High Impact Practices Student Showcase Spring 2025
Files
Course Code
STA
Course Number
4164
Faculty/Instructor
Professor Nathaniel Simone
Faculty/Instructor Email
nathaniel.simone@ucf.edu
Abstract, Summary, or Creative Statement
This project began with the goal of finding the predictive power of oil and natural gas on the U.S. stock market. We gathered and used government-issued data on foreign oil imports volume and grade, domestic crude oil prices, domestic natural gas prices and volume, and S&P 500 prices from the 2023 fiscal year. We wrote a program in R that used several different criteria to give us the relationship between the above variables in a simple, optimal, mathematical model. We also used methods from our course such as the Box Cox transformation test to refine our variables. Ultimately, we found the value of the S&P 500 is incredibly difficult to predict with energy commodity values, with the only model of significant prediction power simply having natural gas volume as its only variable.
Keywords
Energy; stock market; oil; gas; S&P500
Recommended Citation
Seel, Griffin; Arroyave, Mari; Griffin, Jack; and Murphy, James, "The Relationship between the U.S Stock Market and Energy Commodities" (2025). High Impact Practices Student Showcase Spring 2025. 42.
https://stars.library.ucf.edu/hip-2025spring/42
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