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What drives robo-advice?

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  • Scherer, Bernd
  • Lehner, Sebastian

Abstract

The promise of robo-advisory firms is to provide low-cost access to diversified portfolios built according to academic literature on normative portfolio choice. We investigate the extent to which robo-advice aligns with normative advice. Using web-scraped portfolio recommendations for 151,200 investor types from a major US robo-advisor, we find that investment goals and time horizons significantly influence recommended equity allocations, while Merton-type hedging demands are largely ignored. Our results suggest that commercial robo-advisors prioritize simplicity and client perceptions over complex, normative models. By integrating data from the NFCS survey, we further explore how demographic factors influence the likelihood of using robo-advisory services. This study provides empirical evidence on how closely robo-advisory services align with normative portfolio theory, highlighting the practical compromises made in the pursuit of broad market appeal and user-friendly solutions.

Suggested Citation

  • Scherer, Bernd & Lehner, Sebastian, 2025. "What drives robo-advice?," Journal of Empirical Finance, Elsevier, vol. 80(C).
  • Handle: RePEc:eee:empfin:v:80:y:2025:i:c:s0927539824001087
    DOI: 10.1016/j.jempfin.2024.101574
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    as
    1. Back, Kerry, 2010. "Asset Pricing and Portfolio Choice Theory," OUP Catalogue, Oxford University Press, number 9780195380613, Decembrie.
    2. Khemka, Gaurav & Steffensen, Mogens & Warren, Geoffrey J., 2021. "How sub-optimal are age-based life-cycle investment products?," International Review of Financial Analysis, Elsevier, vol. 73(C).
    3. van Rooij, Maarten & Lusardi, Annamaria & Alessie, Rob, 2011. "Financial literacy and stock market participation," Journal of Financial Economics, Elsevier, vol. 101(2), pages 449-472, August.
    4. Joao F. Cocco, 2005. "Portfolio Choice in the Presence of Housing," The Review of Financial Studies, Society for Financial Studies, vol. 18(2), pages 535-567.
    5. 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.
    6. John Y. Campbell, 2016. "Restoring Rational Choice: The Challenge of Consumer Financial Regulation," American Economic Review, American Economic Association, vol. 106(5), pages 1-30, May.
    7. 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.
    8. Bodie, Zvi & Merton, Robert C. & Samuelson, William F., 1992. "Labor supply flexibility and portfolio choice in a life cycle model," Journal of Economic Dynamics and Control, Elsevier, vol. 16(3-4), pages 427-449.
    9. Annamaria Lusardi & Pierre-Carl Michaud & Olivia S. Mitchell, 2017. "Optimal Financial Knowledge and Wealth Inequality," Journal of Political Economy, University of Chicago Press, vol. 125(2), pages 431-477.
    10. Merton, Robert C., 1971. "Optimum consumption and portfolio rules in a continuous-time model," Journal of Economic Theory, Elsevier, vol. 3(4), pages 373-413, December.
    11. Spaenjers, Christophe & Spira, Sven Michael, 2015. "Subjective life horizon and portfolio choice," Journal of Economic Behavior & Organization, Elsevier, vol. 116(C), pages 94-106.
    12. Das, Sanjiv & Markowitz, Harry & Scheid, Jonathan & Statman, Meir, 2010. "Portfolio Optimization with Mental Accounts," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(2), pages 311-334, April.
    13. John Beshears & James J. Choi & David Laibson & Brigitte C. Madrian, 2018. "Behavioral Household Finance," NBER Working Papers 24854, National Bureau of Economic Research, Inc.
    14. Utpal Bhattacharya & Andreas Hackethal & Simon Kaesler & Benjamin Loos & Steffen Meyer, 2012. "Is Unbiased Financial Advice to Retail Investors Sufficient? Answers from a Large Field Study," The Review of Financial Studies, Society for Financial Studies, vol. 25(4), pages 975-1032.
    15. LuisM. Viceira & John Y. Campbell, 2001. "Who Should Buy Long-Term Bonds?," American Economic Review, American Economic Association, vol. 91(1), pages 99-127, March.
    16. John H Cochrane, 2022. "Portfolios for Long-Term Investors [Rare disasters and asset markets in the twentieth century]," Review of Finance, European Finance Association, vol. 26(1), pages 1-42.
    17. Bannier, Christina E. & Neubert, Milena, 2016. "Gender differences in financial risk taking: The role of financial literacy and risk tolerance," Economics Letters, Elsevier, vol. 145(C), pages 130-135.
