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
This paper looks at defined contribution 401(k) plans in the United States to analyze whether or not participants have plans with better plan characteristics defined in this study by paying more for administration services, advisory services, and investments. By collecting and analyzing Form 5500 and audit data, I find that there is no relation between how much a plan and its participants are paying for recordkeeping, advisory, and investment fees and the analyzed characteristics of the plan that they receive in regards to active/passive allocation, revenue share, and the performance of the funds.
ContributorsAziz, Julian (Author) / Wahal, Sunil (Thesis director) / Bharath, Sreedhar (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / Department of Finance (Contributor)
Created2015-05
Description
Natural Language Processing (NLP) techniques have increasingly been used in finance, accounting, and economics research to analyze text-based information more efficiently and effectively than primarily human-centered methods. The literature is rich with computational textual analysis techniques applied to consistent annual or quarterly financial fillings, with promising results to identify similarities between documents and firms, in addition to further using this information in relation to other economic phenomena. Building upon the knowledge gained from previous research and extending the application of NLP methods to other categories of financial documents, this project explores financial credit contracts, better understanding the information provided through their textual data by assessing patterns and relationships between documents and firms. The main methods used throughout this project is Term Frequency-Inverse Document Frequency (to represent each document as a numerical vector), Cosine Similarity (to measure the similarity between contracts), and K-Means Clustering (to organically derive clusters of documents based on the text included in the contract itself). Using these methods, the dimensions analyzed are various grouping methodologies (external industry classifications and text derived classifications), various granularities (document-wise and firm-wise), various financial documents associated with a single firm (the relationship between credit contracts and 10-K product descriptions), and how various mean cosine similarity distributions change over time.
ContributorsLiu, Jeremy J (Author) / Wahal, Sunil (Thesis director) / Bharath, Sreedhar (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / School for the Future of Innovation in Society (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
This thesis examines the impact of price changes of select microprocessors on the market share and 5-year gross profit net present values of Company X in the networking market through a multi-step analysis. The networking market includes segments including media processing, cloud services, security, routers & switches, and access points. For this thesis our team focused on the routers & switches, as well as the security segments. Company X wants to capitalize on the expected growth of the networking market as it transitions to its fifth generation (henceforth referred to as 5G) by positioning itself favorably in its customers eyes through high quality products offered at competitive prices. Our team performed a quantitative analysis of benchmark data to measure the performances of Company X's products against those of its competitors. We collected this data from third party computer reviewers, as well as the published reports of Company X and its competitors. Through the use of a preference matrix, we then normalized this performance data to adjust for different scales. In order to provide a well-rounded analysis, we adjusted these normalized performances for power consumption (using thermal design power as a proxy) as well as price. We believe these adjusted performances are more valuable than raw benchmark data, as they appeal to the demands of price-sensitive customers. Based on these comparisons, our team was able to assess price changes for their market and discounted financial impact on Company X. Our findings challenge the current pricing of one of the two products being analyzed and suggests a 9% decrease in the price of said product. This recommendation most effectively positions Company X for the development of 5G by offering the best balance of market share and NPV.
ContributorsArias, Stephen (Co-author) / Masson, Taylor (Co-author) / McCall, Kyle (Co-author) / Dimitroff, Alex (Co-author) / Hardy, Sebastian (Co-author) / Simonson, Mark (Thesis director) / Haller, Marcie (Committee member) / School of Accountancy (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05