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Using Machine Learning and Google Searches to Predict Stock Market Changes

MA Thesis - Jarred Glaser

Spring 2018

This repo holds the code for my MA thesis: "Using Machine Learning and Google Searches to Predict Stock Market Changes".

MAThesisR.R

The main script that I used to generate features, run random forest and SVM models, and plot data.

Packages Used in this script:

  • ggplot2
  • tidyverse
  • fpp2
  • TTR
  • pracma
  • data.tables
  • caret
  • mlbench
  • randomForest
  • gridExtra
  • ggpubr
  • mlbench
  • e1071

GoogleSearchVolume.py

A Python script I created and used to collect and normalize daily Google search data. Special thanks and credit goes to a module called pytrends, a pseudo API created by GeneralMills for grabbing data from Google Trends. See the module here.

Modules used in this script:

  • pytrends
  • datetime
  • pandas
  • matplotlib
  • time
  • random