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Randomized strategies and prospect theory in a dynamic context

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  • Henderson, Vicky
  • Hobson, David
  • Tse, Alex S.L.

Abstract

When prospect theory (PT) is applied in a dynamic context, the probability weighting component brings new challenges. We study PT agents facing optimal timing decisions and consider the impact of allowing them to follow randomized strategies. In a continuous-time model of gambling and optimal stopping, Ebert and Strack (2015) show that a naive PT investor with access only to pure strategies never stops. We show that allowing randomization can significantly alter the predictions of their model, and can result in voluntary cessation of gambling.

Suggested Citation

  • Henderson, Vicky & Hobson, David & Tse, Alex S.L., 2017. "Randomized strategies and prospect theory in a dynamic context," Journal of Economic Theory, Elsevier, vol. 168(C), pages 287-300.
    • Handle: RePEc:eee:jetheo:v:168:y:2017:i:c:p:287-300
    DOI: 10.1016/j.jet.2017.01.003
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    References listed on IDEAS

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    7. Nicholas Barberis, 2012. "A Model of Casino Gambling," Management Science, INFORMS, vol. 58(1), pages 35-51, January.
    8. Amit Kothiyal & Vitalie Spinu & Peter Wakker, 2011. "Prospect theory for continuous distributions: A preference foundation," Journal of Risk and Uncertainty, Springer, vol. 42(3), pages 195-210, June.
    9. Zuo Quan Xu & Xun Yu Zhou, 2011. "Optimal stopping under probability distortion," Papers 1103.1755, arXiv.org, revised Feb 2013.
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    Citations

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    Cited by:

    1. He, Xue Dong & Hu, Sang & Obłój, Jan & Zhou, Xun Yu, 2019. "Two explicit Skorokhod embeddings for simple symmetric random walk," Stochastic Processes and their Applications, Elsevier, vol. 129(9), pages 3431-3445.
    2. Vicky Henderson & Jonathan Muscat, 2020. "Partial liquidation under reference-dependent preferences," Finance and Stochastics, Springer, vol. 24(2), pages 335-357, April.
    3. Sarah Auster & Christian Kellner, 2023. "Timing Decisions Under Model Uncertainty," CRC TR 224 Discussion Paper Series crctr224_2023_460, University of Bonn and University of Mannheim, Germany.
    4. Markus Dertwinkel-Kalt & Jonas Frey, 2020. "Optimal Stopping in a Dynamic Salience Model," CESifo Working Paper Series 8496, CESifo.
    5. Sarah Auster & Christian Kellner, 2023. "Timing Decisions under Model Uncertainty," ECONtribute Discussion Papers Series 252, University of Bonn and University of Cologne, Germany.
    6. Henderson, Vicky & Hobson, David & Tse, Alex S.L., 2018. "Probability weighting, stop-loss and the disposition effect," Journal of Economic Theory, Elsevier, vol. 178(C), pages 360-397.
    7. Sang Hu & Jan Obloj & Xun Yu Zhou, 2021. "When to Quit Gambling, if You Must!," Papers 2102.03157, arXiv.org.

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    More about this item

    Keywords

    Behavioral economics; Prospect theory; Probability weighting; Randomized strategies;
    All these keywords.

    JEL classification:

    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles

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