Skip to content

A machine learning (ML) pair trading (PT) strategy to automatically identify trading pairs and implement a market neutral mean reversion strategy

Notifications You must be signed in to change notification settings

diodz/MLPairTrading_Strategy

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

8 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

The following files are included with this submission:

- Pitchbook.pdf of presentation slides detailing the trading strategy
- Technical paper.ipynb notebook of technical analysis
- Sarmento Horta 2019.pdf & Gatev Goetzmann Rouwenhorst 2006.pdf:
academic papers most relevant to our strategy
- util.py source code library with all the methods, classes, and 
mechanics of the trading strategy
- data folder with data downloaded or produced through the strategy


Note: Only the ff3.csv file with Fama french factors is necessary to
execute the code. All the other data can be downloaded directly by 
executing the code. However, intermediate data files (pkl) are included to avoid running code
that downloads data for faster execution and modular testing.


Student name: Diego A. Diaz
Student id: 12248985

About

A machine learning (ML) pair trading (PT) strategy to automatically identify trading pairs and implement a market neutral mean reversion strategy

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published