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Automatic versus manual investing: Role of past performance

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  • Kaawach, Said
  • Kowalewski, Oskar
  • Talavera, Oleksandr

Abstract

Using unique data from a leading peer-to-peer (P2P) lending platform, we investigate the link between past investment performance and choice of auto-investing tool. Our results suggest that investors who experience fewer defaults in the manual mode are more inclined to switch to automatic investment. Several factors account for this relationship, including investor inattention, decision speed, investment delegation, and experience. Regarding the latter, our results suggest that experienced investors are more likely to continue self-directed bidding, even if they have faced defaults in manual investments in the past. These investors may attribute their previous mistakes to their own actions rather than the limitations of the self-directed bids. Our results are robust to alternative specifications.

Suggested Citation

  • Kaawach, Said & Kowalewski, Oskar & Talavera, Oleksandr, 2024. "Automatic versus manual investing: Role of past performance," Journal of Financial Stability, Elsevier, vol. 74(C).
    • Handle: RePEc:eee:finsta:v:74:y:2024:i:c:s1572308924001049
    DOI: 10.1016/j.jfs.2024.101319
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    as
    1. Neal M. Stoughton & Youchang Wu & Josef Zechner, 2011. "Intermediated Investment Management," Journal of Finance, American Finance Association, vol. 66(3), pages 947-980, June.
    2. Gervais, Simon & Odean, Terrance, 2001. "Learning to be Overconfident," The Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 1-27.
    3. Duan, Yang & Hsieh, Tien-Shih & Wang, Ray R. & Wang, Zhihong, 2020. "Entrepreneurs' facial trustworthiness, gender, and crowdfunding success," Journal of Corporate Finance, Elsevier, vol. 64(C).
    4. Chiara Longoni & Andrea Bonezzi & Carey K Morewedge, 2019. "Resistance to Medical Artificial Intelligence," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 46(4), pages 629-650.
    5. Terrance Odean., 1996. "Volume, Volatility, Price and Profit When All Trader Are Above Average," Research Program in Finance Working Papers RPF-266, University of California at Berkeley.
    6. D’Hondt, Catherine & De Winne, Rudy & Ghysels, Eric & Raymond, Steve, 2020. "Artificial Intelligence Alter Egos: Who might benefit from robo-investing?," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 278-299.
    7. 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.
    8. 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.
    9. Li Liao & Zhengwei Wang & Jia Xiang & Hongjun Yan & Jun Yang & LaurenCohen, 2021. "User Interface and Firsthand Experience in Retail Investing," The Review of Financial Studies, Society for Financial Studies, vol. 34(9), pages 4486-4523.
    10. Chen, Xiao & Huang, Bihong & Ye, Dezhu, 2020. "Gender gap in peer-to-peer lending: Evidence from China," Journal of Banking & Finance, Elsevier, vol. 112(C).
    11. Caglayan, Mustafa & Talavera, Oleksandr & Zhang, Wei, 2021. "Herding behaviour in P2P lending markets," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 27-41.
    12. 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.
    13. Cheng, We Geng & Leite, Rodrigo de Oliveira & Caldieraro, Fabio, 2022. "Financial contagion in internet lending platforms: Who pays the price?," Finance Research Letters, Elsevier, vol. 45(C).
    14. Martin G. Kocher & Julius Pahlke & Stefan T. Trautmann, 2013. "Tempus Fugit : Time Pressure in Risky Decisions," Management Science, INFORMS, vol. 59(10), pages 2380-2391, October.
    15. Caglayan, Mustafa & Pham, Tho & Talavera, Oleksandr & Xiong, Xiong, 2020. "Asset mispricing in peer-to-peer loan secondary markets," Journal of Corporate Finance, Elsevier, vol. 65(C).
    16. D'Acunto, Francesco & Ghosh, Pulak & Jain, Rajiv & Rossi, Alberto G., 2022. "How costly are cultural biases?," LawFin Working Paper Series 34, Goethe University, Center for Advanced Studies on the Foundations of Law and Finance (LawFin).
    17. David Easley & David Michayluk & Maureen O’Hara and Tālis & J Putniņš, 2021. "The Active World of Passive Investing [Mutual fund’s R2 as predictor of performance]," Review of Finance, European Finance Association, vol. 25(5), pages 1433-1471.
    18. Logg, Jennifer M. & Minson, Julia A. & Moore, Don A., 2019. "Algorithm appreciation: People prefer algorithmic to human judgment," Organizational Behavior and Human Decision Processes, Elsevier, vol. 151(C), pages 90-103.
    19. 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.
    20. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
    21. Nicolae Gârleanu & Lasse Heje Pedersen, 2022. "Active and Passive Investing: Understanding Samuelson’s Dictum [A noisy rational expectations equilibrium for multi-asset securities markets]," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 12(2), pages 389-446.
    22. Jon Kleinberg & Himabindu Lakkaraju & Jure Leskovec & Jens Ludwig & Sendhil Mullainathan, 2018. "Human Decisions and Machine Predictions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(1), pages 237-293.
    23. Gogoll, Jan & Uhl, Matthias, 2018. "Rage against the machine: Automation in the moral domain," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 74(C), pages 97-103.
    24. Antonio Gargano & Alberto G. Rossi, 2024. "Goal Setting and Saving in the FinTech Era," Journal of Finance, American Finance Association, vol. 79(3), pages 1931-1976, June.
    25. repec:bla:jfinan:v:53:y:1998:i:6:p:1887-1934 is not listed on IDEAS
    26. Robert F. Stambaugh, 2014. "Presidential Address: Investment Noise and Trends," Journal of Finance, American Finance Association, vol. 69(4), pages 1415-1453, August.
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    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G40 - Financial Economics - - Behavioral Finance - - - General
    • G51 - Financial Economics - - Household Finance - - - Household Savings, Borrowing, Debt, and Wealth
    • D90 - Microeconomics - - Micro-Based Behavioral Economics - - - General

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