Summary
Weizhi Liu is a research analyst and quantitative researcher with 11 years of experience building and evaluating systematic strategies across global markets, currently at Cubist Systematic Strategies in Hong Kong. He combines a PhD-focused background in Industrial System Engineering and Management from NUS with hands-on production research spanning bonds, equities, commodities, and FX, including portfolio optimization and data-ops tooling. His track record includes designing hundreds of long-short strategies at WorldQuant with strong risk-adjusted performance, including an out-of-sample Sharpe ratio of 5.26 for a top-performing strategy and top regional honors in the 2017 WorldQuant Alphathon. Earlier, he led simulation-budget allocation research at NUS and developed a multi-factor, machine-learning-driven framework for forecasting month-ahead returns, plus an automatic stowage planning tool saving millions for CMA CGM. He also built graph-based anti-fraud analytics at ADVANCE.AI, deploying production-ready detections on large ride-order datasets. Based in Hong Kong, he blends rigorous optimization with pragmatic engineering to turn noisy data into disciplined, low-correlation alpha.
11 years of coding experience
3 years of employment as a software developer
Bachelor's Degree, Financial Engineering, Bachelor's Degree, Financial Engineering at Nanjing University
Doctor of Philosophy (Ph.D.), Industrial System Engineering and Management, Doctor of Philosophy (Ph.D.), Industrial System Engineering and Management at National University of Singapore
Chinese, English