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    FACTOR-BASED INVESTING IN AN OVERVALUED MARKET

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    Author
    Zai, Andreas Grant
    Issue Date
    2018
    Advisor
    Cederburg, Scott
    
    Metadata
    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Abstract
    Tasked with creating a market-neutral, beta-neutral, long / short, unlevered, minimal-cash portfolio for the Chicago Quantitative Alliance Challenge, our team used a factor-based methodology to develop a portfolio of securities that we believed would perform in a period of market correction from November of 2017 through March of 2018. These factors were weighted in the portfolio as size (20%), value (35%), momentum (30%), and beta (15%). We later added quality as a factor and removed size, while also adding a small sector bet on technology and healthcare. We backtested the portfolio seven times by reconstructing the factor-method with a Python algorithm that ran on data and computing power provided by the Quantopian servers. These backtests indicated that the portfolio would succeed in a period of market correction. At the end of the challenge, the portfolio returned -0.07% and had a Sharpe ratio of -0.37. Despite not generating positive returns, we believe that these results were overall positive in teaching us how to construct and manage a portfolio with an array of quantitative skills.
    Type
    text
    Electronic Thesis
    Degree Name
    B.S.
    Degree Level
    bachelors
    Degree Program
    Honors College
    Finance
    Collections
    Honors Theses

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