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https://github.com/amor71/LiuAlgoTrader

Framework for algorithmic trading
https://github.com/amor71/LiuAlgoTrader

algo-trading algorithmic-trading alpaca-markets alpaca-trading-api artificial-intelligence-algorithms cryptocurrency-exchanges gemini-api liualgotrader machine-learning machinelearning python trade trader traders trading trading-algorithms trading-platform trading-platforms trading-strategies trading-systems

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Framework for algorithmic trading

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README 

        
# LiuAlgoTrader

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## 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](https://alpaca.markets/) APIs for trading, and data loading & streaming.

* [Gemini Crypto Exchange](https://www.gemini.com/) APIs for trading, data loading & streaming.

* [Polygon.io](https://polygon.io/) APIs for data-loading, and streaming.

* (**BETA**) [Tradier](https://tradier.com/) 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](https://youtu.be/rVwFCbHsbIY) using LiuAlgoTrader Framework for Day Trading.

- [Watch Trend-Following strategy beating SP-500](https://youtu.be/BhifqoJBn84) using LiuAlgoTrader out-of-the-box tools for Swing Trading,

- [Sample tear-sheet](https://amor71.github.io/LiuAlgoTrader/tearsheet.html) using LiuAlgoTrader sample Trend Follow strategy.

- [Make 30% trading pair volatility](https://amor71.github.io/LiuAlgoTrader/brandtreade_tearsheet.html) using LiuAlgoTrader.



## Quick-start



### Prerequisite



- Paper, and/or a funded account with [Alpaca Markets](https://alpaca.markets/docs/about-us/).

OR Polygon.io subscription optional (`Starter` plan and above),

- Installed [Docker Engine](https://docs.docker.com/engine/install/) and [Docker Compose](https://docs.docker.com/compose/install/)



### Install & Configure



**Step 1**: 

To install LiuAlgoTrader just type: 



`pip install liualgotrader`



Having issues installation? check out the [installation FAQ page](https://liualgotrader.readthedocs.io/en/latest/Troubleshooting.html)

 

**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](https://liualgotrader.readthedocs.io/en/latest/Troubleshooting.html#q-can-i-run-liu-on-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](examples) directory. 



## Tutorials



LiuAlgoTraders articles are published on [Medium](https://amor71.medium.com/):



* [Walk thru of setup and backtesting (2 parts)](https://amor71.medium.com/liualgotrader-part-i-3334a27edd4b)

* [How to use the optimizer app](https://amor71.medium.com/liu-optimizer-42b0d6805d77)

* [How to setup a Trading Platform](https://amor71.medium.com/how-to-setup-your-trading-platform-part-i-64ea8ea828bb)



## 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](https://github.com/amor71/LiuAlgoTrader/blob/master/design/ml-concepts.ipynb),

* [LSTM sample](https://github.com/amor71/LiuAlgoTrader/blob/master/analysis/notebooks/LSTM.ipynb)  

* 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](https://liualgotrader.readthedocs.io/en/latest/) 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](https://github.com/amor71/LiuAlgoTrader/tree/master/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](https://github.com/amor71/LiuAlgoTrader/blob/master/CONTRIBUTING.md) or 

email me at  [email protected]



## Contributors



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



- [Jonathan Morland-Barrett](https://github.com/sigmantium)

- [Alex Lau](https://github.com/riven314)

- [Rokas Gegevicius](https://github.com/ksilo)

- Shlomi Kushchi [shlomikushchi](https://github.com/shlomikushchi)

- Venkat Y [vinmestmant](https://github.com/vinmestmant)

- Chris [crowforc3](https://github.com/crawforc3)

- [TheSnoozer](https://github.com/TheSnoozer)

- [Aditya Gupta](https://github.com/adi0x90)