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Estimating cumulative prospect theory parameters from an international survey

Author

Listed:
  • Marc Oliver Rieger

    (University of Trier, Chair of Banking and Finance)

  • Mei Wang

    (WHU, Otto Beisheim School of Management, Chair of Behavioral Finance)

  • Thorsten Hens

    (Swiss Finance Institute Professor at the Department of Banking and Finance of the University of Zurich
    NHH)

Abstract

We conduct a standardized survey on risk preferences in 53 countries worldwide and estimate cumulative prospect theory parameters from the data. The parameter estimates show that significant differences on the cross-country level are to some extent robust and related to economic and cultural differences. In particular, a closer look on probability weighting underlines gender differences, economic effects, and cultural impact on probability weighting. The data set is a useful starting point for future research that investigates the impact of risk preferences on the market level.

Suggested Citation

  • Marc Oliver Rieger & Mei Wang & Thorsten Hens, 2017. "Estimating cumulative prospect theory parameters from an international survey," Theory and Decision, Springer, vol. 82(4), pages 567-596, April.
    • Handle: RePEc:kap:theord:v:82:y:2017:i:4:d:10.1007_s11238-016-9582-8
    DOI: 10.1007/s11238-016-9582-8
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    References listed on IDEAS

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    Cited by:

    1. Matthew D. Rablen, 2023. "Loss Aversion, Risk Aversion, and the Shape of the Probability Weighting Function," Working Papers 2023013, The University of Sheffield, Department of Economics.
    2. Stefan Graf & Jochen Ruß & Stefan Schelling, 2019. "As you like it: Explaining the popularity of life‐cycle funds with multi cumulative prospect theory," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 22(2), pages 221-238, July.
    3. Lobel, Robert Eugene & Klotzle, Marcelo Cabus & Silva, Paulo Vitor Jordão da Gama & Pinto, Antonio Carlos Figueiredo, 2017. "Teoria do prospecto: Uma análise paramétrica de formas funcionais no Brasil," RAE - Revista de Administração de Empresas, FGV-EAESP Escola de Administração de Empresas de São Paulo (Brazil), vol. 57(5), October.
    4. Giovanni, Domenico De & Lamantia, Fabio & Pezzino, Mario, 2019. "A behavioral model of evolutionary dynamics and optimal regulation of tax evasion," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 79-89.
    5. Shunta Akiyama & Mitsuaki Obara & Yasushi Kawase, 2022. "Optimal design of lottery with cumulative prospect theory," Papers 2209.00822, arXiv.org.
    6. Kim, Duk Gyoo, 2021. "Vaccination lottery," Economics Letters, Elsevier, vol. 208(C).
    7. Rieger, Marc Oliver & Wang, Mei & Huang, Po-Kai & Hsu, Yuan-Lin, 2022. "Survey evidence on core factors of behavioral biases," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 100(C).
    8. Minh Hai Ngo & Marc Oliver Rieger & Shuonan Yuan, 2018. "The Fundamental Equity Premium and Ambiguity Aversion in an International Context," Risks, MDPI, vol. 6(4), pages 1-24, November.
    9. Felix Reichenbach & Martin Walther, 2023. "Financial recommendations on Reddit, stock returns and cumulative prospect theory," Digital Finance, Springer, vol. 5(2), pages 421-448, June.
    10. Ruß, Jochen & Schelling, Stefan, 2021. "Return smoothing in life insurance from a client perspective," Insurance: Mathematics and Economics, Elsevier, vol. 101(PA), pages 91-106.
    11. Chen, Rongxin & Lepori, Gabriele M. & Tai, Chung-Ching & Sung, Ming-Chien, 2022. "Explaining cryptocurrency returns: A prospect theory perspective," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    12. Fang, Yi & Niu, Hui & Lin, Yuen, 2023. "Ex-ante Valuation based on Prospect Theory," MPRA Paper 116386, University Library of Munich, Germany.
    13. Dian Yu & Jianjun Gao & Weiping Wu & Zizhuo Wang, 2022. "Price Interpretability of Prediction Markets: A Convergence Analysis," Papers 2205.08913, arXiv.org, revised Nov 2023.
    14. Pengguang Lu, 2023. "A Simple Model of Herding and Contrarian Behaviour with Biased Informed Traders," Economics Discussion Paper Series 2307, Economics, The University of Manchester, revised Dec 2023.
    15. Illiashenko, Pavlo, 2019. "“Tough Guy” vs. “Cushion” hypothesis: How does individualism affect risk-taking?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 24(C).
    16. Shi, Hai-Liu & Chen, Sheng-Qun & Chen, Lei & Wang, Ying-Ming, 2021. "A neutral cross-efficiency evaluation method based on interval reference points in consideration of bounded rational behavior," European Journal of Operational Research, Elsevier, vol. 290(3), pages 1098-1110.
    17. Rablen, Matthew D., 2019. "Foundations of the Rank-Dependent Probability Weighting Function," IZA Discussion Papers 12701, Institute of Labor Economics (IZA).
    18. Hollstein, Fabian & Sejdiu, Vulnet, 2023. "Probability distortions, collectivism, and international stock prices," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    19. Anuradha M. Annaswamy & Vineet Jagadeesan Nair, 2022. "Human Behavioral Models Using Utility Theory and Prospect Theory," Papers 2210.07322, arXiv.org.
    20. Joo, M. Hashemi & Parhizgari, A.M., 2021. "A behavioral explanation of credit ratings and leverage adjustments," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    21. Yu, Dian & Gao, Jianjun & Wang, Tongyao, 2022. "Betting market equilibrium with heterogeneous beliefs: A prospect theory-based model," European Journal of Operational Research, Elsevier, vol. 298(1), pages 137-151.
    22. Garg, Karan, 2021. "Machines and Markets : Assessing the Impact of Algorithmic Trading on Financial Market Efficiency," Warwick-Monash Economics Student Papers 11, Warwick Monash Economics Student Papers.

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