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- All Subjects: Finance
- Creators: WPC Graduate Programs
- Resource Type: Text
Description
This thesis takes the form of a market research report with the goal of analyzing the implications of the United Kingdom (UK) leaving the European Union (EU) (known as “Brexit”) on London’s office commercial real estate market. The ultimate goal of this report is to make a prediction, firmly grounded in quantitative and qualitative research conducted over the past several months, as to the direction of London’s commercial real estate market going forward (post-Brexit). Within the commercial real estate sector, this paper narrows its focus to the office segment of the London market.
Understanding the political landscape is crucial to formulating a reasonable prediction as to the future of the London market. Aside from research reports and articles, our main insights into the political direction of Brexit come from our recordings from meetings in March of 2017 with two high-ranking members of Parliament and one member of the House of Lords—all of whom are members of the Tory Party (the meetings being held under the condition of anonymity). The below analysis will be followed by a discussion of the economics of Brexit, primarily focusing on the economic risks and uncertainties which have emerged after the vote, and which currently exist today. Such risks include the UK losing its financial passporting rights, weakening GDP and currency value, the potential for a reduction in foreign direct investment (FDI), and the potential loss of the service sector in the city of London due to not being able to access the European Single Market.
The report will shift focus to analyzing three competing viewpoints of the direction of the London market based on recordings from interviews of stakeholders in the London real estate market. One being an executive of one of the largest REITs in the UK, another being the Global Head of Real Estate at a top asset management firm, and another being a director at a large property consulting firm. The report includes these differing “sub-theses” in order to try to make sense of the vast market uncertainties post-Brexit as well as to contrast their viewpoints with where the market is currently and with the report’s investment recommendation.
The remainder of the report will consist of the methods used for analyzing market trends including how the data was modeled in order to make the investment recommendation. The report will analyze real estate and market metrics pre-Brexit, immediately after the vote, post-Brexit, and will conclude with future projections encapsulating the investment recommendation.
Understanding the political landscape is crucial to formulating a reasonable prediction as to the future of the London market. Aside from research reports and articles, our main insights into the political direction of Brexit come from our recordings from meetings in March of 2017 with two high-ranking members of Parliament and one member of the House of Lords—all of whom are members of the Tory Party (the meetings being held under the condition of anonymity). The below analysis will be followed by a discussion of the economics of Brexit, primarily focusing on the economic risks and uncertainties which have emerged after the vote, and which currently exist today. Such risks include the UK losing its financial passporting rights, weakening GDP and currency value, the potential for a reduction in foreign direct investment (FDI), and the potential loss of the service sector in the city of London due to not being able to access the European Single Market.
The report will shift focus to analyzing three competing viewpoints of the direction of the London market based on recordings from interviews of stakeholders in the London real estate market. One being an executive of one of the largest REITs in the UK, another being the Global Head of Real Estate at a top asset management firm, and another being a director at a large property consulting firm. The report includes these differing “sub-theses” in order to try to make sense of the vast market uncertainties post-Brexit as well as to contrast their viewpoints with where the market is currently and with the report’s investment recommendation.
The remainder of the report will consist of the methods used for analyzing market trends including how the data was modeled in order to make the investment recommendation. The report will analyze real estate and market metrics pre-Brexit, immediately after the vote, post-Brexit, and will conclude with future projections encapsulating the investment recommendation.
ContributorsHorn, Jonathan (Co-author) / Sidi, Adam (Co-author) / Bonadurer, Werner (Thesis director) / McDaniel, Cara (Committee member) / Department of Finance (Contributor) / School of Politics and Global Studies (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
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
By the year 2021, the gift card market is expected to grow to more than 200 billion dollars. Gift cards are extremely popular among consumers and retailers. They are the most requested gift of the holiday season. They are popular for retailers because gift card sales mean more first time customers, more returning customers, and more money spent in their stores. The growth of gift cards has been very rapid since their introduction by Blockbuster Entertainment in 1994. As the gift card market has increased, so too has gift card breakage. According to FASB ASC 405-20-40-3 gift card breakage is, "the portion of the dollar value of prepaid stored-value products that ultimately is not redeemed by product holders for cash or not used to purchase goods and/or services". The average consumer may contribute to gift card breakage by not using the full dollar amount of their gift card, or by losing the gift card and therefore not redeeming it. For 2011, breakage was expected to be around two billion dollars, roughly two percent of all gift cards purchased. Gift card breakage is free money for the retail companies. They are able to recognize the breakage as revenue without having to give up merchandise or services. Recently, abandoned property laws have minimized the profits on gift card breakage for large retailers. In states where abandoned property laws include gift cards, retailers have been forced to turn over the cash from their unused gift cards. These laws are going to have an effect on many large retailers as some recognize tens of millions of dollar in gift card breakage income but will no longer be able to do so.
