Quantitative Portfolio Management and Algorithmic Trading
Course Code
FINM 25000 10
Course Description
This course teaches quantitative finance and algorithmic trading with an approach that emphasizes computation and application. The first half of the course covers key tools for “quants” via case studies in quantitative investment that illustrate allocation, attribution, pricing, and risk management. You will have a chance to learn classic models as well as more modern, computational approaches, all illustrated with application. The second half of the course focuses on designing, coding, and testing automated trading strategies in Python, with particular consideration to market models, infrastructure, and order execution.
Statistics, math, finance and Python programming will be featured. Familiarity in some of these areas is helpful, but there are not strict prerequisites. Some experience in regression and programming is highly recommended, but the course is accessible to motivated students still new to some of these areas.
One additional class will be held on July 6 to make up for the observance of Independence Day on July 5.
Instructor(s)
Mark Hendricks, Sebastian Donadio
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Residential