Metadata-Version: 1.1
Name: margot
Version: 0.2.2
Summary: simple to use, batteries included, tools for quantitative trading.
Home-page: https://github.com/atkinson/margot
Author: Rich Atkinson
Author-email: rich@airteam.com.au
License: apache-2.0
Download-URL: https://github.com/atkinson/margot/archive/v_0.1-alpha.tar.gz
Description: # What is margot?
        
        ## margot wants you to be a better quant.
        
        margot is a "batteries included" library for systematic trading with an emphasis on ease of use.
        
        ## margot wants to help you:
        
        **- Wrangle data** - use a simple Django ORM inspired API to blend data from a variety of sources into a consolidated time-series dataframe.
        
        **- Reuse features** - a library of reusable features to apply to your data.
        
        **- Make custom features** - easily create features out of your preferred indicators or ratios, and incorporate them in to your algorithms in a repeatable way. 
        
        **- Write algorithms that trade** - TODO express your idea using simple logic, without getting bogged down by the nuances of Pandas or stochastic algebra.
        
        **- Walk-forward backtest your algos** - TODO Backtest your algorithm, generating a historical returns time-series that can be analysed using pyfolio.
        
        **- Manage risk** - TODO Learn the expected volatility of a strategy so that you can size it into your portfolio.
        
        **- Allocate accordingly** - TODO allocate funds to a strategy based on realised volatility.
        
        **- Trade** - TODO execute your trades with your brokers API.
        
        **- Bookkeep** - TODO track fees and P&L, per strategy.
        
        ## Status
        This is still an early stage software project, and should not be used for live trading.
        
        ## Getting Started
        
        pip install margot
        
        ## Documentation
        
        in progress - for examples see the notebooks folder.
        
        ## Contributing
        Feel free to make a pull request; but please feel even free-er to chat about your idea first via issues.
        
        The general idea is to **keep things simple**. This is intended to be long-running operational software; it must be easy to maintain, and easy to understand.
        
        Dependencies are kept to a minimum. Generally if there's a way to do something in the standard library (or numpy / Pandas), let's do it that way rather than seeking the convenience of another library. 
        
        ## Resources 
        
        If you come across this, I suggest you checkout http://robotwealth.com. Kris and James taught me everything I know about trading. They're like 5th Dan blackbelts at quantitative finance. You should try one of their bootcamps.
        
        ## License
        This version of this software may only be used under the terms set out in [the License](License.txt).
        
Keywords: quant,trading,systematic
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
