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Private Equity Reputation: Arbitrage Spreads and Offer Premiums of Public to Private Transactions

Description

This paper classifies private equity groups (PEGs) seeking to engage in public to private transactions (PTPs) and determines (primarily through an examination of the implied merger arbitrage spread), whether certain reputational factors associated with the private equity industry affect a

This paper classifies private equity groups (PEGs) seeking to engage in public to private transactions (PTPs) and determines (primarily through an examination of the implied merger arbitrage spread), whether certain reputational factors associated with the private equity industry affect a firm's ability to acquire a publicly-traded company. We use a sample of 1,027 US-based take private transactions announced between January 5, 2009 and August 2, 2018, where 333 transactions consist of private-equity led take-privates, to investigate how merger arbitrage spreads, offer premiums, and deal closure are impacted based on PEG- and PTP-specific input variables. We find that the merger arbitrage spread of PEG-backed deals are 2-3% wider than strategic deals, hostile deals have a greater merger arbitrage spread, larger bid premiums widen spreads and markets accurately identify deals that will close through a narrower spread. PEG deals offer lower premiums, as well as friendly deals and larger deals. Offer premiums are 8.2% larger among deals that eventually consummate. In a logistic regression, we identified that PEG deals are less likely to close than strategic deals, however friendly deals are much more likely to close and Mega Funds are more likely to consummate deals among their PEG peers. These findings support previous research on PTP deals. The insignificance of PEG-classified variables on arbitrage spreads and premiums suggest that investors do not differentiate PEG-backed deals by PEG due to most PEGs equal ability to raise competitive financing. However, Mega Funds are more likely to close deals, and thus, we identify that merger arbitrage spreads should be narrower among this PEG classification.

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2019-05

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Iot Manufacturing

Description

As the IoT (Internet of Things) market continues to grow, Company X needs to find a way to penetrate the market and establish larger market share. The problem with Company X's current strategy and cost structure lies in the fact

As the IoT (Internet of Things) market continues to grow, Company X needs to find a way to penetrate the market and establish larger market share. The problem with Company X's current strategy and cost structure lies in the fact that the fastest growing portion of the IoT market is microcontrollers (MCUs). As Company X currently holds its focus in manufacturing microprocessors (MPUs), the current manufacturing strategy is not optimal for entering competitively into the MCU space. Within the MCU space, the companies that are competing the best do not utilize such high level manufacturing processes because these low cost products do not demand them. Given that the MCU market is largely untested by Company X and its products would need to be manufactured at increasingly lower costs, it runs the risk of over producing and holding obsolete inventory that is either scrapped or sold at or below cost. In order to eliminate that risk, we will explore alternative manufacturing strategies for Company X's MCU products specifically, which will allow for a more optimal cost structure and ultimately a more profitable Internet of Things Group (IoTG). The IoT MCU ecosystem does not require the high powered technology Company X is currently manufacturing and therefore, Company X loses large margins due to its unnecessary leading technology. Since cash is king, pursuing a fully external model for MCU design and manufacturing processes will generate the highest NPV for Company X. It also will increase Company X's market share, which is extremely important given that every tech company in the world is trying to get its hands into the IoT market. It is possible that in ten to thirty years down the road, Company X can manufacture enough units to keep its products in-house, but this is not feasible in the foreseeable future. For now, Company X should focus on the cost market of MCUs by driving its prices down while maintaining low costs due to the variables of COGS and R&D given in our fully external strategy.

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Date Created
2016-05

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The Valuation Effects of a Drug Recall

Description

The pharmaceutical industry is heavily regulated. This regulation results in a high number of recalls in this industry compared to other industries. The pharmaceutical industry is subject to high regulation because of the harmful effects pharmaceuticals can have on consumers.

The pharmaceutical industry is heavily regulated. This regulation results in a high number of recalls in this industry compared to other industries. The pharmaceutical industry is subject to high regulation because of the harmful effects pharmaceuticals can have on consumers. In this paper I examine the valuation effects that a drug recall has on both the recalling firm and the recalling firm's rivals. I perform an event study analysis on the data. I show that there exists a statistically significant negative effect for a drug recall on the recalling firm's market value immediately surrounding the announcement. Additionally, there is a statistically significant positive effect for a drug recall on the recalling firm's rivals after the announcement.

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Date Created
2015-12

A Fortune 100 Technology Company Collaborative Thesis: Third-Party Services \u2014 Optimizing Headcount

Description

The object of the present study is to examine methods in which the company can optimize their costs on third-party suppliers whom oversee other third-party trade labor. The third parties in scope of this study are suspected to overstaff their

The object of the present study is to examine methods in which the company can optimize their costs on third-party suppliers whom oversee other third-party trade labor. The third parties in scope of this study are suspected to overstaff their workforce, thus overcharging the company. We will introduce a complex spreadsheet model that will propose a proper project staffing level based on key qualitative variables and statistics. Using the model outputs, the Thesis team proposes a headcount solution for the company and problem areas to focus on, going forward. All sources of information come from company proprietary and confidential documents.

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Date Created
2014-05

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Prioritizing Projects on Time and Cost Savings for a more Efficient Manufacturing Process of a Semiconductor Company

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,

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.

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Created

Date Created
2015-05

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Company A Data Center Group (DCG) Server Segment Analysis

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

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.

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Created

Date Created
2016-05

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Local Freight Optimization

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

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.

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Agent

Created

Date Created
2015-05

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Foundry Opportunities

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.

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.

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Created

Date Created
2015-05

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Company X Collaborative Thesis: Real Estate

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

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.

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Agent

Created

Date Created
2021-05

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Company X Collaborative Thesis: Real Estate

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

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.

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Agent

Created

Date Created
2021-05