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- Creators: Department of Finance
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
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- Resource Type: Text
Description
For this thesis, the authors would like to create a hypothetical Private Equity Real Estate Investment firm that focuses on creating value for partners by taking an opportunistic approach to acquiring under-performing urban multi-family properties with large upside potential for investing. The project will focus on both the market analysis and financial modeling associated with investment strategy and transactions. There is a substantial amount of complexity within commercial real estate and this thesis seeks to offer an accurate and comprehensive documentary of the process, while simplifying it for everyday readers. Additionally, there are a significant amount of risk factors associated with investment decisions, so the best practices from the industry documented in this manuscript are valuable tools for successful investing in the future. To gain the most profound and reliable industry knowledge, the authors leveraged the experience of dozens of industry professionals through research and personal interviews. Through careful analysis, the authors were able to ascertain the current economic position in the real estate cycle and to create a plan for future investing. Additionally, they were able to identify and evaluate a specific asset for purchase. As a result, the authors found that multifamily properties are a sound investment for the next two years and that the company should slowly start to shift directions to office and retail in 2018.
ContributorsBacon, David (Co-author) / Soto, Justin (Co-author) / Kashiwagi, Dean (Thesis director) / Kashiwagi, Jacob (Committee member) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / Department of Marketing (Contributor) / W. P. Carey School of Business (Contributor) / School of Accountancy (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
My Honors Thesis is about answering a central question regarding the business of real estate: "What is the return on investment of obtaining a real estate license?" I focused my research on the monetary, time, and other value factors that affect the initial cost of securing a real estate salesperson license in the State of Arizona (costs) and the amount of money a licensed salesperson makes as a result of having a salesperson license (income). Licensees make this trade-off: the cost in terms of real dollars to obtain a license, as well as the opportunity costs associated with the time to secure, start using, and begin to earn money by way of a salesperson license. To answer the central question I conducted a survey of active licensees in order to determine the value ascribed to holding a real estate salesperson license. Through my research, I concluded that there is not a single number that can be assigned to a real estate license that indicates its value, but the data collected reveals that the return on investment has the potential to be great. Upfront costs and fees necessary to obtain a license are insignificant when the commission a licensee can then make from a single transaction is enough to cover those expenses. Therefore, based on the survey results and research into the initial costs associated with obtaining a real estate license, there appears to be sufficient data to support a positive return on investment and warrant obtaining a real estate license.
ContributorsSanders, Sarah (Author) / Stapp, Mark (Thesis director) / Koblenz, Blair (Committee member) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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
We gathered and analyzed key data from a wide-range of competitors in the foundry, fabless, and Integrated design manufacturing business. After detecting a downward trend in the return of invested capital (ROIC) and higher capital intensity of Company X, we searched for alternatives to turn this around. We conclude that, to decrease the net PPE of Company X, a sale-leaseback transaction would help Company X reduce their balance sheet and provided financing to advance their manufacturing capabilities.
ContributorsBhat, Arjun Khandige (Co-author) / Brock, Ethan (Co-author) / Gamperl, Max (Co-author) / Gupta, Viraj (Co-author) / Macha, Sanketh (Co-author) / Simonson, Mark (Thesis director) / Duran, Juan Carlos (Committee member) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Music streaming services have affected the music industry from both a financial and legal standpoint. Their current business model affects stakeholders such as artists, users, and investors. These services have been scrutinized recently for their imperfect royalty distribution model. Covid-19 has made these discussions even more relevant as touring income has come to a halt for musicians and the live entertainment industry. <br/>Under the current per-stream model, it is becoming exceedingly hard for artists to make a living off of streams. This forces artists to tour heavily as well as cut corners to create what is essentially “disposable art”. Rapidly releasing multiple projects a year has become the norm for many modern artists. This paper will examine the licensing framework, royalty payout issues, and propose a solution.
ContributorsKoudssi, Zakaria Corley (Author) / Sadusky, Brian (Thesis director) / Koretz, Lora (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
This thesis explores the profitability of various technical trading strategies to explore their ability, generate returns in the American stock market. All strategies are based on five popular technical indicators, including the volume-weighted average price, moving average convergent-divergent index, Bollinger bands, support/resistance, and simple momentum trading. Most strategies were tested from 2019-2022 and tested for the SPY and QQQ stocks, representing the S&P 500 and NASDAQ. 3 of the 26 strategies had win rates of over 50%, but several were able to greatly outperform broader market returns. The best performing strategies were based on simple momentum trading, while the MACD and Bollinger Bands produced the worst results. Some strategies based on simple momentum trading or Bollinger bands found results greatly exceeding standard market returns in recent years, but most do not.
