Bit(cointegration) BackTester

Code to accompany Medium post

Contains .py version for running in terminal with no charting and full jupyter notebbook .ipynb version with full analysis

This tutorial is in 2 parts - (you can run the backtester as a separate standalone module) :

Learn the Statistical technique of Cointegration.

Build a Bitcoin Backtesting engine using Python to analyze the performance of a Cointegration based trading strategy.

What are we building

We are going to build a python based event-driven backtester that pulls 2 crypto securities Bitcoin (BTC)and Bitcoin Cash (BCH) from an API, passes it through a trading strategy that uses the mean reverting cointegration spread between the 2 securities and generates buy/sell signals when the spread hits ± 1 stdev. We then send these signals to the Portfolio class which handles the logic of the backtester. One time stamp will be pulled and processed at a time, allowing us to see what would have happened in tick-by-tick. Finally we print the results to console (or jupyter notebook) and print out the PnL (profit and loss).

To run the .py version simply clone the repo, and run: python bitcoin_backtester.py

To run the ipynb version, cd into the repo folder after downloading it and run: jupyter notebook