Introduction to the Quantitative Investment Process

Quantitative approaches to investing have taken center stage in asset management business in recent years. Quantitative candidates for positions in investment research, alpha generation, quantitative development, data engineering, portfolio construction, algorithmic trading, performance measurement, risk management, manager selection, product development and distribution, are increasingly in demand from both quantitative and discretionary investment managers, as well as sell-side service providers. In addition to computer engineering and data fluency, the best candidates are increasingly expected to have a strong understanding of the investment process, with a grounding in sound idea generation and testing, data management, modeling, implementation, and measurement practices. This course is intended to provide a foundation in the quantitative domains of investing for students seeking employment in asset management and related fields. It will position students to meet the demands of employers that are becoming more analytical, data driven, and process-driven. The material in highly integrative, drawing on theory and practice in financial economics, statistics, data science, and optimization. Since each topic in the course is complex, with a large academic and practitioner literature behind it, the course will only scratch the surface in some areas. However, students will be introduced to the richness of each topic and pointed in the right direction for deeper study in areas of interest. Analysis of several real-world dataset investment problems will be woven into and built upon throughout the course. The principles covered in this course can be applied in any quantitative investment context, but the datasets and application studied will be long-short investing and statistical arbitrage in U.S. equity markets. The course material will be organized into six three-hour lectures with one industry speaker. There will be three problem sets involving data analysis and analytical problems, to be completed in groups, and a final individual exam.