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Quantitative Portfolio Management and Algorithmic Trading

Program(s): Undergraduate Courses

*Taught Online*  This course teaches quantitative finance and algorithmic trading with an approach that emphasizes computation and application. The first 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. The second half of the course builds on this by covering case studies in quantitative investment that illustrate key issues in allocation, attribution, and risk management. Students will have the chance to learn classic models as well as more modern, computational approaches, all illustrated with application.

Remote or Residential

✓ Remote Course

 

Course Considerations

Statistics, math, finance and Python programming will be featured. Familiarity in some of these areas is helpful, but there are not strict pre-reqs. Some experience in regression and programming is highly recommended. But the course is accessible to motivated students still new to some of these areas.

 

Course Overview

Start Date

June 10

End Date

August 09

Current Grade / Education Level

Undergrad / Grad

Program

Undergraduate Courses

Class Details

Course Code

FINM 25000 91

Class Day(s)

Mon

Class Duration (CST)

18:00

9:00 P.M.

Session

Session I

Course Length

9 weeks

Primary Instructor

Mark Hendricks

Secondary Instructor

Sebastien Donadio

Academic Interest

Math and Computer Science
Social Sciences (e.g., history, sociology)