Solving the St. Petersburg Paradox in cumulative prospect theory: the right amount of probability weighting
David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jonathan Jenkins Ichikawa
Jack Alan Reynolds
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Theory and Decision 71 (3):325-341 (2011)
Cumulative Prospect Theory (CPT) does not explain the St. Petersburg Paradox. We show that the solutions related to probability weighting proposed to solve this paradox, (Blavatskyy, Management Science 51:677–678, 2005; Rieger and Wang, Economic Theory 28:665–679, 2006) have to cope with limitations. In that framework, CPT fails to accommodate both gambling and insurance behavior. We suggest replacing the weighting functions generally proposed in the literature by another specification which respects the following properties: (1) to solve the paradox, the slope at zero has to be finite. (2) to account for the fourfold pattern of risk attitudes, the probability weighting has to be strong enough.
|Keywords||St. Petersburg Paradox Cumulative prospect theory Gambling Probability weighting|
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References found in this work BETA
Paul Slovic & Sarah Lichtenstein (1968). Relative Importance of Probabilities and Payoffs in Risk Taking. Journal of Experimental Psychology 78 (3p2):1.
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