Junting (Amy) Yan graduated from the University of International Business and Economics (UIBE) in 2025 with a Bachelor's degree in Statistics, providing her with rigorous mathematical training. During her exchange semester at UC Berkeley, she excelled in multiple graduate and PhD-level courses. In particular, in the Intro to AI course, she ranked in the top 5% among a class of declared Computer Science majors. Beyond her academic training, Amy has actively applied theoretical knowledge to practical challenges. As a freshman, she became the first in her cohort to participate in a modeling competition, leading her three-person team to the top 1% out of 5000+ teams.
Amy has completed three quantitative research internships in diverse settings, including mutual funds, proprietary trading, and hedge funds. In these roles, she worked on stock alpha research using order-book data, feature selection, factor models, and intraday momentum strategies. In her most recent internship at F-lab, she applied machine learning techniques to build a cross-sectional ETF model for the U.S. market. After thorough backtesting, the model was deployed into live production, generating notable returns.
Amy joined the MSCF program to enhance her quantitative skills and deepen her understanding of their application in finance. Upon graduation, she aims to pursue a career in quantitative trading or research, leveraging her statistical expertise and machine learning experience to innovate in financial strategies.
