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Overconfidence and the adoption of robo-advice: why overconfident investors drive the expansion of automated financial advice

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  • Dominik M. Piehlmaier

    (University of Sussex)

Abstract

Adaptive online platforms, powered by artificial intelligence, commonly referred to as robo-advice, steadily increase their market share. Yet these comparably new financial services are critically understudied. Little is known about why some investors adopt robo-advice for something as essential as asset allocation. The current paper tries to close this gap by shedding light on the causal effect of investor overconfidence on the propensity of using robo-advice. The study proposes a theoretical framework that combines the divergence of opinion hypothesis with consumer behavior insights and information technology diffusion research. The framework is empirically tested on the Investor Sample of the 2015 National Financial Capability Study, a subsample of 2000 US investors. The results from a series of generalized linear, structural, and semiparametric models show that in a pre-chasm market, overconfident investors have a significantly higher propensity of adopting robo-advice. While higher financial literacy seems to decrease robo-advice uptake, unjustified confidence in one’s knowledge causally increases it. Willingness to take financial risk cannot account for the significantly increased adoption of robo-advice among overconfident investors. The findings help managers to better position robo-advice by offering behavioral insights into their user base. In addition, the results outline a managerial tool to take demand-side actions to increase the likelihood of an end-user innovation crossing the chasm.

