Matching Items (33)
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- All Subjects: Finance
- All Subjects: Physics
- Creators: School of Mathematical and Statistical Sciences
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
- Status: Published
Description
Preliminary feasibility studies for two possible experiments with the GlueX detector, installed in Hall D of Jefferson Laboratory, are presented. First, a general study of the feasibility of detecting the ηC at the current hadronic rate is discussed, without regard for detector or reconstruction efficiency. Second, a study of the use of statistical methods in studying exotic meson candidates is outlined, describing methods and providing preliminary data on their efficacy.
ContributorsPrather, Benjamin Scott (Author) / Ritchie, Barry G. (Thesis director) / Dugger, Michael (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Physics (Contributor)
Created2015-05
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 explores the history of sovereign debt default in developing economies and attempts to highlight the mistakes and accomplishments toward achieving debt sustainability. In the past century, developing economies have received considerable investment due to higher returns and a degree of disregard for the risks accompanying these investments. As the former Citibank chairman, Walter Wriston articulated, "Countries don't go bust" (This Time is Different, 51). Still, unexpected negative externalities have shattered this idea as the majority of developing economies follow a cyclical pattern of default. As coined by Reinhart and Rogoff, sovereign governments that fall into this continuous cycle have become known as serial defaulters. Most developed markets have not defaulted since World War II, thus escaping this persistent trap. Still, there have been developing economies that have been able to transition out of serial defaulting. These economies are able to leverage debt to compound growth without incurring the protracted consequences of a default. Although the cases are few, we argue that developing markets such as Chile, Mexico, Russia, and Uruguay have been able to escape this vicious cycle. Thus, our research indicates that collaborative debt restructurings coupled with long term economic policies are imperative to transitioning out of debt intolerance and into a sustainable debt position. Successful economies are able to leverage debt to create strong foundational growth rather than gambling with debt in the hopes of achieving rapid catch- up growth.
ContributorsPitt, Ryan (Co-author) / Martinez, Nick (Co-author) / Choueiri, Robert (Co-author) / Goegan, Brian (Thesis director) / Silverman, Daniel (Committee member) / Department of Economics (Contributor) / Department of Information Systems (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Politics and Global Studies (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
This paper provides evidence through an event study, portfolio simulation, and regression analysis that insider trading, when appropriately aggregated, has predictive power for abnormal risk-adjusted returns on some country and sector exchange traded funds (ETFs). I examine ETFs because of their broad scope and liquidity. ETF markets are relatively efficient and, thus, the effects I document are unlikely to appear in ETF markets. My evidence that aggregated insider trading predicts abnormal returns in some ETFs suggests that aggregated insider trading is likely to have predictive power for financial assets traded in less efficient markets. My analysis depends on specialized insider trading data covering 88 countries is generously provided by 2iQ.
ContributorsKerker, Mackenzie Alan (Author) / Coles, Jeffrey (Thesis director) / Mcauley, Daniel (Committee member) / Licon, Wendell (Committee member) / Barrett, The Honors College (Contributor) / Department of Economics (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Finance (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
A Guide to Financial Mathematics is a comprehensive and easy-to-use study guide for students studying for the one of the first actuarial exams, Exam FM. While there are many resources available to students to study for these exams, this study is free to the students and offers an approach to the material similar to that of which is presented in class at ASU. The guide is available to students and professors in the new Actuarial Science degree program offered by ASU. There are twelve chapters, including financial calculator tips, detailed notes, examples, and practice exercises. Included at the end of the guide is a list of referenced material.
ContributorsDougher, Caroline Marie (Author) / Milovanovic, Jelena (Thesis director) / Boggess, May (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
Description
We develop the mathematical tools necessary to describe the interaction between a resonant pole and a threshold energy. Using these tools, we analyze the properties an opening threshold has on the resonant pole mass (the "cusp effect"), leading to an effect called "pole-dragging." We consider two models for resonances: a molecular, mesonic model, and a color-nonsinglet diquark plus antidiquark model. Then, we compare the pole-dragging effect due to these models on the masses of the f0(980), the X(3872), and the Zb(10610) and compare the effect's magnitude. We find that, while for lower masses, such as the f 0 (980), the pole-dragging effect that arises from the molecular model is more significant, the diquark model's pole-dragging effect becomes dominant at higher masses such as those of the X(3872) and the Z b (10610). This indicates that for lower threshold energies, diquark models may have less significant effects on predicted resonant masses than mesonic models, but for higher threshold energies, it is necessary to include the pole-dragging effect due to a diquark threshold in high-precision QCD calculations.
ContributorsBlitz, Samuel Harris (Author) / Richard, Lebed (Thesis director) / Comfort, Joseph (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Physics (Contributor) / Barrett, The Honors College (Contributor)
Created2015-05
Description
The COVID-19 pandemic has and will continue to radically shift the workplace. An increasing percentage of the workforce desires flexible working options and, as such, firms are likely to require less office space going forward. Additionally, the economic downturn caused by the pandemic provides an opportunity for companies to secure favorable rent rates on new lease agreements. This project aims to evaluate and measure Company X’s potential cost savings from terminating current leases and downsizing office space in five selected cities. Along with city-specific real estate market research and forecasts, we employ a four-stage model of Company X’s real estate negotiation process to analyze whether existing lease agreements in these cities should be renewed or terminated.
ContributorsSaker, Logan (Co-author) / Ries, Sarah (Co-author) / Hegardt, Brandon (Co-author) / Patterson, Jack (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Department of Finance (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Since the acceptance of Einstein's special theory of relativity by the scientific community, authors of science fiction have used the concept of time dilation to permit seemingly impossible feats. Simple spacecraft acceleration schemes involving time dilation have been considered by scientists and fiction writers alike. Using an original Java program based upon the differential equations for special relativistic kinematics, several scenarios for round trip excursions at relativistic speeds are calculated and compared, with particular attention to energy budget and relativistic time passage in all relevant frames.
ContributorsAlfson, Jonathan William (Author) / Jacob, Richard (Thesis director) / Covatto, Carl (Committee member) / Foy, Joseph (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Physics (Contributor)
Created2015-05
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