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Finance Research Seminar – Dr. Wing Cheung | Thursday, 19 June, 2–3 PM (Online)

When:
Venue: Online

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We are delighted to invite you to the upcoming Online Finance Research Seminar on Thursday, 19 June, from 2:00 to 3:00 PM. We are pleased to welcome Dr. Wing Cheung from the University of Roehampton, who will present his research:

Title:
Exploring Parsimonious Principles that Unify Active Portfolio Selection
(I) Model • (II) Validation

Abstract:
This research demonstrates that two key principles—Subjective Allocation Rule-based allocation and Minimum Tracking Error-guided mimicking—are sufficient to create a unified framework for diverse active portfolio selection behaviors. These principles offer efficient, cognition-friendly mechanisms for translating broad investor insights into optimal portfolios aligned with dynamic, subjective utility. Portfolio selection is presented as a goal-directed, feedback-responsive process that evolves with beliefs and portfolio characteristics, in line with descriptive decision theory.

Empirical validation shows that investor subjectivity, when coupled with skill, can substantially improve performance—outperforming traditional models such as Markowitz’s mean-variance framework.

·         The first paper develops the theoretical model.

·         The second paper provides the empirical validation.

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Speakers
  • Dr. Wing Cheung -

    Dr. Wing Cheung is a practitioner-turned-academic with over 15 years of experience in the financial industry, specialising in quantitative research, executive education, consulting, and FinTech innovation. He is the developer of a behaviourally consistent portfolio theory that has influenced hundreds of fund managers and led to award-winning FinTech solutions recognised by Accenture, UBS, and Alibaba. Previously Head of Portfolio Analytics at Lehman Brothers and Nomura, his team was ranked No.1 in the 2010 Institutional Investor European Quant Survey. Dr. Cheung holds a PhD in Mathematical Finance from the University of Cambridge and has published widely, taught at several institutions, supervised PhD-level analysts, and reviewed for academic journals.