Barrett, The Honors College Thesis/Creative Project Collection
Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.
Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.
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Description
Every year, major companies buy Super Bowl advertisements (‘ads’) to fuel growth through the creation of brand awareness among a large, diverse audience. Although measuring the effectiveness of these marketing tactics is difficult, evaluating the abnormal returns (‘alpha’) of company stocks in the five days following the Super Bowl is effective because it provides insight into how actual returns compare to expected returns (calculated using data from the preceding 250 days). Analysis of a comprehensive sample, which includes all Super Bowl ads for public companies between the years 2015 and 2019, accurately demonstrates the relationship between these returns, illustrating the effectiveness of this type of marketing. To account for variation resulting from different inputs in different financial models, it is important to evaluate alpha based on several, reputable models of expected return to best capture the result. In this study, alpha will be analyzed using the Capital Asset Pricing Model (‘CAPM’) and the Fama and French 3 and 5 factor models. Although the ideology that increased marketing improves stock returns through brand awareness suggests a positive alpha, these models all indicate a statistically significant negative alpha for large, public companies who bought Super Bowl ads over the past five years. Therefore, actual returns, on average, are lower than projected returns for the evaluated five-day window following the Super Bowl. In examining alpha and statistical significance according to these financial models, this thesis will explore different market factors that may explain this counterintuitive result, primarily focusing on the investors’ opinions about this type of marketing. Therefore, in researching various discrepancies contributing to the negative alpha result, this study will accurately assess the effectiveness of Super Bowl advertising in terms of stock performance.
ContributorsWynne, Shannon Elizabeth (Author) / Budolfson, Arthur (Thesis director) / Smith, Geoffrey (Committee member) / Department of Finance (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-12
Description
Elon Musk is known for making controversial tweets, which often lead to lawsuits. Our thesis focuses on analyzing the effect that these individual tweets have on stock prices. Our hypothesis focuses on the idea that when Elon Musk makes a controversial tweet, the volatility of Tesla stock will increase, while the price of Tesla stock will on average decrease. The thirteen tweets that we are examining are the tweets that we deemed to be most important, which are measured by the amount of press coverage that they have received. We also evaluated the effect that two different lawsuits that stemmed from Musk’s reckless tweets had on Tesla stock. After evaluating the effect that Elon Musk’s tweets had on the stock volume and price, we will then determine whether or not Elon Musk and other CEO’s alike should be able to tweet in a similar manner. In order to analyze stock movement, volume, and significance we imported statistical data from Yahoo Finance and Nasdaq into Excel. From there, We added charts to model the volatility and the direction of price data. Additionally, we created separate indexes to compare stock moves and test for abnormal returns. From these returns we were able to calculate the alpha and beta for Tesla, its peers and competitors. To analyze Musk’s tweets, we collected close to 7,000 tweets and ordered them chronologically in Excel. With the combination of the stock and tweet data, we were in an excellent spot to analyze the data and come to a conclusion.
ContributorsDe Roo, Gilles (Co-author) / Lueck, Elliott (Co-author) / Budolfson, Arthur (Thesis director) / Hertzel, Michael (Committee member) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05