Fantasy football is a game derived from America’s National Football League and involves players managing “teams” of fantasy football players. Given that the game contains elements of value, risk, and reward, this project aims to draw parallels between fantasy football and Modern Portfolio Theory, a well-regarded theory describing portfolio construction and performance in financial markets. This hypothesis is tested through a simulation of the 2019 – 2020 fantasy football season using this strategy; a sample team is generated, the team is adjusted as per the rules outlined in the risk-reducing and value-preserving strategy, and the results are tabulated per the team’s fantasy football scoring output. The results show that a volatility-reducing strategy fails to achieve a consistent, good performance from the fantasy team portfolio, but can result in a relatively successful season. Key issues to consider in this outcome are the low volume of data, the high volatility and situational nature of the underlying statistics from which fantasy scoring is derived, and the inefficiency of financial markets. The value of this research demonstrates that strict algorithmic, numerical, or technical methods are insufficient to succeed in fantasy football, and that information availability, access, and speed, along with a significant allotment of luck, are needed to succeed. The implication for the financial field is that the rules and theories formulated for it are based on certain crucial assumptions such as a centralized supply and demand for securities, an objective theory of value, and efficiency of markets, which cannot be translated directly to fantasy football.

This thesis will be exploring the situation of one of the most vulnerable groups during the COVID-19 pandemic, low-income renters. As businesses and whole states were shutdown, jobs and wages were lost and the over 100 million renters in the United States, many of whom spend a significant chunk of their income on their rent, were forced into a precarious situation. <br/><br/>The Federal Rent Moratorium that is currently in effect bars any evictions for missed rent payments, but these are expenses that if left unpaid, are just continuously accruing. These large sums of rent payments are currently scheduled to be dropped on struggling individuals at the end of the recently extended date of June 30th, 2021. As these renters are unable to pay for their housing, landlords lose the revenue streams from their investment properties, and are in turn unable to cover the debt service on the financing they utilized to acquire the property. In turn, financial institutions can then face widespread defaults on these loans.<br/><br/>The rental property market is massive, as roughly 34% of the American population consist of renters. If left unaddressed, this situation has the potential to cause cataclysmal consequences on the economy, including mass homelessness and foreclosures of rental properties and complexes. Everyone, from the tenants to the bankers and beyond, are stakeholders in this dire situation and this paper will seek to explore the issues, desires, and potential solutions applicable to all parties involved. Beginning with the pre-pandemic outlook of the rental housing market, then examining the impact of the coronavirus and the resulting federal actions, to finally explore solutions that may prevent or mitigate this potential disaster.

This thesis explores the benefits of tax loss harvesting by examining the time period from 1999-2000 to determine the potential profits investors could realize from utilizing this strategy. The first step to accomplishing this was to collect data from the past 20-plus years from the SPDR S&P 500 Exchange Traded Fund (SPY) and its 11 sectors: Energy (XLE), Consumer Staples (XLP), Consumer Discretionary (XLY), Communication Services (XLC), Real Estate (XLRE), Technology (XLK), Utilities (XLU), Materials (XLB), Industrials (XLI), Financials (XLF), and Health Care (XLV). The next step was to clean the data from hundreds of months of opening prices, closing prices, and quarterly dividends into an annual opening price and total annual dividends to calculate a rate of return. Finally, I found the weightings of the S&P 500 and its sectors on January 1st of every year and input this data into a model whose output reflected the growth of a portfolio with and without the use of tax loss harvesting. Once this model was created, I determined the benefits of tax loss harvesting in the present and the value of carrying these losses forward. The outcomes of this thesis solely reflect the benefits of using tax loss harvesting through a passive investment strategy. This research will enrich academic and professional understandings of tax loss harvesting through its clear demonstration of how much tax loss carryforward can be accessed, as well as the opportunity for gains from compounding interest on previous tax savings due to tax loss harvesting.

The growth of fintech companies in developing countries has led to increased levels of economic development and financial inclusion. This thesis explores the reasons for the success of these companies, with a focus on the impact they have on the local economy and their ability to provide financial services to underserved populations. The intent of this thesis is to educate the reader on the overall landscape of financial technology companies in developing countries. The writing will examine the specific types of services offered by these fintech companies that operate in developing countries and the catalysts that make them successful. It will also cover the impact that these companies have on the nations they operate in by looking at contributions to overall economic development and financial inclusion. The results of this literature will have implications for business leaders, policymakers, and investors interested in promoting financial inclusion and economic development through fintech.