Wealth Management Systems for Individual Investors Conference

Four-University Rotating FinTech Conference

In the context of the fourth revolution, the digital revolution, which is likely to have a dramatic impact on the investment industry, four prominent academic institutions renowned for the quality and relevant of their educational and research programmes in finance and technology – EDHEC-Risk Institute, KAIST, Princeton and Tsinghua Universities – are partnering for the first time.

Together, they will host an international series of rotational conferences on financial technologies and offer a forum that will facilitate discussion among all interested parties (academics, practitioners and regulators) around the world.

The conferences will take place annually, starting on 26 April 2017 with the Four-University Rotating FinTech Conference: Wealth Management Systems for Individual Investors, which will take place on Princeton Campus, and jointly organised by EDHEC-Risk Institute and Princeton University ORFE department.

Leading experts from the US, Asia and Europe will be featured at the conference, including, Andrew Yao (Turing Award recipient and founder of IIIS FinTech Center at Tsinghua University), Woo Chang Kim (Associate Professor at KAIST), Lionel Martellini (Director of EDHEC-Risk Institute), and John Mulvey (Professor and founding member of the Bendheim Center for Finance at Princeton University).

Program - 26 April, 2017

  • Morning Sessions (9:00am-12:45pm)

9:00am-9:15am: Opening Address
John Mulvey, Professor of Operations Research and Financial Engineering, ORFE Department, Princeton University
Lionel Martellini, Professor of Finance, EDHEC Business School, and Director, EDHEC-Risk Institute

9:15am-10:15am: Mass-Customisation of Goal-Based Investment Solutions: The New Frontier in Digital Wealth Management Services
Lionel Martellini, Professor of Finance, EDHEC Business School, and Director, EDHEC-Risk Institute
As a result of a massive shift of retirement risks on individuals, the investment management industry is currently facing an historical responsibility in terms of the need to provide households with suitable retirement solutions. Target date funds, annuities, variable annuities and other existing retirement products, however, suffer from a number of shortcomings that make them ill-suited for investors saving for retirement in the accumulation phase of their life-cycle. In this presentation, we shall describe how dynamic asset pricing theory and financial engineering can be used to design scalable mass-customized forms of retirement solutions that can address in a relatively parsimonious manner the specific retirement needs and constraints of a large number of individuals. We shall also discuss how digital wealth management services are ideally suited to allow for a meaningful goal-based dialogue with individual investors, a dialogue that is a pre-requisite for the production and digital distribution of mass-customized investment solutions that can effectively meet their retirement goals and beyond.

10:15am-11:15am: Goal-Based Investment via Multi-Stage Stochastic Goal Programming for Robo-Advisor Services
Woo Chang Kim, Associate Professor, Industrial and Systems Engineering Department, and Head, KAIST Center for Wealth Management Technologies, Korea
Advanced Institute of Science and Technology (KAIST)

11:15am-11:45am: Morning Break

11:45am-12:45pm: Applying machine learning concepts for asset allocation and ALM
John Mulvey, Professor of Operations Research and Financial Engineering, ORFE Department, Princeton University
Over the past decade, large institutional investors have shifted capital to alternative asset categories (private equity, real assets, hedge funds and so on), led by leading U.S. university endowments. We discuss the impact of these trends on the practice of asset allocation and ALM. Alternative assets are more difficult to evaluate due to the blending of multiple risk factors. Machine learning approaches can assist with several critical tasks: 1) identifying economic regimes, 2) estimating the underlying factors and the factor loadings in a robust manner, and 3) setting capital market assumptions. Each of these topics will be discussed with reference to robo-advisor modeling systems.

12:45pm-2:00pm: Luncheon talk: Big Data - Yesterday, Today and Tomorrow
John Mashey, Consultant, Techviser
The phrase “Big Data” was introduced in the early 1990s (by the speaker), but the general computing problem has been given many names, starting as early as 1890.
In every era of computing, computing hardware has grown in performance and capacity, often needing new software to employ it well. As a result, audiences for Big Data applications have grown, enabling even small organizations to tackle problems that were beyond even large companies and governments just a few decades ago. Lessons can be learned from its history and current status, hopefully to offer some insights about its future prospects and plausible new applications.

  • Afternoon Sessions (2:00pm-5:00pm)

2:00pm-3:00pm: FinTech: Drawing Strengths from Computing Theories
Andrew Yao, Professor and Dean of Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University

3:00pm-3:30pm: Afternoon Break

3:00pm-4:15pm: Savings and Investing to Achieve Retirement Goals: an Update Given Current Market Assumptions
Reading of exclusive John C. Bogle's report, Founder of The Vanguard Group and President of the Bogle Financial Markets Research Center with comments from roundtable's panelists

4:15pm-5:30pm: Roundtable The Rise of RoboAdvisors: A Threat or an Opportunity for the Wealth Management Industry?
Moderator: Pensions & Investments (P&I)

  • Thomas Bauerfeind, Managing Director, Protinus
  • Anil Suri, Head of Portfolio Analytics & Innovation Development Center, Merrill Lynch Wealth Management
  • Changle Lin, Assistant Professor, Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University
  • Pierre Laroche, Vice President – Business Strategy, Wealth Management, National Bank of Canada
  • Lisa Huang, Director of Quantitative Investing, Betterment
  • Arthur Berd, Founder and CEO, General Quantitative
  • Ashish Gupta, VP, Model Risk Management, E*TRADE Financial Corp
  • Alan Qi, Chief Data Scientist, Ant Financial

5:30pm-6:30pm: Drinks Reception

Download the full conference program 26 April, 2017