Summary
Tore Opsahl is an executive leader in quantitative finance with 17 years of experience designing systematically-aware strategies for institutional clients, now heading Nomura’s Quantitative Solutions Advisory group after a decade leading BofA’s Systematic Investment Group. He blends deep academic rigour—a PhD in Complex Networks and a postdoc at Imperial—with hands-on product and startup experience as a founder and former Chief Scientist, enabling practical signal-to-production workflows. Tore teaches Advanced Machine Learning in Finance at NYU, translating cutting-edge research into curriculum and industry solutions that reduce unintended risk and distill alpha. Known for synthesising market-wide, industry rotation, and style-factor drivers, he focuses on building bespoke hedges, pure-factor allocations, and tracking strategies that are systematically aware rather than purely model-driven. An uncommon strength is his ability to bridge sell-side execution nuances with institutional portfolio construction, making complex quantitative insights actionable for clients.
16 years of coding experience
1 year of employment as a software developer
PhD, Complex networks and organisation theory, PhD, Complex networks and organisation theory at University of London, QM
-, Management, -, Management at University of California, Irvine - The Paul Merage School of Business
English, Norwegian