Module 3 Challenge: Arbitrage:
For this project, we sorted through historical data for Bitcoin on two exchanges: Bitstamp ($BPI) and Coinbase ($COIN).
We then applied three phases of financial analysis to determine if arbitrage opportunies exist: 1.) Collecting the CSV data in a Juypter notebook file; 2.) Preparing the datasets for analysis by cleaning missing and erroneous data; 3.) A high-level analysis though summary statistics and visualizations; thus allowing for deeper analysis on three specific dates within the data.
This project uses Python 3.7.11.
It uses the following packages:
- Pandas
- Path from Pathlib
- inline dependency from %Matplot
The project uses two datasets
1.) 'bitstamp.csv' Stock data for $BTI from January 1, 2018 through March 31st, 2018. 2.) 'coinbase.csv' Stock data for $COIN from January 1, 2018 through March 31st, 2018.
Created by Arthur Lovett