Solving the St. Petersburg Paradox in cumulative prospect theory: the right amount of probability weighting
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DOI: 10.1007/s11238-009-9191-x
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Cited by:
- Martín Egozcue & Luis Fuentes García & Ričardas Zitikis, 2023. "The Slicing Method: Determining Insensitivity Regions of Probability Weighting Functions," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1369-1402, April.
- Martina Nardon & Paolo Pianca, 2019. "Behavioral premium principles," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(1), pages 229-257, June.
- Martina Nardon & Paolo Pianca, 2015. "Probability weighting functions," Working Papers 2015:29, Department of Economics, University of Venice "Ca' Foscari".
- Kim Kaivanto & Eike Kroll, 2014. "Alternation bias and reduction in St. Petersburg gambles," Working Papers 65600286, Lancaster University Management School, Economics Department.
- Martina Nardon & Paolo Pianca, 2019. "European option pricing under cumulative prospect theory with constant relative sensitivity probability weighting functions," Computational Management Science, Springer, vol. 16(1), pages 249-274, February.
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Keywords
St. Petersburg Paradox; Cumulative prospect theory; Gambling; Probability weighting;All these keywords.
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