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Arbitrage Analysis

Task

Using historical trade data for Bitcoin on two exchanges: Bitstamp and Coinbase. Your task is to apply the three phases of financial analysis to determine if any arbitrage opportunities exist for Bitcoin.

After reviewing the profit information across each date from the different time periods, can you identify any patterns or trends? We can clearly see that in the early date there was a bigger opportunity to profit from the arbitrage, which clearly is reduced as time passed, reducing our profit to $0 in the late period.

Early Period

Analysis

There were 73 profitable arbitrage trades to be made in the Middle Period resulting in $14147.17 of profit with an average of $193.79 per trade. All of them ocurring between around 2am and 8pm.

Date: '2018-01-16' Data Summary

Unit Value
count 73.000000
mean 193.796849
std 88.701429
min 112.520000
25% 139.420000
50% 171.310000
75% 210.060000
max 606.800000

Profitable Trades (First and Last 5)

Date and Time Profit
2018-01-16 02:56:00 162.01
2018-01-16 02:57:00 135.00
2018-01-16 02:59:00 176.13
2018-01-16 03:00:00 134.01
2018-01-16 03:06:00 241.54
...
2018-01-16 19:23:00 125.09
2018-01-16 19:26:00 131.78
2018-01-16 19:38:00 124.01
2018-01-16 19:48:00 117.63
2018-01-16 20:07:00 113.69

Total Profit: $14147.17

Middle Period

Analysis

There were 3 profitable arbitrage trades to be made in the Middle Period resulting in $330.07 of profit with an average of $110.02 per trade. All of them ocurring from 8:30am to 9:40am

Date: '2018-02-24' Data Summary

Unit Value
count 3.000000
mean 110.023333
std 10.129246
min 101.750000
25% 104.375000
50% 107.000000
75% 114.160000
max 121.320000

Profitable Trades

Date and Time Profit
2018-02-24 08:32:00 121.32
2018-02-24 09:32:00 107.00
2018-02-24 09:39:00 101.75

Total Profit: $330.07

Late Period

Analysis

There were no profitable arbitrage trades to be made in the Late Period resulting.

Date: '2018-03-26' Data Summary

Unit Value
count 0.0
mean NaN
std NaN
min NaN
25% NaN
50% NaN
75% NaN
max NaN

Profitable Trades None

Total Profit: $0

Technologies

Developed in Python and tested on MacOS. It requires to have the following installed (Versions tested):

  • Python 3.9.7
  • Path
  • pandas
  • matplotlib

Installation Guide

  1. Clone this project using git with the following command: git clone [email protected]:galcivar/module_03.git
  2. Install Python you should follow this instructions depending on you OS: https://realpython.com/installing-python/

Usage

You can use this program by navigating to the folder of the project (where app.py is) and run: jupiter lab then open the crypto_arbitrage.ipynb file in Jupiter Lab


Contributors

Gabriel Alcivar Email - LinkedIn - GitHub


MIT License

Copyright (c) [2022] [Gabriel Alcivar]

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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