Can Liu
Manager Quant Risk Research and Analysis at CME Group
- Role
- Manager Quantitative Risk Management at CME Group
- Location
- New York, NY, US
- LinkedIn followers
- 500 followers
About Can Liu
Dedicated to pushing the boundaries of quantitative finance and risk management, I have spent the last several years honing my skills in the quant finance industry. Currently serving as a Senior Quantitative Researcher at CME Group, I collaborate with a team of talented individuals in the research and development of cutting-edge models for Commodity and Equity derivatives. My expertise spans the complete model lifecycle, from research and development to production launch and maintenance. Notable achievements include spearheading the creation of SPAN2, a sophisticated Portfolio Margin model that is stable, scalable, and brings significant capital efficiency to our clients, as well as improving pricing and volatility calibration for different types of derivatives. With a Master\'s degree in Financial Mathematics from the University of Chicago, a solid foundation in Mathematics and Economics from the University of Illinois, and various internship experiences in trading strategy research, I thrive on solving complex quantitative challenges and driving innovation in the financial industry.
Experience
Manager Quantitative Risk Management
Apr 2018 — Present · New York, NY, US
Full-cycle experience spanning model research, development, backtesting, regulatory approval, productionization, and ongoing performance governance- Principal contributor to SPAN2, CME’s next-generation portfolio margin model-driving historical VaR/stress risk framework, liquidity/concentration risk assessment, and cross-asset integration- Managing SPAN2 new product launching by driving cross-functional efforts, evaluating risk factors, identifying Pricing methods and Data Simulation for new products with limited history- Applied machine learning (K-means, PCA) and time-series/statistical modeling to measure portfolio risk and support model calibration- Automated model monitoring and backtesting workflows, improving transparency and early-warning capabilities across market regimes- Defined business requirements for Brooklyn, an internal parallel-computing research and risk analytics platform used firmwide
Education
University of Illinois Urbana-Champaign
Bachelor of Science, Mathematic; Economics
2012 — 2016
University of Chicago
Master of Science (MS), Financial Mathematics
2016 — 2017
University of Melbourne
Exchange Student
2014 — 2014
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