    18. Sendhil Mullainathan & Markus Noeth & Antoinette Schoar, 2012. "The Market for Financial Advice: An Audit Study," NBER Working Papers 17929, National Bureau of Economic Research, Inc.
    19. Daniel Hoechle & Stefan Ruenzi & Nic Schaub & Markus Schmid, 2017. "The Impact of Financial Advice on Trade Performance and Behavioral Biases," Review of Finance, European Finance Association, vol. 21(2), pages 871-910.
    20. John H. Cochrane, 1999. "Portfolio advice of a multifactor world," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 23(Q III), pages 59-78.
    21. Paola Sapienza & Anna Toldra‐Simats & Luigi Zingales, 2013. "Understanding Trust," Economic Journal, Royal Economic Society, vol. 123(12), pages 1313-1332, December.
    22. Juhani T. Linnainmaa & Brian T. Melzer & Alessandro Previtero, 2021. "The Misguided Beliefs of Financial Advisors," Journal of Finance, American Finance Association, vol. 76(2), pages 587-621, April.
    23. Tao, Ran & Su, Chi-Wei & Xiao, Yidong & Dai, Ke & Khalid, Fahad, 2021. "Robo advisors, algorithmic trading and investment management: Wonders of fourth industrial revolution in financial markets," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    24. Söhnke M. Bartram & Jürgen Branke & Mehrshad Motahari, 2020. "Artificial intelligence in asset management," Working Papers 20202001, Cambridge Judge Business School, University of Cambridge.
    25. William F. Sharpe, 1963. "A Simplified Model for Portfolio Analysis," Management Science, INFORMS, vol. 9(2), pages 277-293, January.
    26. Christian Hildebrand & Anouk Bergner, 2021. "Conversational robo advisors as surrogates of trust: onboarding experience, firm perception, and consumer financial decision making," Journal of the Academy of Marketing Science, Springer, vol. 49(4), pages 659-676, July.
    27. Stephen Foerster & Juhani T. Linnainmaa & Brian T. Melzer & Alessandro Previtero, 2017. "Retail Financial Advice: Does One Size Fit All?," Journal of Finance, American Finance Association, vol. 72(4), pages 1441-1482, August.
    28. Zefeng Bai, 2024. "Examining the association between robo-advisory and perceived financial satisfaction," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 16(4), pages 668-681, January.
    29. Hsu, Jason C., 2012. "What drives equity market non-participation?," The North American Journal of Economics and Finance, Elsevier, vol. 23(1), pages 86-114.
    30. Zvi Bodie & Dwight B. Crane, 1997. "Personal Investing: Advice, Theory, and Evidence," Financial Analysts Journal, Taylor & Francis Journals, vol. 53(6), pages 13-23, November.
    31. Bernd Scherer, 2017. "Algorithmic portfolio choice: lessons from panel survey data," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(1), pages 49-67, February.
    32. Ankita Bhatia & Arti Chandani & Rizwana Atiq & Mita Mehta & Rajiv Divekar, 2021. "Artificial intelligence in financial services: a qualitative research to discover robo-advisory services," Qualitative Research in Financial Markets, Emerald Group Publishing Limited, vol. 13(5), pages 632-654, September.
    33. Joao F. Cocco, 2005. "Consumption and Portfolio Choice over the Life Cycle," The Review of Financial Studies, Society for Financial Studies, vol. 18(2), pages 491-533.
    34. Anna Warchlewska & Krzysztof Waliszewski, 2020. "Who uses Robo-Advisors? The Polish Case," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 97-114.
    35. Merton, Robert C, 1969. "Lifetime Portfolio Selection under Uncertainty: The Continuous-Time Case," The Review of Economics and Statistics, MIT Press, vol. 51(3), pages 247-257, August.
    36. Bernd Scherer & Sebastian Lehner, 2023. "Trust me, I am a Robo-advisor," Journal of Asset Management, Palgrave Macmillan, vol. 24(2), pages 85-96, March.
    37. Mark Grinblatt & Matti Keloharju & Juhani Linnainmaa, 2011. "IQ and Stock Market Participation," Journal of Finance, American Finance Association, vol. 66(6), pages 2121-2164, December.
    38. Nicholas Barberis, 2000. "Investing for the Long Run when Returns Are Predictable," Journal of Finance, American Finance Association, vol. 55(1), pages 225-264, February.
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    Cited by:

    1. Christian Fieberg & Lars Hornuf & Maximilian Meiler & David J. Streich, 2025. "Using Large Language Models for Financial Advice," CESifo Working Paper Series 11666, CESifo.

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    More about this item

    Keywords

    Robo-advice; Portfolio theory; Merton hedging demand; Behavioral finance; Demographic factors;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance

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