Undergraduate and graduate students from across the Rice University campus are finding that what they learn in Quantitative Financial Risk Management (STAT 449/649) and Quantitative Financial Analytics (482/682) is amplified through trading simulation platforms.
Quantitative Finance (STAT 499/699) is a unique one-credit course offered for repeatable credit every semester. Its curriculum and guest lectures from industry experts are designed to connect techniques in mathematics and modern statistical analysis with learning to trade futures and options through trading simulation platforms.
“This year, we had the strongest class performances to date. Two students doubled their portfolio size, and 64 percent of the class had positive returns, averaging approximately 42 percent. The average return for the entire class was 14.8 percent, which both beat the market over the same time period,” said course instructor Michael Jackson, who is also head of data science and machine learning for New Territory Advisors, LLC, a multi-strategy hedge fund in Houston, TX.
During the fall semester, Jackson also co-teaches Quantitative Financial Risk Management with Max Lee, a portfolio manager at Jain Global and adjunct professor of the practice at Rice.
Katherine Ensor, the Noah G. Harding Professor of Statistics, is co-instructor of another fall course, Quantitative Financial Risk Management, with Wentao Zhao, a global quantitative analytics manager at ExxonMobil Global Trading and adjunct professor of the practice of statistics at Rice. Statistics doctoral student Arnold Muchatibaya was also a lecturer in the course.
Many graduate students enrolled in Quantitative Finance are students in the Financial Statistics and the Statistics of Risk concentration of the Professional Mater Degree Program (MStat) managed by Jackson. Undergraduate students who enroll are earning degrees in economics and mathematical economic analysis, statistics, computational and applied mathematics, business, computer science, or other disciplines in engineering. Several undergraduate students are also minoring in Financial Computation and Modeling (FCAM).
Jackson says, “After taking STAT 499/699, a growing number of students are taking advantage of university trading challenges to continue to put their skills to the test.”
This fall, Rice had the largest number of teams with a competitive finish in the 2024 CME Trading Challenge. The four-week competition had 2,300 students who formed nearly 570 teams from 24 countries representing 180 universities.
At the start of the competition, teams of up to five students are given a $500,000 balance to trade in agriculture, energy, metals equity indices, interest rates, and foreign exchange contracts using CQG’s real-time electronic trading platform. Throughout the challenge, students receive live market updates through Dow Jones newsfeeds and The Hightower Report.
Rice University undergraduate team The Price of Rice placed 63 with a trading end balance of $583,543. Team members included Ryker Dolese, Lucas He, Austin Tran, Krish Kumar, and Greyson Elyalderani.
“Overall, the CME Challenge was a fun experience, and we were happy to end in the green. We would definitely do it again,” said Dolese, the team captain of The Price of Rice.
“Most of our group has taken CoFES and statistics courses. We found our coursework, especially STAT 499, to be helpful since we had already worked with futures and options trading,” said Dolese, a sophomore majoring in statistics with a minor in FCAM.
A total of five undergraduate teams and two graduate teams participated in the CME University Trading Challenge. During the competition, teams are required to execute at least 10 contracts per day in one competition product or a combination of the competition products.
“Trading can be extremely frustrating and requires dedication and planning. I encourage students to dedicate a set number of hours each week to study their trades – determine what worked and evaluate what didn’t,” said Jackson.
In the spring semester, Jackson will organize a trading challenge for the Quantitative Finance class. As in past years, students enrolled in Market Models (STAT 486/686) can also experience the excitement, energy, and decision-making environment of simulated trading.
Students in CoFES courses also benefit from guest lectures on the management of risk, the evolution of machine learning, artificial intelligence, and artificial neural network applications.
Since its founding in 2002, CoFES has been dedicated to the advancement of quantitative finance and economic systems and their ultimate impact on society. Using and developing modern computational, statistical and mathematical techniques for modeling complex problems, we strive to deliver world-class research, expand education and advance public knowledge.
- Shawn Hutchins, Communications and Marketing Specialist
