IDEAS home Printed from https://ideas.repec.org/a/zbw/jumsac/294920.html
   My bibliography  Save this article

UX in AI: Trust in Algorithm-based Investment Decisions

Author

Listed:
  • Szeli, Leon

Abstract

This Thesis looks at investors' loss tolerance with portfolios managed by a human advisor compared to an algorithm with different degrees of humanization. The main goal is to explore differences between these groups (Humanized Algorithm, Dehumanized Algorithm, Humanized Human and Dehumanized Humans) and a potential diverging effect of humanizing. The Thesis is based on prior research (Hodge et al., 2018) but incorporates new aspects such as additional variables (demographics, prior experiences) and a comparison between users and non-users of automated-investment products. The core of this research is an experiment simulating an investment portfolio over time with four different portfolio managers. Subjects were asked to decide if they want to hold or sell a declining portfolio at five points in time to measure their loss tolerance. A cox regression model shows that portfolios managed by the Humanized Human had the highest loss tolerance. Humanizing leads to higher loss tolerance for the human advisor but to lower loss tolerance for algorithmic advisors within the non-user group.

Suggested Citation

  • Szeli, Leon, 2020. "UX in AI: Trust in Algorithm-based Investment Decisions," Junior Management Science (JUMS), Junior Management Science e. V., vol. 5(1), pages 1-18.
    • Handle: RePEc:zbw:jumsac:294920
    DOI: 10.5282/jums/v5i1pp1-18
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/294920/1/5061-3261.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.5282/jums/v5i1pp1-18?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Laura Bottazzi & Marco Da Rin & Thomas Hellmann, 2016. "Editor's Choice The Importance of Trust for Investment: Evidence from Venture Capital," The Review of Financial Studies, Society for Financial Studies, vol. 29(9), pages 2283-2318.
    2. Houser, Daniel & Schunk, Daniel & Winter, Joachim, 2010. "Distinguishing trust from risk: An anatomy of the investment game," Journal of Economic Behavior & Organization, Elsevier, vol. 74(1-2), pages 72-81, May.
    3. L. Bottazzi & M. Da Rin & T. Hellmann, 2007. "The Importance of Trust for Investment: Evidence from Venture Capital," Working Papers 612, Dipartimento Scienze Economiche, Universita' di Bologna.
    4. repec:bla:jfinan:v:53:y:1998:i:5:p:1775-1798 is not listed on IDEAS
    5. 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.
    6. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    7. Luigi Guiso & Paola Sapienza & Luigi Zingales, 2008. "Trusting the Stock Market," Journal of Finance, American Finance Association, vol. 63(6), pages 2557-2600, December.
    8. Grinblatt, Mark & Keloharju, Matti, 2000. "The investment behavior and performance of various investor types: a study of Finland's unique data set," Journal of Financial Economics, Elsevier, vol. 55(1), pages 43-67, January.
    9. Highhouse, Scott, 2008. "Stubborn Reliance on Intuition and Subjectivity in Employee Selection," Industrial and Organizational Psychology, Cambridge University Press, vol. 1(3), pages 333-342, September.
    10. Harvey James, 2002. "The Trust Paradox: A Survey of Economic Inquiries Into the Nature of Trust and Trustworthiness," Microeconomics 0202001, University Library of Munich, Germany.
    11. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Qin, Wei & Liang, Quanxi & Jiao, Yan & Lu, Meiting & Shan, Yaowen, 2022. "Social trust and dividend payouts: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 72(C).
    2. Jens Hagendorff & Sonya Lim & Duc Duy Nguyen, 2023. "Lender Trust and Bank Loan Contracts," Management Science, INFORMS, vol. 69(3), pages 1758-1779, March.
    3. Dowling, Michael & O’Gorman, Colm & Puncheva, Petya & Vanwalleghem, Dieter, 2019. "Trust and SME attitudes towards equity financing across Europe," Journal of World Business, Elsevier, vol. 54(6), pages 1-1.
    4. Amore, Mario Daniele & Epure, Mircea, 2021. "Riding out of a financial crisis: The joint effect of trust and corporate ownership," Journal of Comparative Economics, Elsevier, vol. 49(1), pages 92-109.
    5. Alessandro, Martin & Cardinale Lagomarsino, Bruno & Scartascini, Carlos & Streb, Jorge & Torrealday, Jerónimo, 2021. "Transparency and Trust in Government. Evidence from a Survey Experiment," World Development, Elsevier, vol. 138(C).
    6. Markus Jung & Mischa Seiter, 2021. "Towards a better understanding on mitigating algorithm aversion in forecasting: an experimental study," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 32(4), pages 495-516, December.
    7. Dak-Adzaklo, Cephas Simon Peter & Wong, Raymond M.K., 2024. "Corporate governance reforms, societal trust, and corporate financial policies," Journal of Corporate Finance, Elsevier, vol. 84(C).
    8. Francisco Gomes & Michael Haliassos & Tarun Ramadorai, 2021. "Household Finance," Journal of Economic Literature, American Economic Association, vol. 59(3), pages 919-1000, September.
    9. Nicola Gennaioli & Rafael La Porta & Florencio Lopez-de-Silanes & Andrei Shleifer, 2022. "Trust and Insurance Contracts," The Review of Financial Studies, Society for Financial Studies, vol. 35(12), pages 5287-5333.
    10. Wagner, Alexander F. & Gibson Brandon, Rajna & Sohn, Matthias & Tanner, Carmen, 2018. "Earnings Management and Managerial Honesty: The Investors’ Perspectives," CEPR Discussion Papers 13207, C.E.P.R. Discussion Papers.
    11. Jin, Ming & Liu, Jinshan & Chen, Zhongfei, 2022. "Impacts of social trust on corporate leverage: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 505-521.
    12. Brice Corgnet, 2023. "An Experimental Test of Algorithmic Dismissals," Working Papers 2302, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    13. David Tsui & Marshall Vance, 2023. "Sorting Effects of Broad-Based Equity Compensation," Management Science, INFORMS, vol. 69(7), pages 4240-4258, July.
    14. Paul Brockman & Sadok El Ghoul & Omrane Guedhami & Ying Zheng, 2022. "Does social trust affect international contracting? Evidence from foreign bond covenants," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 53(6), pages 1011-1044, August.
    15. Knetsch, Andreas & Salzmann, Astrid, 2022. "Societal trust and corporate underinvestment," Global Finance Journal, Elsevier, vol. 54(C).
    16. Füllbrunn, Sascha & Vyrastekova, Jana, 2023. "Does trust break even? A trust-game experiment with negative endowments," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 103(C).
    17. Massimiliano Barbi & Valentina Febo & Giancarlo Giudici, 2023. "Community-level social capital and investment decisions in equity crowdfunding," Small Business Economics, Springer, vol. 61(3), pages 1075-1110, October.
    18. Wang, Zhenshan & Xu, Huilin, 2024. "Trust and inter-regional M&As: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 796-818.
    19. Glaser, Markus & Weber, Martin, 2009. "Which past returns affect trading volume?," Journal of Financial Markets, Elsevier, vol. 12(1), pages 1-31, February.
    20. Georg D. Blind & Stefania Lottanti von Mandach, 2021. "Of pride and prejudice: agent learning under sticky and persistent stereotype," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(2), pages 381-410, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:jumsac:294920. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://jums.academy/en/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.