ContributorsEberle-Taylor, Nicholas (Author) / Boguth, Oliver (Thesis director) / Ikram, Atif (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor)
Created2022-05
Description
The Solis Lofts Development Proposal thesis consisted of a full prospective development within the City of Tempe. Our team conducted a vast amount of market research to determine what sector of the market would provide the best return on investment. We organized meetings with local brokers from Cushman & Wakefield, CBRE, JLL, and Colliers International to learn more about the current market environment. Also, we organized meetings with local developers, architects, and lenders. These included Merit Partners, Sunbelt Holdings, MODUS Development, Catclar Investments, 5Visual, Butler Design Group, and Colonial Capital. Through the research we conducted we were able to successfully determine that a multifamily development within the City of Tempe would be a great way to enter the Commercial Real Estate Development field. Our project consisted of the full land acquisition process, architectural site plan review, financial analysis, and completion of the product.
ContributorsLiu, Braden John (Co-author) / Butura, Alexander (Co-author) / Zwillinger, Mason (Co-author) / Farnsworth, Yzaac (Co-author) / Sadusky, Brian (Thesis director) / Avrhami, Matthew (Committee member) / Department of Finance (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Although Spotify’s extensive library of songs are often seen broken up by “Top 100” and main lyrical genres, these categories are primarily based on popularity, artist and general mood alone. If a user wanted to create a playlist based on specific or situationally specific qualifiers from their own downloaded library, he/she would have to hand pick songs that fit the mold and create a new playlist. This is a time consuming process that may not produce the most efficient result due to human error. The objective of this project, therefore, was to develop an application to streamline this process, optimize efficiency, and fill this user need.
Song Sift is an application built using Angular that allows users to filter and sort their song library to create specific playlists using the Spotify Web API. Utilizing the audio feature data that Spotify attaches to every song in their library, users can filter their downloaded Spotify songs based on four main attributes: (1) energy (how energetic a song sounds), (2) danceability (how danceable a song is), (3) valence (how happy a song sounds), and (4) loudness (average volume of a song). Once the user has created a playlist that fits their desired genre, he/she can easily export it to their Spotify account with the click of a button.
Song Sift is an application built using Angular that allows users to filter and sort their song library to create specific playlists using the Spotify Web API. Utilizing the audio feature data that Spotify attaches to every song in their library, users can filter their downloaded Spotify songs based on four main attributes: (1) energy (how energetic a song sounds), (2) danceability (how danceable a song is), (3) valence (how happy a song sounds), and (4) loudness (average volume of a song). Once the user has created a playlist that fits their desired genre, he/she can easily export it to their Spotify account with the click of a button.
ContributorsDiMuro, Louis (Author) / Balasooriya, Janaka (Thesis director) / Chen, Yinong (Committee member) / Arts, Media and Engineering Sch T (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
This paper will examine the statistical significance of IRR dispersions caused by adjustments to property conditions. Many different economic metrics affect the returns and performance of real estate assets. During the underwriting process, many of these factors are considered and analyzed to find the true value of the asset given a set of market conditions. Because of the dynamic nature of the market, these factors fluctuate and therefore affect asset returns. Using Argus software, real estate managers can identify these variables and see how their adjustments affect asset returns in real-time. The beginning of this paper will start with an outline of the properties being analyzed, and well as financial information and market assumptions. For the statistical analysis, the Argus inputs that will be analyzed are:
1. Rental Revenue
2. Occupancy Rate
3. Tenant Improvements
4. Leasing Commissions
5. Operating Expenses
6. Capital Expenditures
7. Purchase Price
8. LTV
9. Debt Service Payment
10. Exit Sales Price
For the analysis, each variable will be individually adjusted without any changes to the other variables to ensure that changes in IRR are solely a result of the variable being adjusted. After the sensitivity analysis, each variable will be examined further the showcase differences in disparities and provide managerial insight. Finally, the findings will be applied to a modern-day scenario for additional insight on the practice use of the data. The importance of this data is that once analyzed, it can help real estate managers understand the main determinants of value in commercial real estate investments.
1. Rental Revenue
2. Occupancy Rate
3. Tenant Improvements
4. Leasing Commissions
5. Operating Expenses
6. Capital Expenditures
7. Purchase Price
8. LTV
9. Debt Service Payment
10. Exit Sales Price
For the analysis, each variable will be individually adjusted without any changes to the other variables to ensure that changes in IRR are solely a result of the variable being adjusted. After the sensitivity analysis, each variable will be examined further the showcase differences in disparities and provide managerial insight. Finally, the findings will be applied to a modern-day scenario for additional insight on the practice use of the data. The importance of this data is that once analyzed, it can help real estate managers understand the main determinants of value in commercial real estate investments.
ContributorsMakhija, Aditya (Author) / Stapp, Mark (Thesis director) / Koblenz, Blair (Committee member) / Department of Finance (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
This thesis is broken up into two parts: a research paper and a creative project. The paper provides an overview of the REIT universe as well as important historical and legal information about REITs. The creative project explores how REIT performance varied based on valuation multiples during a five-month period from October of 2021 to March of 2022. My initial objective was to determine whether a “growth” or “value” investment strategy worked best in the current market. However, I quickly discovered that the prevailing market conditions were far different than I expected. As a result, I gained valuable insight into how REITs behave during periods of market uncertainty.
ContributorsLicon, Lawrence (Author) / Koblenz, Blair (Thesis director) / Stapp, Mark (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor)
Created2022-05