:

pip install liualgotrader

Step 2: To configure the frame work type:

liu quickstart

and follow the installation wizard instructions. The wizard will walk you through the configuration of environment variables, setup of a local dockerized PostgreSQL and pre-populate with test data.

Try the samples

LiuAlgoTrader quickstart wizard installs samples allowing a first-time experience of the framework. Follow the post-installation instructions, and try to back-test a specific day.

Additional samples can we found in the examples directory.

Back-testing

While Liu is first and foremost a trading platform, it comes equipped with full back-testing capabilities, providing command-line tool & jupyter notebook for analysis, and a browser-based UI covering both functionalities.

Machine Learning

These features are still work in process:

Analysis & Analytics

The framework includes a wide ranges of analysis Jupyter Notebooks, as well as streamlit applications for analysis for both trading and back-testing sessions. To name a few of the visual analytical tools:

  • tear-sheet analysis,
  • gain&loss analysis,
  • anchored-VWAPs,
  • indicators & distributions

What's Next?

Read the documentation and learn how to use LiuAlgoTrader to develop, deploy & testing money making strategies.

Watch the Evolution

LiuAlgoTrader is an ever evolving platform, to glimpse the concepts, thoughts and ideas visit the design folder and feel free to comment.

Contributing

Would you like to help improve & evolve LiuAlgoTrader? Do you have a suggestion, comment, idea for improvement or a have a wish-list item? Please read our Contribution Document or email me at amichay@sgeltd.com

Contributors

Special thanks to the below individuals for their comments, reviews and suggestions: