Wing Cheung

I am a practitioner-turned academic with 15 years of experience in the financial industry, specialising in quantitative finance research, executive education, and consulting, as well as financial technology (FinTech) innovation and entrepreneurship. I have published extensively in the field of quantitative methodology and developed a behaviour-consistent portfolio theory, which has influenced hundreds of professional fund managers worldwide and led to multiple inventions, earning top FinTech awards in the UK, Hong Kong, Singapore, and China, with recognition from organisations such as Accenture, UBS, and Alibaba.

Previously, I served as Head of Portfolio Analytics at Lehman Brothers and Nomura International plc (London), where my team was ranked No.1 in the 2010 Institutional Investor (II) European "Quantitative Research" Survey.

During my time as a practitioner, I spoke at both professional and academic research conferences, taught at financial institutions and graduate schools, supervised PhD-level analysts, and served as a peer reviewer for academic journals and funding bodies.

I hold a PhD from the University of Cambridge, where I specialised in mathematical financial modelling.

Investment decision-making rationale, philosophy, behaviour and ethics; financial information processing; market modelling; holistic factor and risk management; portfolio theorisation and engineering; unified and cognitive investment process; cost-aware portfolio construction and trading; digital asset management (robo-advisor); asset management and WealthTech innovations; investor skill versus luck; transparency and regulation; regulation and RegTech innovations; artificial intelligence (AI) vs science; humanising financial models and theories; risk-neutral pricing etc.

I believe in scientific elegance. Finance is widely recognised as both an art and a science. If this is true, there should be universal principles governing the scientific aspect of finance. Hence, one focus of my research is the discovery and validation of a unified portfolio theory, i.e., universal principles of multi-dimensional decision making.

Since the publication of Modern Portfolio Theory (MPT) (Markowitz, 1952), both practitioners and academics (e.g., Treynor and Black, 1972) have recognised its passive nature. They have called for an active portfolio theory that is more appropriate for broader practices aiming to outperform the market. In response, I published the ABL model (Cheung, 2013), which incorporates natural investor opinions, optimally translates forecasting skills into outperformance, and unifies diverse investor behaviours into a single governing equation. ABL has gained recognition in both industry and academia for its ability to generate purer, more robust, and diversified portfolios that are efficiently aligned with investors’ intentions.

My recent contributions include: (1) empirically demonstrating the reasons and conditions under which investor subjectivity and alternative behaviours outperform MPT (Cheung, 2024c); (2) distilling and validating universal principles that coherently explain and guide diverse portfolio-selection practices, encompassing alternative techniques, folk wisdom, and investor behaviours (Cheung, 2024a & b); and (3) formulating an elegant yet comprehensive portfolio theory that truly unifies theory and (passive as well as active) practice.

SSRN Author page:

https://papers.ssrn.com/sol3/cf_dev/AbsByAuth.cfm?per_id=1171776