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Composite Prospect Theory: A proposal to combine ‘prospect theory’ and ‘cumulative prospect theory’

Author

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  • Ali al-Nowaihi
  • Sanjit Dhami

Abstract

Evidence shows that (i) people overweight low probabilities and underweight high probabilities, but (ii) ignore events of extremely low probability and treat extremely high probability events as certain. The main alternative decision theories, rank dependent utility (RDU) and cumulative prospect theory (CP) incorporate (i) but not (ii). By contrast, prospect theory (PT) addresses (i) and (ii) by proposing an editing phase that eliminates extremely low probability events, followed by a decision phase that only makes a choice from among the remaining alternatives. However, PT allows for the choice of stochastically dominated options, even when such dominance is obvious. We propose to combine PT and CP into composite cumulative prospect theory (CCP). CCP combines the editing and decision phases of PT into one phase and does not allow for the choice of stochastically dominated options. This, we believe, provides the best available alternative among decision theories of risk at the moment. As illustrative examples, we also show that CCP allows us to resolve three paradoxes: the insurance paradox, the Becker paradox and the St. Petersburg paradox.

Suggested Citation

  • Ali al-Nowaihi & Sanjit Dhami, 2010. "Composite Prospect Theory: A proposal to combine ‘prospect theory’ and ‘cumulative prospect theory’," Discussion Papers in Economics 10/11, Division of Economics, School of Business, University of Leicester.
    • Handle: RePEc:lec:leecon:10/11
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    References listed on IDEAS

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    Cited by:

    1. Antonio Nicita & Matteo Rizzolli, 2014. "In Dubio Pro Reo. Behavioral Explanations of Pro-defendant Bias in Procedures," CESifo Economic Studies, CESifo Group, vol. 60(3), pages 554-580.
    2. Ali al-Nowaihi & Sanjit Dhami, 2010. "The Behavioral Economics of Insurance," Discussion Papers in Economics 10/12, Division of Economics, School of Business, University of Leicester, revised Apr 2010.
    3. Ali al-Nowaihi & Sanjit Dhami, 2010. "Probability Weighting Functions," Discussion Papers in Economics 10/10, Division of Economics, School of Business, University of Leicester.
    4. Sanjit Dhami & Ali al-Nowaihi, 2010. "The Behavioral Economics of Crime and Punishment," Discussion Papers in Economics 10/14, Division of Economics, School of Business, University of Leicester, revised Jul 2010.
    5. Rogelio Ladrón de Guevara Cortés & Alina Gómez Mejía & Víctor Peña Vargas & Rosa Marina Madrid Paredones, 2020. "Influencia del nivel de avance educativo y el género en la toma de decisiones financieras: una aproximación desde la Prospect Theory," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, vol. 12(1), pages 19-54, June.
    6. Beinhocker, Eric & Dhami, Sanjit, 2019. "The Behavioral Foundations of New Economic Thinking," INET Oxford Working Papers 2019-13, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    7. Martina Nardon & Paolo Pianca, 2015. "Probability weighting functions," Working Papers 2015:29, Department of Economics, University of Venice "Ca' Foscari".

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    More about this item

    Keywords

    Decision making under risk; Composite Prelec probability weighting functions; Composite cumulative prospect theory; Composite rank dependent utility theory; Insurance; St. Petersburg paradox; Becker.s paradox;
    All these keywords.

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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