Michael Pang

Michael Pang is a Quantitative Researcher at Aquatic Capital Management, based in Chicago, IL. In his current role, he focuses on the development and implementation of quantitative trading strategies, leveraging advanced data analysis and statistical modeling to optimize investment decisions within the hedge fund's portfolio. While the firm manages multi-asset class strategies, Pang's expertise centers on systematic approaches to liquid markets, including equities and derivatives, employing cutting-edge techniques in machine learning and predictive modeling.

Prior to joining Aquatic in early 2020, Pang gained experience as a Software Engineering Intern and AI Research Intern at Wish, where he built robust data-driven solutions and worked on artificial intelligence applications tailored to e-commerce and recommendation algorithms. These roles honed his programming and analytical skills, providing a strong foundation for transitioning to quantitative finance.

Pang holds a degree from the University of Waterloo, a university renowned for its STEM programs, which equipped him with deep proficiency in computer science, statistics, and applied mathematics. His contributions to Aquatic Capital Management include advances in research infrastructure and modeling efficiency, supporting the firm's success in competitive markets and systematic investing.