The Effect of Size and Diversification on a Concentrated Portfolio of Consumer Discretionary Stocks: An Empirical Analysis of Portfolio Returns, 2009-2021
Vincent Patrick Rullo
We develop portfolio weighting models for 3 concentrated portfolios: (1) Top Ten by market value, (2) next Ten by market value, (3) Top Twenty by market value. The principal factor loading is Revenue Per Share Growth. Returns are calculated for 2009-2019, the base period,2009-2020, which includes effect of Covid19, and 2009-2021, which includes the effect of Covid-19 and rising interest rates. We test the hypothesis that Revenue Per Share Growth is a priced-in risk factor i.e., all three portfolios out perform the broad market over the abovementioned time periods. We also determine if the risk premium varies by size (Top Ten vs. Next Ten) and by diversification (Top Ten vs. Top Twenty). Finally, to check on the effects of Covid-19 and rising interest rates we check to see if the cumulative return growth for 2009-2020 and 2009-2021 declined relative to the base period, 2009-2019.
Shannon Elizabeth Hirko, Sean Richard Mcgrail, Sophie E. Petras, Patrick F. Sandler, Daniel Franklin Sauder
Research into opportunities to improved bookstore inventory management. Opportunities to reduce inventory costs and improve availability of text books and improved customer service.
Kevin Padraic Cavanaugh, Jack Philip Chevalier, Patrick A. Downey, Michelle Hwang
In partnership with the University of Dayton’s dining services team, we are developing aninventory tracking solution that will solve the issues within the current reusable containerprogram. During the pilot run of this program, which occurred last year (2020) in MarycrestDining Hall, the university ran into a huge problem with students failing to return the reusablecontainers; causing the university to lose over 70% of their inventory. Our solution will be a fulltracking system, with a central database, in which each container can be tracked from the pointof service to a proper return area. Successful completion and implementation of this system willallow the university to identify which student has a reusable container, where the container wasgiven out, and when/if the container has been properly returned. In doing so, we will not only behelping dining services save money but also helping to reduce waste on our campus and withinour community’s landfills. This system will also serve as a foundation in which dining servicescould utilize for any future advancements, such as being able to offer faculty, staff, and gueststhe ability to participate in the program.There are, however, several challenges that we anticipate facing regarding thedevelopment and success of our solution. Moving forward, the technicalities and logisticallimitations are one of the biggest challenges that we are preparing to overcome. We expect to runinto the most issues when it comes to the strict limits on the PCI environment and the types ofscanners we are able to utilize on the containers. We also have to take into account the potentialburdens that our system would be placing on the student and cashier along with a concernregarding the training and additional equipment expenses.Reviewed and approved by Joan Bauman (Executive Director of Dining Service) on 22 September 2021
Fouad O. Saleh
In this study, using a two step regression model, I develop the functional relationship between (1) U.S. govt. debt and safe interest rates (T20 govt. bond) and safe interest rates and 6 sector etf' price indexes. The regression models are run over the period 2009-2019 with quarterly data. I test two key hypotheses: (1) U.S. government debt growth is inversely related to safe interest rates and (2) safe interest rates are inversely related to sector returns.Using the slope coefficients from the safe rate regressions on S&P 500 sector price indexes, I also develop a 6 sector portfolio weighting model and test the hypothesis that safe rates are a priced in risk factor in the equity market i.e., the 6 sector portfolio weighting model outperforms the broad equity market over the long term period,2009-2019.
Jenna N. Patino, William Shattuck, Joncarlo Soto, Brendan J. Steffen
The overall objective of this project is to document, collect, and analyze data of a teacher’s progress toward set goals from their coaches. A subset of that goal is to develop a technology integration plan that combines instructional and technology goals. When talking about how Vartek would like to go forward to complete these goals, we thought of challenges that might come to surface. Misty said that Vartek’s preference to complete this project is to not have a budget, however she is open to a possible budget if money is needed to supply the best solution. Another challenge will be migrating all of the data into one platform because 4 teams of coaches are tracking the teachers in different forms. Coaches have set subjective goals for their teachers which are customized to fulfill the teacher’s needs and this creates an issue because there is no standardization across a big data set. Finally, Misty said that they are open to having a cloud data server to hold all of their information and tracking but has concerns over information security and who will be able to access the notes.