Results 11 to 20 of about 1,248,041 (248)
Second-best probability weighting [PDF]
Games and Economic Behavior, 2023 Non-linear probability weighting is an integral part of descriptive theories of choice under risk such as prospect theory. But why do these objective errors in information processing exist? Should we try to help individuals overcome their mistake of overweighting small and underweighting large probabilities?
Herold, Florian, Netzer, Nick
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Insurance and Probability Weighting Functions [PDF]
SSRN Electronic Journal, 2006 Evidence shows that (i) people overweight low probabilities and underweight high probabilities, but (ii) ignore events of extremely low probability and treat extremely high probability events as certain. Decision models, such as rank dependent utility (RDU) and cumulative prospect theory (CP), use probability weighting functions.
Ali al-Nowaihi, Sanjit Dhami
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Psychophysics of the Probability Weighting Function [PDF]
SSRN Electronic Journal, 2011 A probability weighting function w(p) for an objective probability p in decision under risk plays a pivotal role in Kahneman-Tversky's prospect theory. Although recent studies in econophysics and neuroeconomics widely utilized probability weighting functions, psychophysical foundations of the probability weighting functions have been unknown.
Takahashi, Taiki, Taiki Takahashi
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Probability Weighting Functions [PDF]
SSRN Electronic Journal, 2015 Cumulative prospect theory (CPT) has been proposed as an alternative to expected utility theory to explain irregular behavior by economic agents. CPT comprises two key transformations: one of outcome values and the other of objective probabilities. Risk attitudes are derived from the shapes of these transformations as well as their interaction.
Martina Nardon, Paolo Pianca
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Probability weighting and L-moments
European Journal of Operational Research, 2016 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Blavatskyy, P.
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Inverse probability weighting [PDF]
BMJ, 2016 Statistical analysis usually treats all observations as equally important. In some circumstances, however, it is appropriate to vary the weight given to different observations. Well known examples are in meta-analysis, where the inverse variance (precision) weight given to each contributing study varies, and in the analysis of clustered data.1 ...
Mansournia, M, Altman, D
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Curvature of the Probability Weighting Function [PDF]
Management Science, 1996 When individuals choose among risky alternatives, the psychological weight attached to an outcome may not correspond to the probability of that outcome. In rank-dependent utility theories, including prospect theory, the probability weighting function permits probabilities to be weighted nonlinearly. Previous empirical studies of the weighting function
George Wu, Richard Gonzalez
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Gender, Financial Risk, and Probability Weights [PDF]
Theory and Decision, 2006 Economics Working Paper Series, 04 ...
Helga Fehr-Duda +2 more
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Frontiers in Psychology, 2019 Our understanding of the decisions made under scenarios where both descriptive and experience-based information are available is very limited. Underweighting of small probabilities was observed in the gain domain when both description and experience were
Shruti Goyal, Krishna P. Miyapuram
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Fitness-maximizers employ pessimistic probability weighting for decisions under risk
Evolutionary Human Sciences, 2020 The standard theory of rationality posits that agents order preferences according to average utilities associated with different choices. Expected utility theory has repeatedly failed as a predictive theory, as reflected in a growing literature in ...
Michael Holton Price +1 more
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