ContributorsClasen, Jeffrey Steven (Author) / Call, Andrew (Thesis director) / Huston, Janet (Committee member) / School of Accountancy (Contributor) / WPC Graduate Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Company X is one of the world's largest manufacturer of semiconductors. The company relies on various suppliers in the U.S. and around the globe for its manufacturing process. The financial health of these suppliers is vital to the continuation of Company X's business without any material interruption. Therefore, it is in Company X's interest to monitor its supplier's financial performance. Company X has a supplier financial health model currently in use. Having been developed prior to watershed events like the Great Recession, the current model may not reflect the significant changes in the economic environment due to these events. Company X wants to know if there is a more accurate model for evaluating supplier health that better indicates business risk. The scope of this project will be limited to a sample of 24 suppliers representative of Company X's supplier base that are public companies. While Company X's suppliers consist of both private and public companies, the used of exclusively public companies ensures that we will have sufficient and appropriate data for the necessary analysis. The goal of this project is to discover if there is a more accurate model for evaluating the financial health of publicly traded suppliers that better indicates business risk. Analyzing this problem will require a comprehensive understanding of various financial health models available and their components. The team will study best practice and academia. This comprehension will allow us to customize a model by incorporating metrics that allows greater accuracy in evaluating supplier financial health in accordance with Company X's values.
ContributorsLi, Tong (Co-author) / Gonzalez, Alexandra (Co-author) / Park, Zoon Beom (Co-author) / Vogelsang, Meridith (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Mike (Committee member) / Department of Finance (Contributor) / Department of Information Systems (Contributor) / School of Accountancy (Contributor) / WPC Graduate Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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
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
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
Catastrophe events occur rather infrequently, but upon their occurrence, can lead to colossal losses for insurance companies. Due to their size and volatility, catastrophe losses are often treated separately from other insurance losses. In fact, many property and casualty insurance companies feature a department or team which focuses solely on modeling catastrophes. Setting reserves for catastrophe losses is difficult due to their unpredictable and often long-tailed nature. Determining loss development factors (LDFs) to estimate the ultimate loss amounts for catastrophe events is one method for setting reserves. In an attempt to aid Company XYZ set more accurate reserves, the research conducted focuses on estimating LDFs for catastrophes which have already occurred and have been settled. Furthermore, the research describes the process used to build a linear model in R to estimate LDFs for Company XYZ's closed catastrophe claims from 2001 \u2014 2016. This linear model was used to predict a catastrophe's LDFs based on the age in weeks of the catastrophe during the first year. Back testing was also performed, as was the comparison between the estimated ultimate losses and actual losses. Future research consideration was proposed.
ContributorsSwoverland, Robert Bo (Author) / Milovanovic, Jelena (Thesis director) / Zicarelli, John (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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
The purpose of this paper is to study the impact that poison pills have on the value of share prices after the cancellation of a transaction. While various studies have focused on the generic share price impact of poison pills, very few have focused on the impact of poison pills in cancelled transactions. Based on our research and analysis, in cancelled transactions, target firms that have poison pills prior to the transaction and target firms without poison pills generate returns above the announcement date premium and subsequent investment in the S&P 500 when held to the cancellation of the transaction and when held from cancellation to 6 months after the transaction. This analysis can contribute to the argument that holding shares of firms regardless of cancellation risk is preferable to taking profit at announcement date. Additionally, it can contribute to the study of undiscovered pricing impact of poison pills.
ContributorsChotalla, Gurkaran (Co-author) / Amjad, Hamza (Co-author) / Reddy, Samir (Co-author) / Stein, Luke (Thesis director) / Lindsey, Laura (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Finance (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12