Edhec-Risk

Four-University Rotating FinTech Conference: Wealth Management Systems for Individual Investors

Maud Gauchon, Marketing & Communication Manager, EDHEC-Risk Institute

Maud Gauchon

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 – EDHEC-Risk Institute, Korea Advanced Institute of Science and Technology (KAIST), Princeton University and Tsinghua University – renowned for the quality and relevance of their educational and research programmes in finance and technology 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) from around the world.

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

Lionel Martellini, Professor of Finance, EDHEC Business School and Director, EDHEC-Risk Institute will give the first presentation of the day, entitled by entitled Mass-Customisation of Goal-Based Investment Solutions: The New Frontier in Digital Wealth Management Services. In that presentation, he will describe how dynamic asset pricing theory and financial engineering can be used to design scalable mass-customised forms of retirement solutions that can address the specific retirement needs and constraints of a large number of individuals in a relatively parsimonious manner. He will 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-customised investment solutions that can effectively meet their retirement goals and beyond.

Then, Woo Chang Kim, Associate Professor, Industrial and Systems Engineering Department, and Head, KAIST Center for Wealth Management Technologies, KAIST, will give a talk entitled Goal-Based Investment via Multi-Stage Stochastic Goal Programming for Robo-Advisor Services. Robo-advisors, a term that denotes recently developed online investment management or advisory services, aim to provide individual investors with automatic professional wealth management services and assist financial advisors in solving financial planning and asset allocation solutions. Unfortunately, existing robo-advisory schemes have not been sophisticated enough to provide fully personalized investment advices for two main reasons. In his presentation, he will propose a goal-based investment model that only requires the input of wealth, income, and consumption goals with priorities; the framework clearly defines the personalized wealth management problem mathematically and his algorithm can find the truly optimal solution in theory. Its computational efficiency makes it highly applicable to real-world scenarios. The model combines multi-stage stochastic programming and goal programming approaches, while maintaining its linear programming problem structure. With its simplicity, flexibility, and computational efficiency, it provides a new framework for automated investment management services.

Morning presentations will close with a presentation from John Mulvey, Professor of Operations Research and Financial Engineering, ORFE Department, Princeton University entitled Applying machine learning concepts for asset allocation and ALM. 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. Professor Mulvey will 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 modelling systems.

John Mashey, who has been a pioneer in the world of information technology for over 40 years, will be our lunchtime speaker and he will discuss the topic of big data – from a historical context and looking forward. The term “Big Data” was introduced in the early 1990s (by the speaker), but the general computing problem has been given many names, dating as far back 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 organisations to tackle problems that were beyond the capabilities of even large companies and governments just a few decades ago. His presentation Big Data – Yesterday, Today and Tomorrow will offer a brief history of the phrase’s meaning and applications at various times, and will look at the lessons that can be learned from its history and current status, to offer some insights about its future prospects and plausible new applications.

After lunch, the speaker will be Andrew Yao from Tsinghua University, A.M. Turing Award winner in recognition of his fundamental contributions to the theory of computation. He will give a talk entitled FinTech: Drawing Strengths from Computing Theories.

This presentation will be followed by the reading of a report specially written for the conference by John C. Bogle, Founder of The Vanguard Group and President of the Bogle Financial Markets Research Center, entitled Savings and Investing to Achieve Retirement Goals: an Update Given Current Market Assumptions, to be discussed with the panellists of the closing round table. In 2004, TIME magazine named Mr. Bogle as one of the world's 100 most powerful and influential people and Institutional Investor presented him with its Lifetime Achievement Award. In 1999, Fortune designated him as one of the investment industry's four “Giants of the 20th Century”.

The conference will close with a round table that will discuss The Rise of Robo-Advisors: A Threat or an Opportunity for the Wealth Management Industry? The panel discussion will be moderated by Amy Resnick, Editor of Pensions & Investments (P&I), and will include the participation of Anil Suri, Managing Director, Head of Portfolio Construction & Investment Analytics, Merrill Lynch Wealth Management; Thomas Bauerfeind, Managing Director, Protinus; Changle Lin, Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University; Pierre Laroche, Vice President – Business Strategy, Wealth Management, National Bank of Canada; Arthur M. Berd, Founder and CEO, General Quantitative; Lisa Huang, Head of Quantitative Analysis Research, Betterment; and Ashish Gupta, VP, Model Risk Management, E*TRADE Financial Corp.

The conference will include the participation of official partners SAMSUNG Asset Management and Ant Financial.

Further information on the conference can be found in the programme.

Delegates will also have the opportunity to stay at the Princeton Campus on 27 April for a related event, dedicated to exclusive in-depth tutorial classes and demonstrations (on machine learning in finance, goal-based investing, digital wealth systems and more).

Registrations for the conference are limited to 100 seats (40 seats for the tutorial classes). To book your seat, please access the dedicated registration website. Should you need any help with your registration, please contact me at maud.gauchon@edhec-risk.com or on +33 493 187 887.


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