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- All Subjects: Finance
- Creators: Barrett, The Honors College
- Creators: Wahal, Sunil
Description
In order to discover if Company X's current system of local trucking is the most efficient and cost-effective way to move freight between sites in the Western U.S., we will compare the current system to varying alternatives to see if there are potential avenues for Company X to create or implement an improved cost saving freight movement system.
ContributorsPicone, David (Co-author) / Krueger, Brandon (Co-author) / Harrison, Sarah (Co-author) / Way, Noah (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Barrett, The Honors College (Contributor) / Department of Supply Chain Management (Contributor) / Department of Finance (Contributor) / Economics Program in CLAS (Contributor) / School of Accountancy (Contributor) / W. P. Carey School of Business (Contributor) / Sandra Day O'Connor College of Law (Contributor)
Created2015-05
Description
Company X is one of the world's largest semiconductor companies in the world, having a current market capitalization of 177.44 Billion USD, an enterprise value of 173.6 Billion USD, and generated 52.7 billion USD in revenue in fiscal year 2013. Recently, Company X has been looking to expand its Foundry business. The Foundry business in the semiconductor business is the actual process of making the chips. This process can be approached in several different ways by companies who need their chips built. A company, like TSMC, can be considered a pure-play company and only makes chips for other companies. A fabless company, like Apple, creates its own chip design and then allows another company to build them. It also uses other chip designs for its products, but outsources the building to another company. Lastly, the integrated device manufacturing companies like Samsung or Company X both design and build the chip. The foundry industry is a rather novel market for Company X because it owns less than 1 percent of the market. However, the industry itself is rather large, generating a total of 40 billion dollars in revenue annually, with expectations to have increasing year over year growth into the foreseeable future. The industry is fairly concentrated with TSMC being the top competitor, owning roughly 50 percent of the market with Samsung and Global Foundries lagging behind as notable competitors. It is a young industry and there is potential opportunity for companies that want to get into the business. For Company X, it is not only another market to get into, but also an added business segment to supplant their business segments that are forecasted to do poorly in the near future. This thesis will analyze the financial opportunity for Company X in the foundry space. Our final product is a series of P&L's which illustrate our findings. The results of our analysis were presented and defended in front of a panel of Company X managers and executives.
ContributorsJones, Trevor (Author) / Matiski, Matthew (Co-author) / Green, Alex (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Department of Finance (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2015-05
Description
Dr. Dean Kashiwagi created a new thinking paradigm, Information Measurement Theory (IMT), which utilizes the understanding of natural laws to help individuals minimize decision-making and risk, which leads to reduced stress. In this new paradigm, any given situation can only have one unique outcome. The more information an individual has for the given situation, the better they can predict the outcome. Using IMT can help correctly "predict the future" of any situation if given enough of the correct information. A prime example of using IMT would be: to correctly predict what a young woman will be like when she's older, simply look at the young woman's mother. In essence, if you can't fall in love with the mother, don't marry the young woman. The researchers are utilizing the concept of IMT and extrapolating it to the financial investing world. They researched different financial investing strategies and were able to come to the conclusion that a strategy utilizing IMT would yield the highest results for investors while minimizing stress. Investors using deductive logic to invest received, on average, 1300% more returns than investors who did not over a 25-year period. Where other investors made many decisions and were constantly stressed with the tribulations of the market, the investors utilizing IMT made one decision and made much more than other investors. The research confirms the stock market will continue to increase over time by looking at the history of the stock market from a birds-eye view. Throughout the existence of the stock market, there have been highs and lows, but at the end of the day, the market continues to break through new ceilings. Investing in the stock market can be a dark and scary place for the blind investor. Using the concept of IMT can eliminate that blindfold to reduce stress on investors while earning the highest financial return potential. Using the basis of IMT, the researchers predict the market will continue to increase in the future; in conclusion, the best investment strategy is to invest in blue chip stocks that have a history of past success, in order to capture secure growth with minimal risk and stress.
