Summary
Euiyoung Chung is a quantitative researcher based in New York with eight years of experience building medium-frequency statistical arbitrage alphas and production-grade data pipelines for global equity trading. He has a track record of creating high-sharp (2.5+) daily-traded alpha signals and developing time-series, linear and ML models from diverse financial and alternative datasets, including analyst estimates, options, news and employment data. At Millennium and now Brevan Howard he combined hands-on research with engineering—implementing extended-Python concurrent ingest pipelines and C++ real-time market-data systems that serve firm-wide quant teams. He also led predictive research groups applying LLMs and ML techniques to generate internal alpha sources and operational insights. A Columbia-trained statistician with prior experience in high-throughput tick processing and a background that includes military leadership, he brings disciplined, production-first research that bridges academia and trading-floor exigencies.
8 years of coding experience
6 years of employment as a software developer
M.A., Statistics, M.A., Statistics at Columbia University
B.A., Economics, B.A., Economics at Yonsei University
Korean, English