Suggested Citation

  • Dominik M. Piehlmaier, 2022. "Overconfidence and the adoption of robo-advice: why overconfident investors drive the expansion of automated financial advice," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-24, December.
    • Handle: RePEc:spr:fininn:v:8:y:2022:i:1:d:10.1186_s40854-021-00324-3
    DOI: 10.1186/s40854-021-00324-3
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    as
    1. Lusardi, Annamaria & Mitchell, Olivia S., 2007. "Baby Boomer retirement security: The roles of planning, financial literacy, and housing wealth," Journal of Monetary Economics, Elsevier, vol. 54(1), pages 205-224, January.
    2. Bhatia, Ankita & Chandani, Arti & Chhateja, Jagriti, 2020. "Robo advisory and its potential in addressing the behavioral biases of investors — A qualitative study in Indian context," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).
    3. Kent Daniel & David Hirshleifer, 2015. "Overconfident Investors, Predictable Returns, and Excessive Trading," Journal of Economic Perspectives, American Economic Association, vol. 29(4), pages 61-88, Fall.
    4. Ulrike Malmendier & Timothy Taylor, 2015. "On the Verges of Overconfidence," Journal of Economic Perspectives, American Economic Association, vol. 29(4), pages 3-8, Fall.
    5. Pietro Ortoleva & Erik Snowberg, 2015. "Overconfidence in Political Behavior," American Economic Review, American Economic Association, vol. 105(2), pages 504-535, February.
    6. Berkeley J. Dietvorst & Joseph P. Simmons & Cade Massey, 2018. "Overcoming Algorithm Aversion: People Will Use Imperfect Algorithms If They Can (Even Slightly) Modify Them," Management Science, INFORMS, vol. 64(3), pages 1155-1170, March.
    7. Melissa A. Z. Knoll & Carrie R. Houts, 2012. "The Financial Knowledge Scale: An Application of Item Response Theory to the Assessment of Financial Literacy," Journal of Consumer Affairs, Wiley Blackwell, vol. 46(3), pages 381-410, September.
    8. A. M. Spence, 1981. "The Learning Curve and Competition," Bell Journal of Economics, The RAND Corporation, vol. 12(1), pages 49-70, Spring.
    9. Olsson, Henrik, 2014. "Measuring overconfidence: Methodological problems and statistical artifacts," Journal of Business Research, Elsevier, vol. 67(8), pages 1766-1770.
    10. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    11. Ulrike Malmendier & Geoffrey Tate, 2015. "Behavioral CEOs: The Role of Managerial Overconfidence," Journal of Economic Perspectives, American Economic Association, vol. 29(4), pages 37-60, Fall.
    12. Tam Nguyen & Hae-Ra Han & Miyong Kim & Kitty Chan, 2014. "An Introduction to Item Response Theory for Patient-Reported Outcome Measurement," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 7(1), pages 23-35, March.
    13. Fernandes, Teresa & Oliveira, Elisabete, 2021. "Understanding consumers’ acceptance of automated technologies in service encounters: Drivers of digital voice assistants adoption," Journal of Business Research, Elsevier, vol. 122(C), pages 180-191.
    14. Hall, Crystal C. & Ariss, Lynn & Todorov, Alexander, 2007. "The illusion of knowledge: When more information reduces accuracy and increases confidence," Organizational Behavior and Human Decision Processes, Elsevier, vol. 103(2), pages 277-290, July.
    15. Brenner, Lukas & Meyll, Tobias, 2020. "Robo-advisors: A substitute for human financial advice?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).
    16. Gang Kou & Özlem Olgu Akdeniz & Hasan Dinçer & Serhat Yüksel, 2021. "Fintech investments in European banks: a hybrid IT2 fuzzy multidimensional decision-making approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-28, December.
    17. Markowitz, Harry M, 1991. "Foundations of Portfolio Theory," Journal of Finance, American Finance Association, vol. 46(2), pages 469-477, June.
    18. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    19. Hirshleifer, David & Daniel, Kent, 2015. "Overconfident investors, predictable returns, and excessive trading," MPRA Paper 69002, University Library of Munich, Germany.
    20. David Hirshleifer & Angie Low & Siew Hong Teoh, 2012. "Are Overconfident CEOs Better Innovators?," Journal of Finance, American Finance Association, vol. 67(4), pages 1457-1498, August.
    21. Alberto Abadie & David Drukker & Jane Leber Herr & Guido W. Imbens, 2004. "Implementing matching estimators for average treatment effects in Stata," Stata Journal, StataCorp LP, vol. 4(3), pages 290-311, September.
    22. Amemiya, Takeshi, 1978. "The Estimation of a Simultaneous Equation Generalized Probit Model," Econometrica, Econometric Society, vol. 46(5), pages 1193-1205, September.
    23. James H. Stock & Motohiro Yogo, 2002. "Testing for Weak Instruments in Linear IV Regression," NBER Technical Working Papers 0284, National Bureau of Economic Research, Inc.
    24. Abraham,Facundo & Schmukler,Sergio L. & Tessada,Jose, 2019. "Robo-Advisors : Investing through Machines," Research and Policy Briefs 134881, The World Bank.
    25. Du, Shuili & Xie, Chunyan, 2021. "Paradoxes of artificial intelligence in consumer markets: Ethical challenges and opportunities," Journal of Business Research, Elsevier, vol. 129(C), pages 961-974.
    26. Hill, Aaron D. & Kern, David A. & White, Margaret A., 2014. "Are we overconfident in executive overconfidence research? An examination of the convergent and content validity of extant unobtrusive measures," Journal of Business Research, Elsevier, vol. 67(7), pages 1414-1420.
    27. Kramer, Marc M., 2016. "Financial literacy, confidence and financial advice seeking," Journal of Economic Behavior & Organization, Elsevier, vol. 131(PA), pages 198-217.
    28. Merkle, Christoph, 2017. "Financial overconfidence over time: Foresight, hindsight, and insight of investors," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 68-87.
    29. Lourenço, Carlos J.S. & Dellaert, Benedict G.C. & Donkers, Bas, 2020. "Whose Algorithm Says So: The Relationships Between Type of Firm, Perceptions of Trust and Expertise, and the Acceptance of Financial Robo-Advice," Journal of Interactive Marketing, Elsevier, vol. 49(C), pages 107-124.
    30. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    31. Miller, Edward M, 1977. "Risk, Uncertainty, and Divergence of Opinion," Journal of Finance, American Finance Association, vol. 32(4), pages 1151-1168, September.
    32. Kent Daniel & Alexander Klos & Simon Rottke, 2018. "The Dynamics of Disagreement," NBER Working Papers 25346, National Bureau of Economic Research, Inc.
    33. Al-Nasseri, Alya & Menla Ali, Faek, 2018. "What does investors' online divergence of opinion tell us about stock returns and trading volume?," Journal of Business Research, Elsevier, vol. 86(C), pages 166-178.
    34. David R. Lewis, 2018. "The perils of overconfidence: Why many consumers fail to seek advice when they really should," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 23(2), pages 104-111, June.
    35. Yu, Sandy & Johnson, Scott & Lai, Chiayu & Cricelli, Antonio & Fleming, Lee, 2017. "Crowdfunding and regional entrepreneurial investment: an application of the CrowdBerkeley database," Research Policy, Elsevier, vol. 46(10), pages 1723-1737.
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    2. Esra Alp Coşkun & Hakan Kahyaoglu & Chi Keung Marco Lau, 2023. "Which return regime induces overconfidence behavior? Artificial intelligence and a nonlinear approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-34, December.

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