Yuhan Liu
About Yuhan Liu
Yuhan Liu is a Risk Operation Associate, Market Risk at Jefferies, with a background in market risk analysis and quantitative research.
Current Role at Jefferies
Yuhan Liu is currently employed as a Risk Operation Associate, Market Risk at Jefferies, based in Jersey City, New Jersey, United States. He has been with the firm since 2020. In this role, he focuses on analyzing and managing market risks, and contributing to the enhancement of risk-reporting practices. Notably, Liu initiated a project to transition the Country Risk reporting process from quarterly to daily, utilizing tools such as Python, Bloomberg, and SQL.
Previous Experience at RBC Capital Markets
Prior to his current role, Yuhan Liu worked at RBC Capital Markets as a Market Risk Analyst in the Global Equity Derivatives division. His tenure at RBC extended from 2019 to 2020, lasting for 9 months. During his time there, Liu was responsible for preparing risk presentations aimed at regulators and senior management, covering periodical changes in risk factors, exposures, and stress loss.
Research Assistant at Fordham University
From 2018 to 2019, Yuhan Liu served as a Research Assistant at Fordham University. His research focused on 'The TIPS Yield Curve and Inflation Compensation.' This academic experience allowed Liu to delve into complex financial concepts and contribute to scholarly work in the domain of quantitative finance.
Educational Background
Yuhan Liu earned a Master's of Science in Quantitative Finance from Fordham Gabelli School of Business, completing his studies from 2017 to 2019. Prior to that, he attained a Bachelor's degree in Computer Science and Mathematics from the University of Wisconsin-Madison, where he studied from 2013 to 2017. This blend of education in quantitative finance and computer science equips Liu with a solid foundation in both financial analysis and computational techniques.
Analytical Projects and Initiatives
Among Yuhan Liu's notable projects is the enhancement of the Country Risk reporting process at Jefferies, where he transitioned the reporting frequency from quarterly to daily using Python, Bloomberg, and SQL. Additionally, he has experience mapping daily Value-at-Risk (VaR) and Profit and Loss (PnL) distributions at the division level and interpreting changes under various stress scenarios.