Back to the St. Petersburg Paradox?
Conventional parameterizations of cumulative prospect theory do not explain the St. Petersburg paradox. To do so, the power coefficient of an individual's utility function must be lower than the power coefficient of an individual's probability weighting function.
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- 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.
- Abdellaoui, Mohammed & Vossman, Frank & Weber, Martin, 2003.
"Choice-Based Elicitation and Decomposition of Decision Weights for Gains and Losses Under Uncertainty,"
CEPR Discussion Papers
3756, C.E.P.R. Discussion Papers.
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- Samuelson, Paul A, 1977. "St. Petersburg Paradoxes: Defanged, Dissected, and Historically Described," Journal of Economic Literature, American Economic Association, vol. 15(1), pages 24-55, March.
- Michael Kilka & Martin Weber, 2001.
"What Determines the Shape of the Probability Weighting Function Under Uncertainty?,"
INFORMS, vol. 47(12), pages 1712-1726, December.
- Kilka, Michael & Weber, Martin, 1998. "What Determines the Shape of the Probability Weighting Function under Uncertainty?," Sonderforschungsbereich 504 Publications 98-11, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
- 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.
- Mohammed Abdellaoui, 2000. "Parameter-Free Elicitation of Utility and Probability Weighting Functions," Management Science, INFORMS, vol. 46(11), pages 1497-1512, November.
- Han Bleichrodt & Jose Luis Pinto, 2000. "A Parameter-Free Elicitation of the Probability Weighting Function in Medical Decision Analysis," Management Science, INFORMS, vol. 46(11), pages 1485-1496, November.
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