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Does Aggregated Returns Disclosure Increase Portfolio Risk-Taking?

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Listed:
  • John Beshears
  • James J. Choi
  • David Laibson
  • Brigitte C. Madrian

Abstract

Many previous experiments have found that participants invest more in risky assets if they (i) see their returns less frequently, (ii) see portfolio-level returns (rather than individual asset-by-asset returns), or (iii) see long-horizon (rather than one-year) historical asset class return distributions. In contrast, we find that such information aggregation treatments do not increase equity allocations in an experiment where—unlike previous experiments—participants invest in real mutual funds over the course of one year. In a follow-up experiment, we start with the classic Gneezy and Potters (1997) experimental design and modify it step-by-step to move closer to the design of our first experiment. Using this identification strategy, we show that previously documented aggregation effects are not robust to (i) changes in the distribution of the risky asset’s returns and (ii) the introduction of a multi-day delay between the initial portfolio choice and the realization of returns.

Suggested Citation

  • John Beshears & James J. Choi & David Laibson & Brigitte C. Madrian, 2011. "Does Aggregated Returns Disclosure Increase Portfolio Risk-Taking?," NBER Working Papers 16868, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:16868
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    8. Daniel Gottlieb & Olivia S. Mitchell, 2020. "Narrow Framing and Long‐Term Care Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 87(4), pages 861-893, December.
    9. Borsboom, Charlotte & Janssen, Dirk-Jan & Strucks, Markus & Zeisberger, Stefan, 2022. "History matters: How short-term price charts hurt investment performance," Journal of Banking & Finance, Elsevier, vol. 134(C).
    10. Gerhard, Patrick & Hoffmann, Arvid O.I. & Post, Thomas, 2017. "Past performance framing and investors’ belief updating: Is seeing long-term returns always associated with smaller belief updates?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 15(C), pages 38-51.
    11. van der Heijden, Eline & Klein, Tobias J. & Müller, Wieland & Potters, Jan, 2012. "Framing effects and impatience: Evidence from a large scale experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 84(2), pages 701-711.
    12. Asen Ivanov, 2018. "Optimal Default Policies in Defined Contribution Pension Plans when Employees are Biased," Working Papers 858, Queen Mary University of London, School of Economics and Finance.
    13. Beshears, John & Kosowsky, Harry, 2020. "Nudging: Progress to date and future directions," Organizational Behavior and Human Decision Processes, Elsevier, vol. 161(S), pages 3-19.
    14. Sewaid, Ahmed & Parker, Simon C. & Kaakeh, Abdulkader, 2021. "Explaining serial crowdfunders' dynamic fundraising performance," Journal of Business Venturing, Elsevier, vol. 36(4).
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    16. Immanuel Lampe & Daniel Würtenberger, 2019. "Loss Aversion And The Demand For Index Insurance," Working Papers on Finance 1907, University of St. Gallen, School of Finance.
    17. Matthew Lee & Arzi Adbi & Jasjit Singh, 2020. "Categorical cognition and outcome efficiency in impact investing decisions," Strategic Management Journal, Wiley Blackwell, vol. 41(1), pages 86-107, January.
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    More about this item

    JEL classification:

    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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