a Pythonic all-batteries-included framework for effective algorithmic trading. The framework is intended to simplify development, testing, deployment and evaluating algo trading strategies.
Project description
LiuAlgoTrader
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 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.
Quickstart
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
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:
- 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 amichay@sgeltd.com
Contributors
Special thanks to the below individuals for their comments, reviews and suggestions:
- Shlomi Kushchi shlomikushchi
- Venkat Y vinmestmant
- Chris crowforc3
- TheSnoozer
Project details
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