Presenter(s)
Will Luis Perez
Files
Download Project (588 KB)
Description
Based on Rob Arnott’s foundational work on using stock fundamentals to weigh portfolios of stocks, I developed a smart beta portfolio weighting model for the top 20 stocks by market value in the SPDR Industrial Sector. The model uses a portfolio weighting factor based on the coefficient of variation (COV). In essence, a stock gets a higher weight if the 1/COV (the return-risk ratio) is higher compared to other stocks. A three year moving average of earnings per share is used to calculate the return/risk ratio for each stock. The return-risk ratios are updated yearly with actual portfolio returns generated for the years 2009-2017. The performance benchmark is the S&P 500 ETF (SPY).
Publication Date
4-18-2018
Project Designation
Independent Research
Primary Advisor
Tony S. Caporale, Robert D. Dean
Primary Advisor's Department
Economics and Finance
Keywords
Stander Symposium project
Recommended Citation
"A Smart Beta Portfolio Model for the SPDR Industrial Sector: An Empirical Analysis, 2009-2017" (2018). Stander Symposium Projects. 1177.
https://ecommons.udayton.edu/stander_posters/1177