Elon Musk is known for making controversial tweets, which often lead to lawsuits. Our thesis focuses on analyzing the effect that these individual tweets have on stock prices. Our hypothesis focuses on the idea that when Elon Musk makes a controversial tweet, the volatility of Tesla stock will increase, while the price of Tesla stock will on average decrease. The thirteen tweets that we are examining are the tweets that we deemed to be most important, which are measured by the amount of press coverage that they have received. We also evaluated the effect that two different lawsuits that stemmed from Musk’s reckless tweets had on Tesla stock. After evaluating the effect that Elon Musk’s tweets had on the stock volume and price, we will then determine whether or not Elon Musk and other CEO’s alike should be able to tweet in a similar manner. In order to analyze stock movement, volume, and significance we imported statistical data from Yahoo Finance and Nasdaq into Excel. From there, We added charts to model the volatility and the direction of price data. Additionally, we created separate indexes to compare stock moves and test for abnormal returns. From these returns we were able to calculate the alpha and beta for Tesla, its peers and competitors. To analyze Musk’s tweets, we collected close to 7,000 tweets and ordered them chronologically in Excel. With the combination of the stock and tweet data, we were in an excellent spot to analyze the data and come to a conclusion.

Every year, major companies buy Super Bowl advertisements (‘ads’) to fuel growth through the creation of brand awareness among a large, diverse audience. Although measuring the effectiveness of these marketing tactics is difficult, evaluating the abnormal returns (‘alpha’) of company stocks in the five days following the Super Bowl is effective because it provides insight into how actual returns compare to expected returns (calculated using data from the preceding 250 days). Analysis of a comprehensive sample, which includes all Super Bowl ads for public companies between the years 2015 and 2019, accurately demonstrates the relationship between these returns, illustrating the effectiveness of this type of marketing. To account for variation resulting from different inputs in different financial models, it is important to evaluate alpha based on several, reputable models of expected return to best capture the result. In this study, alpha will be analyzed using the Capital Asset Pricing Model (‘CAPM’) and the Fama and French 3 and 5 factor models. Although the ideology that increased marketing improves stock returns through brand awareness suggests a positive alpha, these models all indicate a statistically significant negative alpha for large, public companies who bought Super Bowl ads over the past five years. Therefore, actual returns, on average, are lower than projected returns for the evaluated five-day window following the Super Bowl. In examining alpha and statistical significance according to these financial models, this thesis will explore different market factors that may explain this counterintuitive result, primarily focusing on the investors’ opinions about this type of marketing. Therefore, in researching various discrepancies contributing to the negative alpha result, this study will accurately assess the effectiveness of Super Bowl advertising in terms of stock performance.

Axon Enterprise, Inc. is a publicly traded company founded in Scottsdale, Arizona in 1993. The company went public on June 7th, 2001. The inspiration for this topic is our interest in equity research. We believe that understanding how to fundamentally research a company is not only beneficial for our careers, but for our own personal financial learning. One thing that stood out about Axon was its dominant control of the stun gun market. Axon captures around 90%.. Because of this, we wanted to dive deeper. Surely, this has to be a good investment. What company owns almost all of the market share but isn’t a good investment? In our heads, none. But that wasn’t enough. We wanted to dive deeper and examine the fundamental business mechanisms of the firm to determine for ourselves why this is, and why we believe the company really does have tremendous growth potential. By connecting with Axon executives, developing an investment thesis, and understanding the fundamental business drivers behind Axon, we will develop a thorough understanding of Axon’s financial standing. Our goals; fundamental analysis of Axon, determine a one year price target, convince readers that Axon is a rewarding and appealing investment opportunity.

The intent of this paper is inform and educate people on micro-investing, so they can better understand this new and growing category of investing. Given that micro-investing is a relatively new phenomenon, people naturally have many questions about it. What is micro-investing, and what makes it different from traditional investing? What are the origins of this growing segment of financial technology? What features and characteristics do micro-investing platforms have in common and what differentiates them from each other? Is micro-investing viable and cost effective, and if so, is it right for you? What is the future of micro-investing, and is it here to stay? This paper seeks to answer these questions and additional questions that the reader may have.

The classification of financially at-risk is an expansive term that fits the personal profile of most individuals when it comes to the conditioning of their attitude toward money management, particularly in the planning and investment of that money for the achievement of long-term goals. In the case of this thesis, we focus primarily on those who have made a career in professional athletics and entertainment. The behavioral finance tendencies of these two industry professions are widely regarded as insufficient and often damaging the to the longevity of achieved financial security. This ideology stems primarily from an environment where individuals enjoy rapid wealth accumulation in a highly competitive and constantly transitioning role within their respective crafts. The subjectively common behavioral shortcomings of these world-class athletes and performers and uncertain day-to-day security of the professions which these at-risk individuals possess make for highly unfavorable circumstances when striving to achieve a lifetime of income and a secure retirement. In examining individuals of these classes who have faced grave financial hardship, this thesis will serve as a basis for identifying measures to recondition problematic behavioral tendencies that ultimately cause disengagement from a prudent financial plan. Therefore, this thesis will also serve as a framework to determine what investment strategies will complement the behavioral modifications financial planners strive to instill in these individuals, so that professional athletes, celebrities, and financially at-risk professionals alike may achieve higher probability of creating financial freedom through the engaged execution of a goals-based financial plan.

