Investigation of stochastic preference theory using experimental data

Carbone, Enrica

doi:10.1016/s0165-1765(97)00244-9

Cited by 41 publications

(24 citation statements)

References 4 publications

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“…A far less common procedure is to select one or two decision theories and to estimate them in conjunction with several models of stochastic choices (e.g. Carbone, 1997;Loomes et al, 2002). As Hey (2005) points out, the selection of a model of stochastic choice is generally considered to be of secondary importance with far more emphasis put on the selection of a decision theory.…”

Section: Models Of Stochastic Choice and Decision Theories: Why Both mentioning

confidence: 99%

Models of stochastic choice and decision theories: why both are important for analyzing decisions

Blavatskyy

Pogrebna

2009

J of Applied Econometrics

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We select a menu of seven popular decision theories and embed each theory in five models of stochastic choice, including tremble, Fechner and random utility model. We find that the estimated parameters of decision theories differ significantly when theories are combined with different models. Depending on the selected model of stochastic choice we obtain different rankings of decision theories with regard to their goodness of fit to the data. The fit of all analyzed decision theories improves significantly when they are embedded in a Fechner model of heteroscedastic truncated errors or a random utility model. Copyright © 2009 John Wiley & Sons, Ltd.

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Section: Models Of Stochastic Choice and Decision Theories: Why Both mentioning

confidence: 99%

Models of stochastic choice and decision theories: why both are important for analyzing decisions

Blavatskyy

Pogrebna

2009

J of Applied Econometrics

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“…This approach is sometimes called the ''random utility'' model. Assuming that CPT parameters change from choice to choice, it follows that a person should satisfy stochastic dominance 100% of the time (Carbone, 1997;Loomes & Sugden, 1995). This follows because under any parameters, CPT always satisfies stochastic dominance.…”

Section: Random Utilitymentioning

confidence: 99%

Tests of rank-dependent utility and cumulative prospect theory in gambles represented by natural frequencies: Effects of format, event framing, and branch splitting

Birnbaum

2004

Organizational Behavior and Human Decision Processes

134

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Four studies with 3440 participants investigated four new paradoxes that refute rank-dependent utility and cumulative prospect theories of risky decision making. All four paradoxes can be interpreted as violations of coalescing, the assumption that branches leading to the same consequence can be combined by adding their probabilities. These studies explored if there is some format in which coalescing and cumulative prospect theory would be satisfied. Three variables were manipulated: probability format, branch splitting, and event-framing. Probability was displayed via text, pie charts, natural frequencies, and lists of equally likely consequences. Probability format and event framing had minimal effects, but branch splitting had large effects. In all 12 conditions of format and framing, splitting created majority violations of stochastic dominance and a second round of splitting reversed preferences, restoring majority satisfaction of stochastic dominance. Two cumulative independence properties were violated in 47 of 48 new tests. BirnbaumÕs TAX model, in which the relative weight of each probability-consequence branch depends on probability and rank of its consequence, correctly predicted the main trends. In this model, splitting the branch with the lowest consequence can make a gamble worse, and splitting the branch with the highest consequence can make a gamble better.

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“…Carbone and Hey (1994), Hey and Orme (1994), Orme (1995), Hey (1995), Hey and Carbone (1995), Carbone and Hey (1995), Loomes and Sugden (1995), Carbone (1997), Carbone and Hey (2000), Loomes et al (2002) and Stott (2006), we refer to Harrison andRutstrom (2008) andde Palma et al (2008) for an overview), several shortcomings in the evaluation of the likelihood function (3.7) can affect our Prospect Theory estimates (see Cramer (1986), Liu and Mahmassani (2000), Rabe-Hersketh and Everitt (2004) and Gould et al (2006)) if these shortcomings are correlated with θ k .…”

Section: Mean Of Estimatesmentioning

confidence: 99%

Taming Models of Prospect Theory in the Wild? Estimation of Vlcek and Hens (2011)

2016

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Abstract. Shortcomings revealed by experimental and theoretical researchers such as Allais (1953), Rabin (2000) and Rabin and Thaler (2001) that put the classical expected utility paradigm von Neumann and Morgenstern (1947) into question, led to the proposition of alternative and generalized utility functions, that intend to improve descriptive accuracy. The perhaps best known among those alternative preference theories, that has attracted much popularity among economists, is the so called Prospect Theory by Kahneman and Tversky (1979) and Tversky and Kahneman (1992). Its distinctive features, governed by its set of risk parameters such as risk sensitivity, loss aversion and decision weights, stimulated a series of economic and financial models that build on the previously estimated parameter values by Tversky and Kahneman (1992) to analyze and explain various empirical phenomena for which expected utility doesn't seem to offer a satisfying rationale. In this paper, after providing a brief overview of the relevant literature, we take a closer look at one of those papers, the trading model of Vlcek and Hens (2011) and analyze its implications on Prospect Theory parameters using an adopted maximum likelihood approach for a dataset of 656 individual investors from a large German discount brokerage firm. We find evidence that investors in our dataset are moderately averse to large losses and display high risk sensitivity, supporting the main assumptions of Prospect Theory.

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Investigation of stochastic preference theory using experimental data

Cited by 41 publications

References 4 publications

Models of stochastic choice and decision theories: why both are important for analyzing decisions

Models of stochastic choice and decision theories: why both are important for analyzing decisions

Tests of rank-dependent utility and cumulative prospect theory in gambles represented by natural frequencies: Effects of format, event framing, and branch splitting

Taming Models of Prospect Theory in the Wild? Estimation of Vlcek and Hens (2011)

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