Service interruption on Monday 11 July from 12:30 to 13:00: all the sites of the CCSD (HAL, EpiSciences, SciencesConf, AureHAL) will be inaccessible (network hardware connection).
Skip to Main content Skip to Navigation
Journal articles

Separating curvature and elevation: A parametric probability weighting function

Abstract : This paper presents a preference foundation for a two-parameter family of probability weighting functions. We provide a theoretical link between the well-established notions of probabilistic risk attitudes (i.e., optimism and pessimism) used in economics and the important independent measures for individual behavior used in the psychology literature (i.e., curvature and elevation). One of the parameters in our model measures curvature and represents the diminishing effect of optimism and pessimism when moving away from extreme probabilities 0 and 1. The other parameter measures elevation and represents the relative strength of optimism vs. pessimism. Our empirical analysis indicates that the new weighting function fits elicited probability weights well, and that it can explain differences in the treatment of probabilities for gains compared to that for probabilities of losses.
Complete list of metadata
Contributor : Antoine Haldemann Connect in order to contact the contributor
Submitted on : Thursday, October 21, 2010 - 4:31:11 PM
Last modification on : Saturday, June 25, 2022 - 10:51:25 AM

Links full text




Olivier L'Haridon, Mohammed Abdellaoui, Horst Zank. Separating curvature and elevation: A parametric probability weighting function. Journal of Risk and Uncertainty, Springer Verlag, 2010, 41 (1), pp.39-65. ⟨10.1007/s11166-010-9097-6⟩. ⟨hal-00528381⟩



Record views