The Center for Computational Finance and Economic Systems (CoFES) at Rice University and investment management firm Jain Global launched a new externship program designed to mentor undergraduate and graduate students as they gain practical experience and project opportunities.
Jain Global, headquartered in New York City, is the second-largest hedge fund launch in history upon its debut on 1 July 2024 with $5.3 billion in capital.
The CoFES-Jain Externship Program, led by Rice alumnus Maxwell Lee, portfolio manager at Jain’s commodities division in Houston, TX, involves students working on projects in quantitative finance and risk analytics in power, gas, and cross-commodity trading.
As part of the program, Rice students earn three hours of credit through STAT 492 Statistics Practicum or STAT 540 Practicum in Statistics or Data Science/Internship in Statistical Modeling. Ideal candidates for the externship have taken CoFES courses and are expected to combine academic understanding and research with practical implementation.
The students selected for the inaugural CoFES-Jain externship included Jack Guan, an undergraduate student double majoring in Statistics and Operations Research with a minor in Financial Computation and Modeling; Jackson Thetford, a graduate student in the Professional Master of Engineering Management and Leadership program; and Amanda Xu is a doctoral student in Statistics.
Guan’s externship project focused on applying statistical methods learned in Professor Katherine Ensor’s 421/621 Applied Time Series Analysis course to visualize commodity market patterns and recognize patterns in the foreign exchange space. He continues his work at Jain this summer as part of the company’s Commodities Systematic Team.
“Dr. Ensor’s emphasis on applying statistical methods to real-world data greatly simplified the transition from lectures to applications, and working at Jain has offered valuable insights into the complexity of the quantitative finance industry,” said Guan.
“Working with and communicating with industry experts and attending meetings with sell-side corporations not only boosted my nomenclature and fluency in professional communication but also taught me methods to interpret and perceive market movements, sentiments, and opportunities,” Guan added.
Thetford also worked at the systematic cross-commodity trading desk, where he developed alpha trading signals across the asset class.
“My main role was researching, prototyping, and backtesting strategies. This usually starts by coming up with a thesis for a feature that could be used as a signal and then coding up the strategy and backtesting its performance with historical data,” Thetford said.
“Another project I worked on at Jain was specific to energy traders, where I helped review and refine an energy-demand forecasting model. I worked with one of the senior quants to fine-tune and evaluate the model over different regions to help better inform the energy trade desk. I also translated the model into Python and connected it to data sources so that it could be put into production. This was another great experience and showed me another niche in the commodities world.”
Designed to bridge the gap between coursework in quantitative finance and risk analysis, Thetford said, “The experience showed me how complex statistical models are implemented in the real world, what assumptions are valid, how to balance generalization and overfitting, and how uncertainties play a role in model development. Max’s statistical expertise in finance was an invaluable resource, and it was a privilege to learn from him.”
Thetford said, “Seeing the behind-the-scenes of the fast-paced, high-stakes environment of a hedge fund was great, and even more so with the global political turbulence we saw this semester with tariffs and their effect on the global commodity landscape.”
Xu developed a comprehensive pairs trading strategy, which she said benefited from the theoretical foundations provided by Dr. Michael Jackson in the STAT 486/686 Market Models class that is offered each spring semester.
Xu said, “The course was instrumental in helping me understand the framework for identifying and evaluating trading opportunities based on asset relationships. It also introduced how machine learning techniques could empower trading strategies so that I could improve the precision and adaptability of the trading signals.”
All students agreed that they benefited greatly from Max's mentorship. “His consistent support, insightful feedback, and guidance greatly improved the quality and depth of my project,” said Xu. “The externship has greatly shaped my career vision by reinforcing my passion for quantitative finance, particularly in systematic trading strategies.”
Announcements will be made soon for fall applications to the CoFES-Jain Externship Program. Look to cofes.rice.edu for updates.
