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
Jack Alan Reynolds
Learn more about PhilPapers
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|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
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.
Citations of this work BETA
No citations found.
Similar books and articles
NG Yew-Kwang (2005). Intergenerational Impartiality: Replacing Discounting by Probability Weighting. [REVIEW] Journal of Agricultural and Environmental Ethics 18 (3):237-257.
David Teira (2006). On the Normative Dimension of St. Petersburg Paradox. Studies in History and Philosophy of Science 37 (2):210-23.
Peter J. Lewis (2010). Probability in Everettian Quantum Mechanics. Manuscrito 33 (1):285--306.
John L. Pollock (1986). The Paradox of the Preface. Philosophy of Science 53 (2):246-258.
Claudio Cioffi-Revilla & Raymond Dacey (1988). The Probability of War in Then-Crises Problem: Modeling New Alternatives to Wright's Solution. Synthese 76 (2):285 - 305.
Rod O'Donnell (1992). Keynes's Weight of Argument and Popper's Paradox of Ideal Evidence. Philosophy of Science 59 (1):44-52.
Theodore Hailperin (2007). Quantifier Probability Logic and the Confirmation Paradox. History and Philosophy of Logic 28 (1):83-100.
Narat Charupat, Richard Deaves, Travis Derouin, Marcelo Klotzle & Peter Miu (2013). Emotional Balance and Probability Weighting. Theory and Decision 75 (1):17-41.
Igor Douven & Timothy Williamson (2006). Generalizing the Lottery Paradox. British Journal for the Philosophy of Science 57 (4):755-779.
Branden Fitelson & James Hawthorne (2010). How Bayesian Confirmation Theory Handles the Paradox of the Ravens. In Ellery Eells & James Fetzer (eds.), The Place of Probability in Science. Springer 247--275.
Raymond S. Nickerson & Ruma Falk (2006). The Exchange Paradox: Probabilistic and Cognitive Analysis of a Psychological Conundrum. Thinking and Reasoning 12 (2):181 – 213.
Martin Smith (2010). A Generalised Lottery Paradox for Infinite Probability Spaces. British Journal for the Philosophy of Science 61 (4):821-831.
Added to index2011-07-13
Total downloads20 ( #130,548 of 1,699,834 )
Recent downloads (6 months)3 ( #206,271 of 1,699,834 )
How can I increase my downloads?