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)
Panelists:

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

Date

Wednesday 26/04/2017 - Wednesday 26/04/2017

Place

School of Engineering and Applied Science, Princeton University Friend Center, corner of Olden & William Streets, Princeton, NJ 08544, United States

About EDHEC

Operating from campuses in Lille, Nice, Paris, London and Singapore, EDHEC is one of the world’s top 15 business schools. Fully international and directly connected to the business world, EDHEC commands a strong reputation for research excellence and the ability to train entrepreneurs and managers capable of breaking new ground. EDHEC functions as a genuine laboratory of ideas and produces innovative solutions valued by businesses. The School’s teaching is inspired by its research work and a focus on “learning by doing”, all with the aim of equipping people with the skills to succeed in business.

About EDHEC-Risk Climate Impact Institute

Marking the priority assigned by the School to sustainability issues and building on its research programmes exploring the relationships between climate change and finance, EDHEC-Risk Institute became EDHEC-Risk Climate Impact Institute in October 2022. The Institute's mission is to help private and public decision-makers manage climate-related financial risks and make the best use of the financial tools available to transition to low-emission and climate-resilient economies. The Institute’s research programmes explore the relationships between climate change and finance and our key ambition is to become a leading academic reference point for long-term investors, helping them to manage the asset-pricing implications of climate change as well as mitigation and adaptation efforts.