The United States has experienced a financial crisis every ten years for the past three decades. Investors, financial institutions, and government officials fear these moments because of how negative the experience is and the strain it puts on the nation’s financial markets. Analyzing the financial crises of 1987, 1997 and 2008 shows what is to blame for the chaotic times that happened. In all these instances, human actions set up the occurrences that allowed a crash to take place. Each crash is different in their own respect; however, greed, procrastination and a herd mentality are the biggest reappearing trends in each ten-year cycle. Human nature helped escalate each of these crises as well, making them worse than they might have been.

It is important to know why financial crises happen every ten years since the United States is approaching what could be the next ten-year cycle. However, 2019 could be the year the financial markets escape past trends, but that will not happen without understanding why past crises have taken place. If humans stop creating the occurrences for a crisis, there will be nothing for human nature to escalate and make worse. The more independence and knowledge investors and financial institutions have, the easier it will be to stop the occurrences that create a crisis every ten years. This thesis explores why human actions are really to blame for the financial crises the United States’ markets have experienced, and why human nature is to blame for escalating the crisis experienced. Moving forward, if humans can stop creating the occurrences for a financial crisis, the markets can be changed for the better.

This thesis set out to find whether or not there is a correlation between assets under management (AUM) of institutional investment managers and their sponsorship of Exchange Traded Funds (ETFs). It first examines the history of how and why ETFs entered the marketplace and how they have evolved over time in use by institutional investors. It then explains the features that make ETFs unique, and which are desirable to investors. Institutional investors can benefit from arbitrage opportunities in the creation redemption process used to bring ETFs to market; however, this paper will assert that the marketability of ETF products and their associated brand recognition contributes to the value of the firms who sponsor them. Finally, this paper will show that between 1993 and 2015, firms who have sponsored ETFs have had a greater growth in AUM than firms who have not sponsored ETFs.

This paper explores the universe of non-performing loans and tries to examine the effects that a sharp increase in NPLs would cause. The first part of the paper explores some of the most shared definitions of NPL as well as the accounting treatment under IFRS (International Financial Reporting Standards). In the second part of the paper, literature regarding determinants of NPLs is summarized and categorized into three broad categories: macroeconomic determinants, institutional variables, and bank-specific variables. Eventually, in the last part of the paper, a fictional bank is built and tested against a two and three standard deviation NPL events. The worst loss occurring in the simulated events eroded 26% of the capital (2.55% of the assets) forcing the fictional bank to recapitalize and experience expensive recovery processes.

There is a long standing debate on the various forms of investment in the growing marketplace as to which is best for the individual investor needs. Two similar types of investments are mutual funds and exchange-traded funds (ETF), which are both securities that are made up of a pool funds. They are comparable in concept but have key differences that make this study unique. Mutual funds are much more commonly used and are more prevalent in investment publications. This study addresses the benefits and drawbacks of mutual funds and ETFs and how their structures influence returns over a period of time. The purpose of this study was to take historical data of both mutual funds and ETFs to find their returns and see which, if either, outperformed the other based on several different calculations and performance measures. To improve the validity of this study, we found funds from both the technology and utility sector, for each investment vehicle in order to evaluate different classes of risk. We kept the study consistent and compared technology mutual funds to technology exchange traded funds, and so on with the utility sector. We created four portfolios consisting of around eight to ten high quality funds based on criteria. Results indicated that ETFs outperformed mutual funds in both the utility and technology sectors. In order to adjust for risk, we ran Jensen's measure and found that ETF's still outperformed mutual funds. This is significant because mutual funds are highly regarded in the investment world and often thought of as better than ETFs mainly due to their active management and long term results as they have been around for longer than ETFs. This study proves that investors should be putting more money into ETFs because they yield higher returns over time and cost less in fees, allowing the investor to retain a larger portion of their investment.

In this paper the interest yield curve will be plotted at three points based upon three models that were found appropriate for each rate. Knowledge of the term structure of interest yield curves is helpful in the understanding of bond pricing, investment decisions, and public policy (ANG). This paper will examine the intricacies of the yield curve by developing three individual reference rates \u2014 a 2-year, a 5-year, and a 10-year \u2014 with the use of financial instruments and multivariate linear regression. Based upon the example of Nelson and Siegel (1987), Black Derman, and Toy (1990), Mishkin (1990), Ang and Piazzesi (2002), and Diebol et al. (2005), the models will feature various financial assets as well as macroeconomic variable in order to gain an understanding of which factors have the most significant effect on interest rates.