Matching Items (23)
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- All Subjects: Finance
- Creators: WPC Graduate Programs
- Creators: Budolfson, Arthur
Description
The Covid-19 pandemic has made a significant impact on both the stock market and the<br/>global economy. The resulting volatility in stock prices has provided an opportunity to examine<br/>the Efficient Market Hypothesis. This study aims to gain insights into the efficiency of markets<br/>based on stock price performance in the Covid era. Specifically, it investigates the market’s<br/>ability to anticipate significant events during the Covid-19 timeline beginning November 1, 2019<br/><br/>and ending March 31, 2021. To examine the efficiency of markets, our team created a Stay-at-<br/>Home Portfolio, experiencing economic tailwinds from the Covid lockdowns, and a Pandemic<br/><br/>Loser Portfolio, experiencing economic headwinds from the Covid lockdowns. Cumulative<br/>returns of each portfolio are benchmarked to the cumulative returns of the S&P 500. The results<br/>showed that the Efficient Market Hypothesis is likely to be valid, although a definitive<br/>conclusion cannot be made based on the scope of the analysis. There are recommendations for<br/>further research surrounding key events that may be able to draw a more direct conclusion.
ContributorsBrock, Matt Ian (Co-author) / Beneduce, Trevor (Co-author) / Craig, Nicko (Co-author) / Hertzel, Michael (Thesis director) / Mindlin, Jeff (Committee member) / Department of Finance (Contributor) / Economics Program in CLAS (Contributor) / WPC Graduate Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
The purpose of our research was to develop recommendations and/or strategies for Company A's data center group in the context of the server CPU chip industry. We used data collected from the International Data Corporation (IDC) that was provided by our team coaches, and data that is accessible on the internet. As the server CPU industry expands and transitions to cloud computing, Company A's Data Center Group will need to expand their server CPU chip product mix to meet new demands of the cloud industry and to maintain high market share. Company A boasts leading performance with their x86 server chips and 95% market segment share. The cloud industry is dominated by seven companies Company A calls "The Super 7." These seven companies include: Amazon, Google, Microsoft, Facebook, Alibaba, Tencent, and Baidu. In the long run, the growing market share of the Super 7 could give them substantial buying power over Company A, which could lead to discounts and margin compression for Company A's main growth engine. Additionally, in the long-run, the substantial growth of the Super 7 could fuel the development of their own design teams and work towards making their own server chips internally, which would be detrimental to Company A's data center revenue. We first researched the server industry and key terminology relevant to our project. We narrowed our scope by focusing most on the cloud computing aspect of the server industry. We then researched what Company A has already been doing in the context of cloud computing and what they are currently doing to address the problem. Next, using our market analysis, we identified key areas we think Company A's data center group should focus on. Using the information available to us, we developed our strategies and recommendations that we think will help Company A's Data Center Group position themselves well in an extremely fast growing cloud computing industry.
ContributorsJurgenson, Alex (Co-author) / Nguyen, Duy (Co-author) / Kolder, Sean (Co-author) / Wang, Chenxi (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Department of Finance (Contributor) / Department of Management (Contributor) / Department of Information Systems (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Accountancy (Contributor) / WPC Graduate Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
This paper intends to inform the reader about the current state of crowdfunding, also known as crowdsourced funding, as of early May 2014. Crowdfunding has proven to be an interesting alternate to other more common financing vehicles with its ability to unite people over common ideas and projects without requiring the contribution of large amounts of capital. Further, the changing legal landscape invites a new era of deregulation that makes crowdfunding easier than ever before. This paper contains explanations of the different types of crowdfunding, platforms (websites), and the international landscape particularly of the US and Europe as well as statistics regarding the predicted future growth of the industry.
ContributorsMurphy, Kevin Edward (Author) / Budolfson, Arthur (Thesis director) / Schein, Stephen (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor)
Created2014-05
Description
The goal of this thesis is to motivate college students to be financially aware and drive them toward attainable financial goals and freedom through budgeting. By providing a foundation of financial knowledge, they can begin to make intelligent decisions about their purchases. After they learn about their current spending habits, students can soundly determine what they have monetarily and then how to allocate that money appropriately. The paper outlines different categories these students should focus on fiscally, like rent and housing as the largest expenses and entertainment expenses as a common pitfall in a college student's budget. Constant financial awareness is reiterated throughout, indicating this is a day-to-day skill to develop. The thesis finally ties up with discussing financing options for college and life in general, with student loans, credit cards, and savings.