ContributorsBerns, Ryan (Co-author) / Ybanez, Julian (Co-author) / Kashiwagi, Dean (Thesis director) / Kashiwagi, Jacob (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Department of Marketing (Contributor) / W. P. Carey School of Business (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
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
Financial Intelligence Pays Off blog is an easy to use blog for high school juniors and seniors and college students to access in order to receive a quick overview of essential financial topics. There are many sources and college courses for students to take to get a more in-depth understanding of topics such as saving, filing taxes, learning about credit but many times students do not know about these courses. However, it is often that courses are restricted to students who are business majors and online sources sometimes use to technical of terminology for young adults to follow along. The goal of this blog is for it to give students just a quick overview of what taxes are, how to manage and have a good credit score, how to keep a budget and other essential financial tasks. There are five topics covered in the blog as well as resources for students to access if they would like more information on a topic.
ContributorsFavata, Danielle (Co-author) / Perez-Vargas, Sofia (Co-author) / Sadusky, Brian (Thesis director) / Hoffman, David (Committee member) / WPC Graduate Programs (Contributor) / School of Accountancy (Contributor) / Department of Information Systems (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
This paper seeks to emphasize how the presence of uncertainty, speculation and leverage work in concert within the stock market to exacerbate crashes in a cyclical market. It analyzes three major stock market events: the crash of Oct. 19, 1987, “Black Monday;” the dotcom bust, from 1999 to 2002; and the subprime mortgage crisis, from 2007 to 2010. Within each event period I define determinants or measurements of uncertainty, speculation. Analysis of how these three concepts functioned during boom and bust will highlight how their presence can amplify the magnitude of a crash. This paper postulates that the amount of leverage during a crash determines how long-term its effects will be. This theory is fortified by extensive research and interviews with experts in the stock market who had a front row view of the discussed crises.
ContributorsGraff, Veronica Camille (Author) / Leckey, Andrew (Thesis director) / Cohen, Sarah (Committee member) / Historical, Philosophical & Religious Studies (Contributor) / Walter Cronkite School of Journalism & Mass Comm (Contributor, Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
When making investment decisions many different indicators are taken into consideration before picking a stock/corporation to invest in (retail or institutional). Traditionally these indicators tend to be financial measures such as earnings per share, price to earnings ratio, price to book value ratio, dividend yield/payout ratio, etc. Often these indicators do not take into consideration the actual running intricacies of a company as they are simply based on historical financial statements, thus limiting an investor's decision-making ability. In this paper I analyze several companies stock performance to see if analyzing operational factors such as supply chain management before making an investment decision would have resulted in a profitable investment and thus prove as a reliable investment indicator. To do this I focused my analysis over a period of 5 years on two companies within three different industries; Fast Food, Processing, and Ecommerce. These industries were selected as the nature of their businesses require intensive supply chains thus this strategy would be most applicable to them as opposed to a software or IT company. Of the two companies selected from each respective industry one company would be listed/analyzed in Gartner's ranking of the "Annual Supply Chain Top 25" while the other company would not be. This Gartner ranking would serve as a measure of whether or not a company had a good supply chain. These companies then had their traditional financial metrics evaluated to see if supply chain analysis indirectly encapsulated some of these metrics as well. The goal of this analysis was to find if there was a strong correlation between companies listed on Gartner's rating scale and strong stock performance. If this was true this would suggest that there is a benefit to be captured by investors through using supply chain analysis as an indicator when making investment decisions.
ContributorsThompson, Tyler Thomas (Author) / Kellso, James (Thesis director) / Smith, Geoffrey (Committee member) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Exchange traded funds (ETFs) in many ways are similar to more traditional closed-end mutual funds, although thee differ in a crucial way. ETFs rely on a creation and redemption feature to achieve their functionality and this mechanism is designed to minimize the deviations that occur between the ETF’s listed price and the net asset value of the ETF’s underlying assets. However while this does cause ETF deviations to be generally lower than their mutual fund counterparts, as our paper explores this process does not eliminate these deviations completely. This article builds off an earlier paper by Engle and Sarkar (2006) that investigates these properties of premiums (discounts) of ETFs from their fair market value. And looks to see if these premia have changed in the last 10 years. Our paper then diverges from the original and takes a deeper look into the standard deviations of these premia specifically.
