Introduction

The pegasus platform is used for price correlation on crypto-currency coins and tokens.

Dependencies

Using Make, everything can be run inside of a virtualenv. Be sure you have python 3.6.1 installed. We utilize the .python-version file to specify our python version via pyenv. Once Python is setup properly, install dependencies:

$> make install

Running tests:

$> make test

Model definition

New models are defined in the src/models directory. You can inherity from Base model and implement the Pipeline class. This is the starting point in processing the data.

Once implemented, you can define a database connection and a model schema for processing data.

model = Model(period=[2018, 2017, 2016, 2015, 2014, 2013], entities=[
    {'slug': 'bitcoin', 'symbol': 'btc'},
    {'slug': 'ethereum', 'symbol': 'eth'},
    {'slug': 'litecoin', 'symbol': 'ltc'},
    {'slug': 'monero', 'symbol': 'xmr'},
])

Pipeline(config, sqlite, model).process()

Economics

The motivation of this project was to learn deeply about volatility across a broad range of different currencies and to understand their specific risk and rewards.

DNVR White Paper

DNVR Mining Model

The Markowitz Efficient frontier demonstrated below in the markowitz.py model.