The research initiative “ Prise de Risque des Épargnants Français “ (PREF), in partnership with the University of Orléans, the Institut Louis (ILB) and Yomoni, organised a “Financial advice, Profiling and Portfolio Choice of Households” workshop, which took place on December 8 at the ILB. This academic event was part of the ILB’s Finance and Insurance Reloaded (FaIR) programme.
The workshop allowed to present recent research on financial advice, profiling, the role of human versus algorithmic advice and the impact of robo advisors.
The event was introduced by Yomoni, the industrial partner of the PREF research initiative, represented by its COO Clément Berlioz, who highlighted issues related to financial advice, profiling and portfolio choices made by households. The guest researchers then presented their work.
Human financial advisors and their clients
Matthias Stefan from the University of Innsbruck in Austria presented his study “You can’t always get what you want – An experiment on finance professionals’ decisions for others“, co-authored with Martin Holmén (University of Gothenburg), Felix Holzmeister (University of Innsbruck), Michael Kirchler (Lund University) and Erik Wengström (Hanken School of Economics). Their work shows that financial professionals exhibit greater decision quality than the general population when investing for their own account, but when deciding on behalf of clients, the decision quality of professionals does not differ significantly from that of their clients.
Do robo-advisors better account for household preferences?
Béatrice Boulu-Reshef (University of Orléans, LEO) presented her study “Algorithmic vs. Human Portfolio Choice“, co-authored with Alexis Direr (University of Orléans, LEO) and Nicole von Wilczur (Ayolab). The paper examines the interaction between portfolio recommendations made by a robo-advisor –Yomoni – and its users, allowing them to choose their risk exposure after receiving this recommendation. Results show that the risk profiles recommended by the robo-advisor are qualitatively aligned with financial portfolio theory. Although a variety of information is used by the algorithm its recommendations are very much based on responses regarding financial risk taking.
Next, Marie Brière (Amundi Asset Management, Paris Dauphine University) presented her paper “Augmenting Investment Decisions with Robo-Advice“, co-authored with Milo Bianchi (Toulouse School of Economics). The paper analyses the implementation of a robo-advisor in Amundi’s employee savings plans. It shows that the introduction of robo-advice increased investors’ attention to their savings plan as well as their exposure to equity markets. It also changed the portfolio rebalancing dynamics by sending alerts. These changes improved portfolios risk-adjusted returns, especially for smaller investors who rarely have access to financial advice.
Indigo Jentry Jones (University of Orleans, LEO) then presented his paper “Who invests on behalf of their children and how?: Evidence from a robo-advisor”, co-authored with Alexis Direr, which studies the investment behaviour of parents on behalf of their children. It shows the existence of a gender bias and a similarity between the risk profiles of parents and children.
Finally, Philippe d’Astous (HEC Montréal) presented his paper “The Quality of Financial Advice: What Influences Client Recommendations?“, co-authored with Irina Gemmo (HEC Montréal) and Pierre-Carl Michaud (HEC Montréal), which shows that financial recommendations are often in line with what one would expect given economic theory. In particular, advisors are sensitive to the relative costs and benefits of investment options. The study illustrates that advisers are more likely to recommend products that they themselves or their spouse owns, or that they are licensed to sell.
Excellent discussions of the above-mentioned papers were given by Hela Maafi (Paris 8, Vincennes-Saint Denis University), Sylvain Carré (Paris-Dauphine PSL University), Frédéric Loss (ENSAE Paris), Luc Arrondel (Paris School of Economics) and Thomas Renault (Paris 1 Panthéon-Sorbonne University).
