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52
Prospect theory: An analysis of decisions under risk
 Econometrica
, 1979
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Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at
Weighing Risk and Uncertainty
, 1995
"... Decision theory distinguishes between risky prospects, where the probabilities associated with the possible outcomes are assumed to be known, and uncertain prospects, where these probabilities are not assumed to be known. Studies of choice between risky prospects have suggested a nonlinear transform ..."
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Cited by 187 (10 self)
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Decision theory distinguishes between risky prospects, where the probabilities associated with the possible outcomes are assumed to be known, and uncertain prospects, where these probabilities are not assumed to be known. Studies of choice between risky prospects have suggested a nonlinear transformation of the probability scale that overweights low probabilities and underweights moderate and high probabilities. The present article extends this notion from risk to uncertainty by invoking the principle of bounded subadditivity: An event has greater impact when it turns impossibility into possibility, or possibility into certainty, than when it merely makes a possibility more or less likely. A series of studies provides support for this principle in decision under both risk and uncertainty and shows that people are less sensitive to uncertainty than to risk. Finally, the article discusses the relationship between probability judgments and decision weights and distinguishes relative sensitivity from ambiguity aversion.
CHOICEBASED ELICITATION AND DECOMPOSITION OF DECISION WEIGHTS FOR GAINS AND LOSSES UNDER UNCERTAINTY
, 2003
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On the Intuition of RankDependent Utility
, 2000
"... Among the most popular models for decision under risk and uncertainty are the rankdependent models, introduced by Quiggin and Schmeidler. Central concepts in these models are rankdependence and comonotonicity. It has been suggested in the literature that these concepts are technical tools that hav ..."
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Cited by 51 (0 self)
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Among the most popular models for decision under risk and uncertainty are the rankdependent models, introduced by Quiggin and Schmeidler. Central concepts in these models are rankdependence and comonotonicity. It has been suggested in the literature that these concepts are technical tools that have no intuitive or empirical content. This paper describes such contents. As
Small worlds: Modeling attitudes toward sources of uncertainty
 Journal of Economic Theory
"... Abstract We introduce the concept of a conditional small world event domainan extension of Savage's [33] notion of a 'small world'as a selfcontained collection of comparable events. Under weak behavioral conditions we demonstrate probabilistic sophistication in any small world eve ..."
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Abstract We introduce the concept of a conditional small world event domainan extension of Savage's [33] notion of a 'small world'as a selfcontained collection of comparable events. Under weak behavioral conditions we demonstrate probabilistic sophistication in any small world event domain without relying on monotonicity or continuity. Probabilistic sophistication within, though not necessarily across, small worlds provides a foundation for modeling a decision maker that has sourcedependent risk attitudes. This also helps formalize the idea of source preference and suggests an interpretation of ambiguity aversion, often associated with Ellsbergtype behavior, in terms of comparative risk aversion across small worlds.
On the Composition of Risk Preference and Belief
, 2004
"... Prospect theory assumes nonadditive decision weights for preferences over risky gambles. Such decision weights generalize additive probabilities. This article proposes a decomposition of decision weights into a component reflecting risk attitude and a new component depending on belief. The decomposi ..."
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Prospect theory assumes nonadditive decision weights for preferences over risky gambles. Such decision weights generalize additive probabilities. This article proposes a decomposition of decision weights into a component reflecting risk attitude and a new component depending on belief. The decomposition is based on an observable preference condition and does not use other empirical primitives such as statements of judged probabilities. The preference condition is confirmed by most of the experimental findings in the literature. The implied properties of the belief component suggest that, besides the oftenstudied ambiguity aversion (a motivational factor reflecting a general aversion to unknown probabilities), perceptual and cognitive limitations play a role: It is harder to distinguish among various levels of likelihood, and to process them differently, when probabilities are unknown than when they are known.
Causes of Ambiguity Aversion: Known versus Unknown Preferences
, 2007
"... with parts of the study conducted at the University of Maastricht. Ambiguity aversion appears to have subtle psychological causes. Curley, Yates, and Abrams found that the fear of negative evaluation by others (FNE) increases ambiguity aversion. This paper introduces a design where preferences can b ..."
