Following the Global Financial Crisis of 2007-2008, financial institutions faced regulatory changes due to inherent weaknesses that were exposed by the recession. Within the United States, regulation came via the passing of the Dodd-Frank Wall Street Reform and Consumer Protection Act in 2010, which was heavily influenced by the internationally focused Basel III accord. A key component to both of these sets of regulations focused on raising the capital requirements for financial institutions, as well as creating capital buffers to help protect solvency during economic downturns in the future. The goal of this study is to evaluate the effectiveness of these changes to capital requirements, and to hypothesize as to what would happen if the modern banking system experienced the COVID-19 pandemic recession with the capital and leverage levels of the banking institutions circa 2007. To accomplish this, data from the Federal Reserve describing the capital and leverage ratios of the banking industry will be evaluated during both the Global Financial Crisis of 2007-2008, as well as during the COVID-19 Recession. Specifically, we will look at by how much capital was improved due to Dodd-Frank/Basel III, the resiliency of the capital and leverage ratios during the modern COVID-19 recession, and we will look at the average drop in capital levels caused by the COVID-19 recession and apply these percentage changes to the leverage/capital levels seen in 2007. Given the results, it is clear to see that the change in capital requirements along with the counter-cyclical buffers described in Dodd-Frank and Basel III allowed the banking system to function throughout the COVID recession without approaching insolvency in the slightest, something that ailed many large banks and firms during the Global Financial Crisis. As an answer to our hypothetical, we found that the drop seen affecting the measures of bank capital experienced during the COVID pandemic when applied to values seen at the beginning of the 2007 recession still led to a well-capitalized banking industry as a whole, highlighting the resiliency seen during the COVID recession thanks to the capital buffers put in place, as well as the direct assistance provided by the federal government (via PPP loans and stimulus checks) and the Federal Reserve in keeping the hit on capital to minimal values throughout the pandemic.

The field of behavioral economics explores the ways in which individuals make choices under uncertainty, in part, by examining the role that risk attitudes play in a person’s efforts to maximize their own utility. This thesis aims to contribute to the body of economic literature regarding risk attitudes by first evaluating the traditional economic method for discerning risk coefficients by examining whether students provide reasonable answers to lottery questions. Second, the answers of reasonable respondents are subject to our economic model using the CRRA utility function in which Python code is used to make predictions of the risk coefficients of respondents via a two-step regression procedure. Lastly, the degree to which the economic model provides a good fit for the lottery answers given by reasonable respondents is discerned. The most notable findings of the study are as follows. College students had extreme difficulty in understanding lottery questions of this sort, with Medical and Life Science majors struggling significantly more than both Business and Engineering majors. Additionally, gender was correlated with estimated risk coefficients, with females being more risk-loving relative to males. Lastly, in regards to the model’s goodness of fit when evaluating potential losses, the expected utility model involving choice under uncertainty was consistent with the behavior of progressives and moderates but inconsistent with the behavior of conservatives.

The Covid-19 pandemic has made a significant impact on both the stock market and the<br/>global economy. The resulting volatility in stock prices has provided an opportunity to examine<br/>the Efficient Market Hypothesis. This study aims to gain insights into the efficiency of markets<br/>based on stock price performance in the Covid era. Specifically, it investigates the market’s<br/>ability to anticipate significant events during the Covid-19 timeline beginning November 1, 2019<br/><br/>and ending March 31, 2021. To examine the efficiency of markets, our team created a Stay-at-<br/>Home Portfolio, experiencing economic tailwinds from the Covid lockdowns, and a Pandemic<br/><br/>Loser Portfolio, experiencing economic headwinds from the Covid lockdowns. Cumulative<br/>returns of each portfolio are benchmarked to the cumulative returns of the S&P 500. The results<br/>showed that the Efficient Market Hypothesis is likely to be valid, although a definitive<br/>conclusion cannot be made based on the scope of the analysis. There are recommendations for<br/>further research surrounding key events that may be able to draw a more direct conclusion.

Covid-19 is unlike any coronavirus we have seen before, characterized mostly by the ease with which it spreads. This analysis utilizes an SEIR model built to accommodate various populations to understand how different testing and infection rates may affect hospitalization and death. This analysis finds that infection rates have a significant impact on Covid-19 impact regardless of the population whereas the impact that testing rates have in this simulation is not as pronounced. Thus, policy-makers should focus on decreasing infection rates through targeted lockdowns and vaccine rollout to contain the virus, and decrease its spread.