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