DDA3600 Factor Investing

• This course offers a thorough exploration of factor investing, blending econometrics and machine learning. Key topics include foundational concepts of factor investing, portfolio sorting, cross-sectional and time-series regression methods, and multiple hypothesis testing. The course also covers advanced machine learning models, integrating alternative data sources, and addressing practical challenges such as factor timing and allocation. Drawing on the instructor’s extensive experience in the quantitative hedge fund industry, the course emphasizes real-world practice and application. By course end, students will be prepared to conduct empirical research, develop and backtest factor-based strategies, and apply factor investing principles in professional settings.
• Instructor (Fall 2024)

2.853/4 Intro to Manufacturing Systems, MIT

• This course provides ways to analyze manufacturing systems in terms of material flow and storage, information flow, capacities, and times and durations of events. Fundamental topics include probability, inventory and queuing models, optimization, and linear and dynamic systems. Factory planning and scheduling topics include flow planning, bottleneck characterization, buffer and batch-size analysis, and dynamic behavior of production systems.
• Teaching Assistant (Fall 2007, 2009, 2010, and 2011)