The course provides an introduction to portfolio management with focus on quantitative investment process and methods. The course balances theoretical foundations with practical applications. Primary topics include asset allocation, portfolio construction including optimization, risk modeling, and risk measurement and management. Instruction will combine lectures, case discussions, and workshops, providing opportunities for students to apply quantitative methods to real world problems in several of the explored areas. The course combines investment ideas with analytics, so prior study in any or all of the following areas will make the course more enjoyable: probability/statistics (e.g., normal distributions, regression analysis), linear algebra (e.g., matrix algebra), and introductory calculus (e.g., derivatives). In addition, workshops will include use of both Microsoft Excel and Python (e.g., Jupyter Notebooks). Basic competency in each is a minimum requirement, and of course, the greater your skills, the better.
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