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Using Logistic Regression to Predict Stock Trends Based on Bag-of-Words Representations of News Article Headlines

Description

We attempted to apply a novel approach to stock market predictions. The Logistic Regression machine learning algorithm (Joseph Berkson) was applied to analyze news article headlines as represented by a bag-of-words (tri-gram and single-gram) representation in an attempt to predict the trends of stock prices based on the Dow Jones…

We attempted to apply a novel approach to stock market predictions. The Logistic Regression machine learning algorithm (Joseph Berkson) was applied to analyze news article headlines as represented by a bag-of-words (tri-gram and single-gram) representation in an attempt to predict the trends of stock prices based on the Dow Jones Industrial Average. The results showed that a tri-gram bag led to a 49% trend accuracy, a 1% increase when compared to the single-gram representation’s accuracy of 48%.
ContributorsBarolli, Adeiron (Author) / Jimenez Arista, Laura (Thesis director) / Wilson, Jeffrey (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Carnesi Thesis Paper

ContributorsCarnesi, Gregory (Author) / O'Rourke, Holly (Thesis director) / Brewer, Gene (Committee member) / Corbin, William (Committee member) / Chassin, Laurie (Committee member) / Barrett, The Honors College (Contributor) / Department of Psychology (Contributor)
Created2022-05
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Final Thesis Defense Presentation

ContributorsCarnesi, Gregory (Author) / O'Rourke, Holly (Thesis director) / Brewer, Gene (Committee member) / Corbin, William (Committee member) / Chassin, Laurie (Committee member) / Barrett, The Honors College (Contributor) / Department of Psychology (Contributor)
Created2022-05
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A Psychometric Analysis of an Operational ASU Exam

Description
This thesis explored the psychometric properties of an ASU midterm. These analyses were done to explore the efficacy of the questions on the exam using the methods of item analysis difficulty and discrimination. The discrimination and difficulty scores as well as the correlations of questions led to suggests of questions…

This thesis explored the psychometric properties of an ASU midterm. These analyses were done to explore the efficacy of the questions on the exam using the methods of item analysis difficulty and discrimination. The discrimination and difficulty scores as well as the correlations of questions led to suggests of questions that may need revision.
ContributorsLowell, Emily M (Author) / Levy, Roy (Thesis director) / O'Rourke, Holly (Committee member) / School of Life Sciences (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05