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Data Science in Quantitative Finance and Risk Management

Program(s): Summer Online

*Taught Online* Have you started or are about to start your investment journey? Do you want to know more about terms like “recession” and “volatility,” and how they might affect your own bank account? Are you interested in mathematics and its application to human emotions? This course introduces the leading statistical models and methods which quantitative  researchers use to understand the ever-evolving markets and build insightful financial strategies, such as machine learning, risk profiling, and portfolio optimization . At first, students will learn about the theoretical and applied foundations of regression and classification designs for predicting market patterns. Next, students will gain exposure to proprietary metrics such as Expected Shortfall used to evaluate  drawdowns of both single and multi-asset portfolios. Lastly, they will experiment with portfolio allocation tactics by visualizing risk-to-reward graphs under various buying and selling conditions. These techniques can be applied to the U.S. and foreign asset classes, including equities, commodities, and cryptocurrencies. Students will form research teams and play a stock market game using the skills they learned throughout the course with the objective of experiencing  how professional Quants pitch asset strategies to their clients. All implementations will be done using Python.

See sample syllabus here.

Remote or Residential

✓ Remote Course

 

Course Considerations

Experience with Python coding experience is required. Prior knowledge on statistics and probabilities is helpful but not required. Prior knowledge in calculus or pre-calc (e.g., integrals, derivatives) is helpful but not required.

Coding Intensive
Math Intensive

Course Overview

Start Date

July 10

End Date

August 09

Current Grade / Education Level

9th Grade
10th Grade
11th Grade

Program

Summer Online

Class Details

Course Code

STAT 13820 96

Class Day(s)

Mon Tues Wed Thurs Fri

Class Duration (CST)

18:00

8:00 P.M.

Session

Session II

Course Length

5 weeks

Primary Instructor

John Lee

Academic Interest

Social Sciences (e.g., history, sociology)