Cumulative prospect theory's functional menagerie

By H. Stott. 2006

462 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Economics and Econometrics, General Decision Sciences

View Paper: https://www.semanticscholar.org/paper/12385d13537e2407352bf8873f0efe2f06c96e08

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Citations in the corpus

Measuring Loss Aversion under Ambiguity: A Method to Make Prospect Theory Completely Observable (2016, unknown): “Reversal rates around one third are common in the literature (Stott 2006).”
Cognitive Imprecision and Small-Stakes Risk Aversion (2018, unknown): “A standard approach in econometric tests of prospect theory (as reviewed in Stott, 2006) is to add a random term to the valuation of each risky prospect that would be specified by Kahneman and Tversky.”
A Reconsideration of Gender Differences in Risk Attitudes (2016, unknown): “Assuming that the error follows a logistic distribution defines the logit specification, used for instance by Stott (2006). The underlying mechanism is the same as in probit, the only difference being that here the probability of choosing R is evaluated using the cumulative distribution function of ”
The trade-off between money and travel time: A test of the theory of reference-dependent preferences (2008, background): “A recent survey of functional forms ( Stott 2006 ) suggests the power function as the best empirical formulation for the value function.”
Joint measurement of risk aversion, prudence, and temperance (2014, unknown): “To this end, we also conduct a basic Maximum-Likelihood estimation, comparable to that of Tversky and Kahneman (1992) or Stott (2006). So far, prospect theory has not been fit to higher-order risk data.”
Measuring the time stability of Prospect Theory preferences (2010, unknown): “17 A comprehensive overview of the gain domain is presented by Stott (2006), Table 5.”
Models of best–worst choice and ranking among multiattribute options (profiles) (2012, methodology): “The experimental design, D(P ), was a Street and Burgess (2007) design for testing the main effects of the attributes.”
Hierarchical Bayesian parameter estimation for cumulative prospect theory (2011, methodology): “Themost common approach is single-subjectmaximum likelihood estimation (MLE; e.g., Harrison &Rutström, 2009; Harless & Camerer, 1994; Rieskamp, 2008; Stott, 2006; for a tutorial see Myung, 2003).”
Exploring Higher-Order Risk Effects (2010, background): “Most of these are analyzed in Stott (2006).”
The affect gap in risky choice : Affect-rich outcomes attenuate attention to probability information (2014, background): “9 Previous investigations considered mainly choice rules with either a constant error probability or an error that is dependent on the ratio of the attractiveness of the options (e.g., Blavatskyy & Pogrebna, 2010; Rieskamp, 2008; Stott, 2006).”
Monetary incentives in the loss domain and behavior toward risk: An experimental comparison of three reward schemes including real losses (2011, result): “4) show a level of risk aversion that is consistent with that found in previous similar studies (e.g. Tversky and Kahneman 1992; Abdellaoui 2000; Stott 2006).”
Risk and Rationality: Uncovering Heterogeneity in Probability Distortion (2009, background): “v(x) =  x if x ≥ 0 −(−x) otherwise, which can be conveniently interpreted and has turned out to be the best compromise between parsimony and goodness of fit in the context of prospect theory (Stott, 2006).”
A tractable method to measure utility and loss aversion under prospect theory (2008, background): “The reliability in the repeat of the third iteration was comparable to the reliability observed in previous studies (for an overview see Table 1 in Stott (2006). In the repeat of the first iteration the reliability was much better, which is not surprising given that these involved choices for which ”
Consistency of Higher Order Risk Preferences (2012, unknown): “To the best of our knowledge, other set-ups, as described in Stott (2006), have not been examined with regards to higher order risk preferences.”