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This paper examines dealers' inventory holding periods and the associated price markups on corporate bonds from 2003 to 2010. Changes in these measures explain a large part of the time series variation in aggregate corporate bond prices. In the cross-section, holding periods and markups overshadow extant liquidity measures and have

This paper examines dealers' inventory holding periods and the associated price markups on corporate bonds from 2003 to 2010. Changes in these measures explain a large part of the time series variation in aggregate corporate bond prices. In the cross-section, holding periods and markups overshadow extant liquidity measures and have significant explanatory power for individual bond prices. Both measures shed light on the credit spread puzzle: changes in credit spread are positively correlated with changes in holding periods and markups, and a large portion of credit spread changes is explained by them. The economic effects of holding periods and markups are particularly sharp during crisis periods.
ContributorsQian, Zhiyi (Author) / Wahal, Sunil (Thesis advisor) / Bharath, Sreedhar (Committee member) / Coles, Jeffrey (Committee member) / Mehra, Rajnish (Committee member) / Arizona State University (Publisher)
Created2012
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The current model of revenue generation for some free to play video games is preventing the companies controlling them from growing, but with a few changes in approach these issues could be alleviated. A new style of video games, called a MOBA (Massive Online Battle Arena) has emerged in the

The current model of revenue generation for some free to play video games is preventing the companies controlling them from growing, but with a few changes in approach these issues could be alleviated. A new style of video games, called a MOBA (Massive Online Battle Arena) has emerged in the past few years bringing with it a new style of generating wealth. Contrary to past gaming models, where users must either purchase the game outright, view advertisements, or purchase items to gain a competitive advantage, MOBAs require no payment of any kind. These are free to play computer games that provides users with all the tools necessary to compete with anyone free of charge; no advantages can be purchased in this game. This leaves the only way for users to provide money to the company through optional purchases of purely aesthetic items, only to be purchased if the buyer wishes to see their character in a different set of attire. The genre’s best in show—called League of Legends, or LOL—has spearheaded this method of revenue-generation. Fortunately for LOL, its level of popularity has reached levels never seen in video games: the world championships had more viewers than game 7 of the NBA Finals (Dorsey). The player base alone is enough to keep the company afloat currently, but the fact that they only convert 3.75% of the players into revenue is alarming. Each player brings the company an average of $1.32, or 30% of what some other free to play games earn per user (Comparing MMO). It is this low per player income that has caused Riot Games, the developer of LOL, to state that their e-sports division is not currently profitable. To resolve this issue, LOL must take on a more aggressive marketing plan. Advertisements for the NBA Finals cost $460,000 for 30 seconds, and LOL should aim for ads in this range (Lombardo). With an average of 3 million people logged on at any time, 90% of the players being male and 85% being between the ages of 16 and 30, advertising via this game would appeal to many companies, making a deal easy to strike (LOL infographic 2012). The idea also appeals to players: 81% of players surveyed said that an advertisement on the client that allows for the option to place an order would improve or not impact their experience. Moving forward with this, the gaming client would be updated to contain both an option to order pizza and an advertisement for Mountain Dew. This type of advertising was determined based on community responses through a sequence of survey questions. These small adjustments to the game would allow LOL to generate enough income for Riot Games to expand into other areas of the e-sports industry.
ContributorsSeip, Patrick (Co-author) / Zhao, BoNing (Co-author) / Kashiwagi, Dean (Thesis director) / Kashiwagi, Jacob (Committee member) / Barrett, The Honors College (Contributor) / Sandra Day O'Connor College of Law (Contributor) / Department of Economics (Contributor) / Department of Supply Chain Management (Contributor)
Created2015-05
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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

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
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This report is a summary of a long-term project completed by Ido Gilboa for his Honors Thesis. The purpose of this project is to determine if an arbitrage between different crypto-currency exchanges exists, and if it is possible to acts upon such triangular arbitrage. Bitcoin, the specific crypto-currency this report

This report is a summary of a long-term project completed by Ido Gilboa for his Honors Thesis. The purpose of this project is to determine if an arbitrage between different crypto-currency exchanges exists, and if it is possible to acts upon such triangular arbitrage. Bitcoin, the specific crypto-currency this report focuses on, has become a household name, yet most do not understand its origin and patterns. The report will detail the process of collecting data from different sources, manipulating it in order to run the algorithms, explain the meaning behind the algorithms, results and important statistics found, and conclusion of the project. In addition to that, the report will go into detail discussing financial terms such as triangular arbitrage as well as information system concepts such as sockets and server communication. The project was completed with the assistance of Dr. Sunil Wahal and Dr. Daniel Mazzola, professors in the W.P. Carey School of business. This project has been stretched over along period of time, spanning from early 2013 to fall of 2015.
ContributorsGilboa, Ido (Author) / Wahal, Sunil (Thesis director) / Mazzola, Daniel (Committee member) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
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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

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
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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

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
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This thesis provides an in-depth comparison of the attractiveness of leveraged buyout (LBO) transactions under low versus high interest rates. In particular, our analysis focuses on how London Interbank Offered Rates (LIBOR) affect internal rates of return for hypothetical LBO transactions, assuming financing structure and operational enhancements for the individual

This thesis provides an in-depth comparison of the attractiveness of leveraged buyout (LBO) transactions under low versus high interest rates. In particular, our analysis focuses on how London Interbank Offered Rates (LIBOR) affect internal rates of return for hypothetical LBO transactions, assuming financing structure and operational enhancements for the individual transactions are held constant. Given that LIBOR rates are currently at historically low levels, we model four hypothetical LBO transactions in the specialty retail space using both historically high and currently low LIBOR rates (for a total of eight model outputs). We quantify the extent to which high rates have the potential to decrease LBO value, while low rates may enhance value. Through this thesis, we have obtained a better understanding of LBO transaction modeling, an understanding that will make us more effective as professionals in investment banking. Finally, this thesis can serve as a step-by-step guide to LBOs for undergraduate finance students, particularly for members of the Investment Banking Industry Scholars (IBIS) program at Arizona State University.
ContributorsGormley, Sean (Co-author) / Hert, James (Co-author) / Coles, Jeffrey (Thesis director) / Bhattacharya, Anand (Committee member) / Barrett, The Honors College (Contributor) / Department of Economics (Contributor) / Department of Finance (Contributor) / School of Accountancy (Contributor)
Created2014-05
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This paper takes a look at developing a technological start up revolving around the world of health and fitness. The entire process is documented, starting from the ideation phase, and continuing on to product testing and market research. The research done focuses on identifying a target market for a 24/7

This paper takes a look at developing a technological start up revolving around the world of health and fitness. The entire process is documented, starting from the ideation phase, and continuing on to product testing and market research. The research done focuses on identifying a target market for a 24/7 fitness service that connects clients with personal trainers. It is a good study on the steps needed in creating a business, and serves as a learning tool for how to bring a product to market.
ContributorsHeck, Kyle (Co-author) / Mitchell, Jake (Co-author) / Korczynski, Brian (Co-author) / Peck, Sidnee (Thesis director) / Eaton, John (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Department of Economics (Contributor) / Department of Management (Contributor) / Department of Psychology (Contributor) / Department of Supply Chain Management (Contributor) / School of Accountancy (Contributor) / W. P. Carey School of Business (Contributor)
Created2014-05
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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 hel

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
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

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