Metadata-Version: 2.1
Name: liualgotrader
Version: 0.2.1
Summary: a Pythonic all-batteries-included framework for effective algorithmic trading. The framework is intended to simplify development, testing, deployment and evaluating algo trading strategies.
Home-page: https://github.com/amor71/LiuAlgoTrader
Author: amor71
Author-email: amichay@sgeltd.com
License: MIT
Description: # LiuAlgoTrader
        [![Build Status](https://travis-ci.org/amor71/LiuAlgoTrader.svg?branch=master)](https://travis-ci.org/amor71/LiuAlgoTrader)
        ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/liualgotrader)
        [![Python 3](https://pyup.io/repos/github/amor71/LiuAlgoTrader/python-3-shield.svg)](https://pyup.io/repos/github/amor71/LiuAlgoTrader/)
        [![Updates](https://pyup.io/repos/github/amor71/LiuAlgoTrader/shield.svg)](https://pyup.io/repos/github/amor71/LiuAlgoTrader/)
        [![Documentation Status](https://readthedocs.org/projects/liualgotrader/badge/?version=latest)](https://liualgotrader.readthedocs.io/en/latest/?badge=latest)
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        [![Sourcery](https://img.shields.io/badge/Sourcery-enabled-brightgreen)](https://sourcery.ai)
        ## 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](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.
        
        
        ## Quickstart
        
        ### 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`
         
        **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](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](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  amichay@sgeltd.com
        
        ## Contributors
        
        Special thanks to the below individuals for their comments, reviews and suggestions:
        
        - 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)
        
        
        
        
        
        
        
        
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
