Yale School of Management

Yale SOM Curriculum: Quantitative Investing - Turning Data Into Investing Insights

The Yale School of Management’s Quantitative Investing course introduces students to systematic, data‑driven portfolio construction. It defines quantitative or systematic investing as the process of converting financial characteristics—such as earnings‑to‑price ratios, momentum quintiles, or other accounting metrics—into repeatable trading rules, akin to a “Moneyball” approach that prioritizes numbers over brand names. The curriculum balances rigorous theory with empirical analysis. Lectures cover the statistical foundations for estimating return drivers, while case studies showcase real‑world research findings. Students then apply these concepts in lab sessions, writing code to rank securities, build factor‑based portfolios, and back‑test strategies against historical data. Instructors emphasize practical skill‑building, noting that the class culminates in a hands‑on project where participants generate their own systematic strategy. A notable example discussed is ranking stocks into quintiles based on momentum, buying the top quintile and shorting the bottom, illustrating how simple signals can be operationalized. By equipping future finance professionals with both analytical frameworks and coding proficiency, the course prepares them to design, evaluate, and implement quantitative strategies in a rapidly data‑centric investment landscape.