Our findings show that over 70% of an ETFs standard deviation of premia can be explained through a linear combination consisting of two variables: a categorical (Domestic[US], Developed, Emerging) and a discrete variable (time-difference from US). This paper also finds that more traditional metrics such as market cap, ETF price volatility, and even 3rd party market indicators such as the economic freedom index and investment freedom index are insignificant predictors of an ETFs standard deviation of premia when combined with the categorical variable. These findings differ somewhat from existing literature which indicate that these factors should have a significant impact on the predictive ability of an ETFs standard deviation of premia.
Our findings show that over 70% of an ETFs standard deviation of premia can be explained through a linear combination consisting of two variables: a categorical (Domestic[US], Developed, Emerging) and a discrete variable (time-difference from US). This paper also finds that more traditional metrics such as market cap, ETF price volatility, and even 3rd party market indicators such as the economic freedom index and investment freedom index are insignificant predictors of an ETFs standard deviation of premia when combined with the categorical variable. These findings differ somewhat from existing literature which indicate that these factors should have a significant impact on the predictive ability of an ETFs standard deviation of premia.
ContributorsZhang, Jingbo (Co-author, Co-author) / Henning, Thomas (Co-author) / Simonson, Mark (Thesis director) / Licon, L. Wendell (Committee member) / Department of Finance (Contributor) / Department of Information Systems (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Exchange traded funds (ETFs) in many ways are similar to more traditional closed-end mutual
funds, although thee differ in a crucial way. ETFs rely on a creation and redemption feature to
achieve their functionality and this mechanism is designed to minimize the deviations that occur
between the ETF’s listed price and the net asset value of the ETF’s underlying assets. However
while this does cause ETF deviations to be generally lower than their mutual fund counterparts,
as our paper explores this process does not eliminate these deviations completely. This article
builds off an earlier paper by Engle and Sarkar (2006) that investigates these properties of
premiums (discounts) of ETFs from their fair market value. And looks to see if these premia
have changed in the last 10 years. Our paper then diverges from the original and takes a deeper
look into the standard deviations of these premia specifically.
Our findings show that over 70% of an ETFs standard deviation of premia can be
explained through a linear combination consisting of two variables: a categorical (Domestic[US],
Developed, Emerging) and a discrete variable (time-difference from US). This paper also finds
that more traditional metrics such as market cap, ETF price volatility, and even 3rd party market
indicators such as the economic freedom index and investment freedom index are insignificant
predictors of an ETFs standard deviation of premia. These findings differ somewhat from
existing literature which indicate that these factors should have a significant impact on the
predictive ability of an ETFs standard deviation of premia.
funds, although thee differ in a crucial way. ETFs rely on a creation and redemption feature to
achieve their functionality and this mechanism is designed to minimize the deviations that occur
between the ETF’s listed price and the net asset value of the ETF’s underlying assets. However
while this does cause ETF deviations to be generally lower than their mutual fund counterparts,
as our paper explores this process does not eliminate these deviations completely. This article
builds off an earlier paper by Engle and Sarkar (2006) that investigates these properties of
premiums (discounts) of ETFs from their fair market value. And looks to see if these premia
have changed in the last 10 years. Our paper then diverges from the original and takes a deeper
look into the standard deviations of these premia specifically.
Our findings show that over 70% of an ETFs standard deviation of premia can be
explained through a linear combination consisting of two variables: a categorical (Domestic[US],
Developed, Emerging) and a discrete variable (time-difference from US). This paper also finds
that more traditional metrics such as market cap, ETF price volatility, and even 3rd party market
indicators such as the economic freedom index and investment freedom index are insignificant
predictors of an ETFs standard deviation of premia. These findings differ somewhat from
existing literature which indicate that these factors should have a significant impact on the
predictive ability of an ETFs standard deviation of premia.
ContributorsHenning, Thomas Louis (Co-author) / Zhang, Jingbo (Co-author) / Simonson, Mark (Thesis director) / Wendell, Licon (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05