Jifan He

Advancing in financial engineering at New York University, my journey in the quantitative realm began at the University of California, Irvine. I majored in quantitative economics, augmented with minors in statistics and mathematics. My academic pursuits ignited a passion during an independent study where I delved deep into the pandemic's impact on a specific industry. This endeavor sharpened my interest, molding my path toward more complex and impactful quantitative research.

Jifan He is currently pursuing her master's degree in financial engineering at New York University, a journey inspired by a profound interest in quantitative research. Before this, She obtained her bachelor’s degree in quantitative economics, minoring in statistics and mathematics at the University of California, Irvine. Her passion for quantitative research was kindled during an independent study, where she analyzed the pandemic’s impact on a specific industry. Her intrigue further intensified during a collaborative project, wherein she and her group harnessed Machine Learning (ML) to devise innovative investment strategies. She was eager to delve deeper into this project during subsequent discussions. After these academic endeavors, she embraced the invaluable opportunity to intern with Numeraxial LLC in the summer of 2023. This hands-on experience reinforced her commitment to employing risk, valuation, statistical, and ML analyses as tools for academic exploration and as instrumental drivers of actionable insights and profitable strategies in the real world.

NYU's Financial Engineering program offers a variety of courses in different areas, helping Jifan He hone her skills in quantitative analysis, machine learning, and pricing models. Her team's paper "Applications of Copulas and Machine Learning Algorithms on Pairs Trading" was accepted by the 2022 International Conference on Economics, Mathematical Finance and Risk Management (EMFRM 2022). She later embraced the invaluable opportunity to intern with Numeraxial LLC in the summer of 2023. This hands-on experience reinforced her commitment to employing risk, valuation, statistical, and ML analyses as tools for academic exploration and as instrumental drivers of actionable insights and profitable strategies in the real world.