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Which Optimal Design For LLDAs?

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  • Marie Pfiffelmann

    () (Laboratoire de Recherche en Gestion et Economie, Université Louis Pasteur)

Abstract

Lottery-linked deposit accounts are financial assets that provide an interest rate determined by a lottery. The aim of this study is to determine the optimal design of these financial assets (under cumulative prospect theory (CPT) framework). We underline that the weighting functions usually specified in the literature should be re-modeled if we want to apply CPT to finance. We propose to replace them by another functional form that preserves the main characteristics of the inverse S-shape specification, but whose slope at zero is finite. The optimal structure of payments obtained is consistent with the conclusions of behavioral portfolio theory (2000).

Suggested Citation

  • Marie Pfiffelmann, 2006. "Which Optimal Design For LLDAs?," Working Papers of LaRGE Research Center 2006-06, Laboratoire de Recherche en Gestion et Economie (LaRGE), Université de Strasbourg.
  • Handle: RePEc:lar:wpaper:2006-06
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    File URL: http://ifs.u-strasbg.fr/large/publications/2006/2006-06.pdf
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    References listed on IDEAS

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    1. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    2. Richard H. Thaler, 2008. "Mental Accounting and Consumer Choice," Marketing Science, INFORMS, vol. 27(1), pages 15-25, 01-02.
    3. David Hirshleifer, 2001. "Investor Psychology and Asset Pricing," Journal of Finance, American Finance Association, vol. 56(4), pages 1533-1597, August.
    4. Camerer, Colin F & Ho, Teck-Hua, 1994. "Violations of the Betweenness Axiom and Nonlinearity in Probability," Journal of Risk and Uncertainty, Springer, vol. 8(2), pages 167-196, March.
    5. Mauro Guillén & Adrian Tschoegl, 2002. "Banking on Gambling: Banks and Lottery-Linked Deposit Accounts," Journal of Financial Services Research, Springer;Western Finance Association, vol. 21(3), pages 219-231, June.
    6. Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-291, March.
    7. Clotfelter, Charles T & Cook, Philip J, 1990. "On the Economics of State Lotteries," Journal of Economic Perspectives, American Economic Association, vol. 4(4), pages 105-119, Fall.
    8. Shefrin, Hersh & Statman, Meir, 2000. "Behavioral Portfolio Theory," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(02), pages 127-151, June.
    9. Enrico Giorgi & Thorsten Hens, 2006. "Making prospect theory fit for finance," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 20(3), pages 339-360, September.
    10. Marie Pfiffelmann, 2007. "How to solve the St Petersburg Paradox in Rank-Dependent Models ?," Working Papers of LaRGE Research Center 2007-08, Laboratoire de Recherche en Gestion et Economie (LaRGE), Université de Strasbourg.
    11. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
    12. Kobberling, Veronika & Wakker, Peter P., 2005. "An index of loss aversion," Journal of Economic Theory, Elsevier, vol. 122(1), pages 119-131, May.
    13. Michael Kilka & Martin Weber, 2001. "What Determines the Shape of the Probability Weighting Function Under Uncertainty?," Management Science, INFORMS, vol. 47(12), pages 1712-1726, December.
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    Cited by:

    1. Rania HENTATI & Jean-Luc PRIGENT, "undated". "Structured Portfolio Analysis under SharpeOmega Ratio," EcoMod2010 259600073, EcoMod.
    2. Marie Pfiffelmann, 2007. "How to solve the St Petersburg Paradox in Rank-Dependent Models ?," Working Papers of LaRGE Research Center 2007-08, Laboratoire de Recherche en Gestion et Economie (LaRGE), Université de Strasbourg.

    More about this item

    Keywords

    Lottery-Linked-Deposit Account; Cumulative Prospect Theory; Design optimal; Probability Weighting.;

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

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