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Robo Advising and Investor Profiling

Author

Listed:
  • Raquel M. Gaspar

    (ISEG, Universidade de Lisboa and REM/Cemapre Research Center, 1200-781 Lisboa, Portugal)

  • Madalena Oliveira

    (AXCO Consulting, 4150-174 Porto, Portugal)

Abstract

The rise of digital technology and artificial intelligence has led to a significant change in the way financial services are delivered. One such development is the emergence of robo advising, which is an automated investment advisory service that utilizes algorithms to provide investment advice and portfolio management to investors. Robo advisors gather information about clients’ preferences, financial situations, and future goals through questionnaires. Subsequently, they recommend ETF-based portfolios tailored to match the investor’s risk profile. However, these questionnaires often appear vague, and robo advisors seldom disclose the methodologies employed for investor profiling or asset allocation. This study aims to contribute by introducing an investor profiling method relying solely on investors’ relative risk aversion (RRA), which, in addition, allows for the determination of optimal allocations. We also show that, for the period under analysis and using the same ETF universe, our RRA portfolios consistently outperform those recommended by the Riskalyze platform, which may suffer from ultraconservadorism in terms of the proposed volatility.

Suggested Citation

  • Raquel M. Gaspar & Madalena Oliveira, 2024. "Robo Advising and Investor Profiling," FinTech, MDPI, vol. 3(1), pages 1-14, February.
    • Handle: RePEc:gam:jfinte:v:3:y:2024:i:1:p:7-115:d:1332493
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    References listed on IDEAS

    as
    1. Zakamouline, Valeri & Koekebakker, Steen, 2009. "Portfolio performance evaluation with generalized Sharpe ratios: Beyond the mean and variance," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1242-1254, July.
    2. Francesco D’Acunto & Nagpurnanand Prabhala & Alberto G Rossi, 2019. "The Promises and Pitfalls of Robo-Advising," The Review of Financial Studies, Society for Financial Studies, vol. 32(5), pages 1983-2020.
    3. Agostino Capponi & Sveinn Ólafsson & Thaleia Zariphopoulou, 2022. "Personalized Robo-Advising: Enhancing Investment Through Client Interaction," Management Science, INFORMS, vol. 68(4), pages 2485-2512, April.
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    5. Donald Meyer & Jack Meyer, 2005. "Relative Risk Aversion: What Do We Know?," Journal of Risk and Uncertainty, Springer, vol. 31(3), pages 243-262, December.
    6. Muhammad Anshari & Mohammad Nabil Almunawar & Masairol Masri, 2022. "Digital Twin: Financial Technology’s Next Frontier of Robo-Advisor," JRFM, MDPI, vol. 15(4), pages 1-9, April.
    Full references (including those not matched with items on IDEAS)

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