Metadata-Version: 2.1
Name: liualgotrader
Version: 0.0.85
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)
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        [![Documentation Status](https://readthedocs.org/projects/liualgotrader/badge/?version=latest)](https://liualgotrader.readthedocs.io/en/latest/?badge=latest)
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        ## 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. 
        
        ## See LiuAlgoTrader in Action
        
        LiuAlgoTrader comes equipped with powerful & user-friendly back-testing tool. 
        
        [Watch a $4,000 Profit](https://youtu.be/rVwFCbHsbIY) using LiuAlgoTrader out-of-the-box tools.
        
        
        ## Quickstart
        
        ### Prerequisite
        
        - Paper, and a funded account with [Alpaca Markets](https://alpaca.markets/docs/about-us/).
        - Installed [Docker Engine](https://docs.docker.com/engine/install/) and [Docker Compose](https://docs.docker.com/compose/install/)
        
        (the prerequisties are for the `quickstart` wizard, not the framework)
        ### 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. 
        
        ## 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.
        
        
        ## 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: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