ContributorsSchachte, Jessica Linn (Author) / Budolfson, Arthur (Thesis director) / Hoffman, David (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor)
Created2013-12
Description
The object of the present study is to examine methods in which the company can optimize their costs on third-party suppliers whom oversee other third-party trade labor. The third parties in scope of this study are suspected to overstaff their workforce, thus overcharging the company. We will introduce a complex spreadsheet model that will propose a proper project staffing level based on key qualitative variables and statistics. Using the model outputs, the Thesis team proposes a headcount solution for the company and problem areas to focus on, going forward. All sources of information come from company proprietary and confidential documents.
ContributorsLoo, Andrew (Co-author) / Brennan, Michael (Co-author) / Sheiner, Alexander (Co-author) / Hertzel, Michael (Thesis director) / Simonson, Mark (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / WPC Graduate Programs (Contributor) / School of Accountancy (Contributor)
Created2014-05
DescriptionA group project working to implemented programs in the Town of Gilbert that build an entrepreneurial ecosystem within the town.
ContributorsCarneal, Tracy (Co-author) / Browning, Kelcey (Co-author) / Camoriano, James (Co-author) / Badulescu, Chris (Co-author) / Lindsey, Laura (Thesis director) / Riddel, Dana (Committee member) / Barrett, The Honors College (Contributor) / School of Accountancy (Contributor) / WPC Graduate Programs (Contributor)
Created2014-05
Description
This paper investigates whether measures of investor sentiment can be used to predict future total returns of the S&P 500 index. Rolling regressions and other statistical techniques are used to determine which indicators contain the most predictive information and which time horizons' returns are "easiest" to predict in a three year data set. The five "most predictive" indicators are used to predict 180 calendar day future returns of the market and simulated investment of hypothetical accounts is conducted in an independent six year data set based on the rolling regression future return predictions. Some indicators, most notably the VIX index, appear to contain predictive information which led to out-performance of the accounts that invested based on the rolling regression model's predictions.
ContributorsDundas, Matthew William (Author) / Boggess, May (Thesis director) / Budolfson, Arthur (Committee member) / Hedegaard, Esben (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Finance (Contributor)
Created2013-12
Description
Over the course of six months, we have worked in partnership with Arizona State University and a leading producer of semiconductor chips in the United States market (referred to as the "Company"), lending our skills in finance, statistics, model building, and external insight. We attempt to design models that help predict how much time it takes to implement a cost-saving project. These projects had previously been considered only on the merit of cost savings, but with an added dimension of time, we hope to forecast time according to a number of variables. With such a forecast, we can then apply it to an expense project prioritization model which relates time and cost savings together, compares many different projects simultaneously, and returns a series of present value calculations over different ranges of time. The goal is twofold: assist with an accurate prediction of a project's time to implementation, and provide a basis to compare different projects based on their present values, ultimately helping to reduce the Company's manufacturing costs and improve gross margins. We believe this approach, and the research found toward this goal, is most valuable for the Company. Two coaches from the Company have provided assistance and clarified our questions when necessary throughout our research. In this paper, we begin by defining the problem, setting an objective, and establishing a checklist to monitor our progress. Next, our attention shifts to the data: making observations, trimming the dataset, framing and scoping the variables to be used for the analysis portion of the paper. Before creating a hypothesis, we perform a preliminary statistical analysis of certain individual variables to enrich our variable selection process. After the hypothesis, we run multiple linear regressions with project duration as the dependent variable. After regression analysis and a test for robustness, we shift our focus to an intuitive model based on rules of thumb. We relate these models to an expense project prioritization tool developed using Microsoft Excel software. Our deliverables to the Company come in the form of (1) a rules of thumb intuitive model and (2) an expense project prioritization tool.
ContributorsAl-Assi, Hashim (Co-author) / Chiang, Robert (Co-author) / Liu, Andrew (Co-author) / Ludwick, David (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / Department of Finance (Contributor) / Department of Economics (Contributor) / Department of Supply Chain Management (Contributor) / School of Accountancy (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / WPC Graduate Programs (Contributor)
Created2015-05
Description
The intent of this paper is inform and educate people on micro-investing, so they can better understand this new and growing category of investing. Given that micro-investing is a relatively new phenomenon, people naturally have many questions about it. What is micro-investing, and what makes it different from traditional investing? What are the origins of this growing segment of financial technology? What features and characteristics do micro-investing platforms have in common and what differentiates them from each other? Is micro-investing viable and cost effective, and if so, is it right for you? What is the future of micro-investing, and is it here to stay? This paper seeks to answer these questions and additional questions that the reader may have.
Contributorsde la Vara, Nicholas (Author) / Budolfson, Arthur (Thesis director) / Hoffman, David (Committee member) / Department of Finance (Contributor, Contributor) / Department of Management and Entrepreneurship (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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