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with parts of the study conducted at the University of Maastricht. Ambiguity aversion appears to have subtle psychological causes. Curley, Yates, and Abrams found that the fear of negative evaluation by others (FNE) increases ambiguity aversion. This paper introduces a design where preferences can be private information of individuals, so that FNE can be avoided entirely. Thus, we can completely control for FNE and other social factors, and can determine exactly to what extent ambiguity aversion is driven by such social factors. In our experiment ambiguity aversion, while appearing as commonly found in the presence of FNE, disappears entirely if FNE is eliminated. Implications are discussed. Key words: ambiguity aversion, fear of negative evaluation, homebias JEL classification: C91, D81, Z13; 2 In decision under uncertainty people have been found to prefer options involving clear probabilities (risk) to options with vague probabilities (ambiguity), even if normative theory (Savage 1954) implies indifference. This phenomenon is called ambiguity aversion (Ellsberg 1961). Ambiguity aversion has been shown to be economically relevant and to persist in experimental market settings (Gilboa 2004) and among business owners and managers familiar with decisions under uncertainty (Chesson and Viscusi 2003). People are often willing to spend significant amounts of money to avoid ambiguous processes in favor of normatively equivalent risky processes (Becker and Brownson 1964; Keren and Gerritsen
Salience Theory of Choice Under Risk
, 2010
"... We present a theory of choice among lotteries in which the decision maker’s attention is drawn to (precisely defined) salient payoffs. This leads the decision maker to a contextdependent representation of lotteries in which true probabilities are replaced by decision weights distorted in favor of s ..."
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We present a theory of choice among lotteries in which the decision maker’s attention is drawn to (precisely defined) salient payoffs. This leads the decision maker to a contextdependent representation of lotteries in which true probabilities are replaced by decision weights distorted in favor of salient payoffs. By endogenizing decision weights as a function of payoffs, our model provides a novel and unified account of many empirical phenomena, including frequent riskseeking behavior, invariance failures such as the Allais paradox, and preference reversals. It also yields new predictions, including some that distinguish it from Prospect Theory, which we test.
Static Portfolio Choice under Cumulative Prospect Theory
, 2009
"... We derive the optimal portfolio choice for an investor who behaves according to Cumulative Prospect Theory. The study is done in a oneperiod economy with one riskfree asset and one risky asset, and the reference point corresponds to the terminal wealth arising when the entire initial wealth is inv ..."
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We derive the optimal portfolio choice for an investor who behaves according to Cumulative Prospect Theory. The study is done in a oneperiod economy with one riskfree asset and one risky asset, and the reference point corresponds to the terminal wealth arising when the entire initial wealth is invested into the riskfree asset. When it exists, the optimal holding is a function of a generalized Omega measure of the distribution of the excess return on the risky asset over the riskfree rate. It conceptually resembles Merton’s optimal holding for a CRRA expectedutility maximizer. We derive some properties of the optimal holding and illustrate our results using a simple example where the excess return has a skewnormal distribution. In particular, we show how a Cumulative Prospect Theory investor is highly sensitive to the skewness of the excess return on the risky asset. In the model we adopt, with a piecewisepower value function with different shape parameters, loss aversion might be violated for reasons that are now wellunderstood in the literature. Nevertheless, we argue, on purely behavioral grounds, that this violation is acceptable.
2004) Expected utility theory with “small worlds”. FRU Worcking Papers 2004/04
"... We formulate a new theory of expected utility under uncertainty based on the notion of an eventlattice, which is a natural generalization of a Savage state space. The modelling of uncertainty is based on the idea that the decision maker for each group of related decisions to be taken creates a ”sma ..."
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We formulate a new theory of expected utility under uncertainty based on the notion of an eventlattice, which is a natural generalization of a Savage state space. The modelling of uncertainty is based on the idea that the decision maker for each group of related decisions to be taken creates a ”small world ” which functions as a local state space. We introduce a set of preference axioms similar in spirit to the Savage axioms, and show that they lead to a generalization of the standard von NeumannSavage theory of expected utility. The generalization allows for an intuitive distinction between risk and uncertainty. In each ”small world ” risk is described by an additive probability measure; and these local risk measures all appear as restrictions of a common integrated additive expectation functional which is defined on the ”grand world”, thereby providing numerical expressions to the notion of uncertainty. We illustrate the use of the theory for the Ellsberg paradox and