Cumulative prospect theory and the St. Petersburg paradox

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Prospect theory, behavioral theory, and the threat-rigidity thesis: Combinative effects on organizational decisions to divest formerly acquired units (2007, background): “... in comparison to a reference point, (2) the utility function is an S-shaped curve, concave for gains and convex for losses, suggesting losses loom larger than corresponding gains, (3) individuals show tendencies toward risk aversion when facing gains and toward risk seeking when facing losses (t”
OPTIMAL INSURANCE DESIGN UNDER RANK‐DEPENDENT EXPECTED UTILITY (2015, unknown): “As noted by Rieger and Wang (2006) and by Ingersoll (2008), this probability distortion function is increasing and inverse-S shaped for any a ∈ (0.279, 1).”
Risk Preferences Around the World (2015, unknown): “(See Rieger and Wang 2006 for a summary of typical parameter values estimated from laboratory experiments.)”
Choice Under Uncertainty: Evidence from Ethiopia, India and Uganda (2010, unknown): “The Prelec (1998) function leads to estimates that are mid-way between those obtained with the Tversky and Kahneman (1992) function and EUT, and the Rieger and Wang (2006) function leads to estimates that are closer to EUT.”
Prospect theory for continuous distributions (2008, methodology): “(The function becomes even non-monotone for very small values, compare [10].”