Course: STAT 13820
Title: Data Science in Quantitative Finance and Risk Management
Instructor(s): Yin Kwong Lee
Class Schedule: Sec 1: MTWRF 6:00 PM-8:00 PM (Remote)
Textbook(s): TBA
Description: 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 financial data researchers use to understand ever-evolving markets and build insightful financial strategies, such as machine learning, risk calculation, and portfolio management . 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 Value-at-Risk(VaR) used to evaluate returns/losses 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 experience how professionals in quantitative trading, hedge funds, and risk analytics collaborate to pitch asset strategies to their clients, and form research teams to play a stock market game using the skills they learned throughout the course with the objective of maximizing the teams' portfolio returns. All implementations will be done using Python.