Yucheng Xu
Quantitative Researcher
Berkeley, California, United States
Summary
👤
Senior🎓
Top SchoolYucheng Xu is a quantitative researcher based in Berkeley with nine years of experience building and deploying mid- to high-frequency trading strategies across Chinese futures, A-shares, and convertible bond markets. He combines hands-on alpha research, feature engineering on order book data, and execution algo development—having deployed an HFT convertible bond strategy that generated meaningful P&L in 2022 and implemented a TWAP variant in C++ that materially cut execution cost. Recent work spans ML-driven return and fill-probability models, LLM/NLP sentiment experiments at Goldman Sachs, and production backtesting and data pipelines at a proprietary trading firm. Comfortable moving models from research to production, he blends quantitative rigor with pragmatic software engineering and a penchant for digging into market microstructure nuances. The Chinese aphorism in his GitHub bio hints at a steady, process-oriented mindset that favors long-term learning over short-term outcomes.
9 years of coding experience
Summer School Program Computer Science, Summer School Program Computer Science at University of California, BerkeleyBachelor of Business Administration Finance General, Bachelor of Business Administration Finance General at The Chinese University of Hong Kong, Shenzhen 香港中文大学（深圳）Master's Degree Financial Engineering, Master's Degree Financial Engineering at University of California, Berkeley, Haas School of Business
Github Skills (23)
datasets7
machine-learning7
torchvision7
loss7
wan7
computer-vision7
scoring6
speaker6
clustering5
supervised-learning5
deep-learning5
pytorch5
recurrent4
verification4
mask3
Programming languages (2)
Github contributions (5)
guruL/CS131_Fall2017_NoteAndHomeWork
Jul 2018 - Aug 2018
Contributions:11 commits, 10 pushes in 20 days
dl416/Read-Deep-Learning-Paper-In-Chinese
Apr 2019 - May 2019
论文笔记
Contributions:27 commits, 18 PRs, 8 pushes in 1 month
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