QMI members investigate systematic methods of alpha generation and synthesize their findings in whitepapers at the end of each academic year. Findings are illustrative in nature and should not inform implementation without full evaluation of methodology and strategy risks. Those interested in discussing specific whitepapers should reach out to the team in question directly.

Current Whitepapers

Stay tuned for our Spring 2020 Papers.

Past Whitepapers

Multi Dimensional Quality Among the S&P 500

Posted April 25, 2019
By Catherine Cheng, Wesley Klock, Matt Hopp, Eric Sun

Traditional factor-based asset pricing models, like the Fama-French three-factor model, use metrics such as firm size and book-to-market ratio to explain deviations from beta-predicted returns (Fama and French, 1992). We propose an enhancement of these models by implementing a trading threshold based on a quality factor that accounts for a company’s relative measures of profitability, stability, and growth within its sector. This idea runs under the underlying fundamental economic hypothesis that securities should be priced according to their potential to generate growing, stable future cash flows.

To leverage this insight for an automated trading model, two key elements are developed. First, an automated, wide-ranging, and holistic quantification of quality is built to allow the model to effectively capture the future earnings potential of a large number of firms based on their current financial profiles. Second, a rolling block-list is implemented to avoid making repetitive mistakes trading on stocks that are not valued by the market based on fundamentals. This tool acts as a “circuit breaker” that recognizes when the economic hypothesis is invalid for a particular security so that the fund can avoid trading it. Together these two innovations allow the model to systematically identify and exploit opportunities to invest in securities that are trading at a discount relative to their future earnings potential.