Summary
Gabriel Feng is a portfolio manager and quantitative researcher with 11 years of experience building data-driven trading systems and managing FoF/MoM investments focused on mainland China. He combines hands-on quant engineering—designing databases, accelerating Python with Numba, and deploying trading bots on Linux—with portfolio-level due diligence and hedge fund sourcing across diverse strategies and AUMs. His work spans mid- and high-frequency strategies, option and arbitrage execution, and factor mining using genetic programming and deep learning, with practical wins like 800x preprocessing speedups and multi-fold factor performance improvements. Based in the New York metro area, he’s currently sourcing risk-differentiated trading ideas while maintaining proprietary data pipelines and automated risk/return attribution tools. Notably, he blends research rigor with production-ready engineering, having rebuilt core systems from schema design to remote execution.
11 years of coding experience
3 years of employment as a software developer
Master’s Degree, Quantitative Finance, 3.78/4.0, Master’s Degree, Quantitative Finance, 3.78/4.0 at Hofstra University
Bachelor’s Degree, Finance, General, 3.3/4.0, Bachelor’s Degree, Finance, General, 3.3/4.0 at Shenzhen University
English, Chinese, Chinese