liualgotrader 0.4.35

a Pythonic all-batteries-included framework for effective algorithmic trading. The framework is intended to simplify development, testing, deployment and evaluating algo trading strategies.

LiuAlgoTrader

Introduction

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

The framework currently support trading and back-testing of US Equities, and Crypto strategies.

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 is a full trading platform with a breath of tools to manage automated investment portfolios.

LiuAlgoTrader supports:

• Alpaca.Markets APIs for trading, and data loading & streaming.
• Gemini Crypto Exchange APIs for trading, data loading & streaming.
• Polygon.io APIs for data-loading, and streaming.
• (BETA) Tradier APIs for trading and data.

See LiuAlgoTrader in Action

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

• Watch a $4,000 Daily Profit using LiuAlgoTrader Framework for Day Trading.
• Watch Trend-Following strategy beating SP-500 using LiuAlgoTrader out-of-the-box tools for Swing Trading,
• Sample tear-sheet using LiuAlgoTrader sample Trend Follow strategy.
• Make 30% trading pair volatility using LiuAlgoTrader.

Quick-start

Prerequisite

• Paper, and/or a funded account with Alpaca Markets. OR Polygon.io subscription optional (Starter plan and above),
• Installed Docker Engine and Docker Compose

Install & Configure

Step 1: To install LiuAlgoTrader just type:

pip install liualgotrader

Having issues installation? check out the installation FAQ page

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.

Note for WINDOWS users

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.

Tutorials

LiuAlgoTraders articles are published on Medium:

• Walk thru of setup and backtesting (2 parts)
• How to use the optimizer app
• How to setup a Trading Platform

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:

• Design & Planning,
• LSTM sample
• Attention (Transformer) : WIP

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 [e-mail]

Contributors

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

• Jonathan Morland-Barrett
• Alex Lau
• Rokas Gegevicius
• Shlomi Kushchi shlomikushchi
• Venkat Y vinmestmant
• Chris crowforc3
• TheSnoozer
• Aditya Gupta