The Experts below are selected from a list of 285 Experts worldwide ranked by ideXlab platform
Götz Uebe - One of the best experts on this subject based on the ideXlab platform.
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Risk Averse Utility Functions
Operations Research ’92, 1993Co-Authors: Götz UebeAbstract:In a most recent paper Cox and Huang describe a class of strictly concave and differentiable Utility Functions by two asymptotic concepts: regular variation at infinity, asymptotic constancy of relative risk aversion, and a norm of loglinear closeness. By generalization and by direct analysis of the underlying second order nonlinear differential equation two constructive schemes for the generation of appropriate Utility Functions are outlined.
Gérard Pafum - One of the best experts on this subject based on the ideXlab platform.
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Utility Functions: From Risk Theory to Finance
North American Actuarial Journal, 1998Co-Authors: Hans U. Gerber A.s.a., Gérard PafumAbstract:This article is a self-contained survey of Utility Functions and some of their applications. Throughout the paper the theory is illustrated by three examples: exponential Utility Functions, power Utility Functions of the first kind (such as quadratic Utility Functions), and power Utility Functions of the second kind (such as the logarithmic Utility function). The postulate of equivalent expected Utility can be used to replace a random gain by a fixed amount and to determine a fair premium for claims to be insured, even if the insurer’s wealth without the new contract is a random variable itself. Then n companies (or economic agents) with random wealth are considered. They are interested in exchanging wealth to improve their expected Utility. The family of Pareto optimal risk exchanges is characterized by the theorem of Borch. Two specific solutions are proposed. The first, believed to be new, is based on the synergy potential; this is the largest amount that can be withdrawn from the system witho...
Wolfram Schultz - One of the best experts on this subject based on the ideXlab platform.
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comparing Utility Functions between risky and riskless choice in rhesus monkeys
bioRxiv, 2021Co-Authors: Philipe M Bujold, Simone Ferraritoniolo, Leo Chi U Seak, Wolfram SchultzAbstract:Decisions can be risky or riskless, depending on the outcomes of the choice. Expected Utility Theory describes risky choices as a Utility maximization process: we choose the option with the highest subjective value (Utility), which we compute considering both the options value and its associated risk. According to the random Utility maximization framework, riskless choices could also be based on a Utility measure. Neuronal mechanisms of Utility-based choice may thus be common to both risky and riskless choices. This assumption would require the existence of a Utility function that accounts for both risky and riskless decisions. Here, we investigated whether the choice behavior of macaque monkeys in riskless and risky decisions could be described by a common underlying Utility function. We found that the Utility Functions elicited in the two choice scenarios were different from each other, even after taking into account the contribution of subjective probability weighting. Our results suggest that distinct Utility representations exist for riskless and risky choices, which could reflect distinct neuronal representations of the Utility quantities, or distinct brain mechanisms for risky and riskless choices. The different Utility Functions should be taken into account in neuronal investigations of Utility-based choice.
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adaptation of Utility Functions to reward distribution in rhesus monkeys
bioRxiv, 2020Co-Authors: Philipe M Bujold, Simone Ferraritoniolo, Wolfram SchultzAbstract:This study investigated the influence of experienced reward distributions on the shape of Utility func-tions inferred from economic choice. Utility is the hypothetical variable that appears to be maximized by the choice. Despite the generally accepted notion that Utility Functions are not insensitive to external references, the exact occurrence of such changes remains largely unknown. Here we benefitted from the capacity to perform thorough and extensive experimental tests of one of our evolutionary closest, experimentally viable and intuitively understandable species, the rhesus macaque monkey. Data from thousands of binary choices demonstrated that the animals9 preferences changed dependent on the sta-tistics of recently experienced rewards and adapted to future expected rewards. The elicited Utility Functions shifted and extended their shape with several months of changes in the mean and range of reward distributions. However, the adaptations were usually not complete, suggesting that past expe-riences remained present when anticipating future rewards. Through modelling, we found that rein-forcement learning provided a strong basis for explaining these adaptations. Thus, rather than having stable and fixed preferences assumed by normative economic models, rhesus macaques flexibly shaped their preferences to optimize decision-making according to the statistics of the environment.
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Utility Functions predict variance and skewness risk preferences in monkeys
Proceedings of the National Academy of Sciences of the United States of America, 2016Co-Authors: Wilfried Genest, William R Stauffer, Wolfram SchultzAbstract:Utility is the fundamental variable thought to underlie economic choices. In particular, Utility Functions are believed to reflect preferences toward risk, a key decision variable in many real-life situations. To assess the validity of Utility representations, it is therefore important to examine risk preferences. In turn, this approach requires formal definitions of risk. A standard approach is to focus on the variance of reward distributions (variance-risk). In this study, we also examined a form of risk related to the skewness of reward distributions (skewness-risk). Thus, we tested the extent to which empirically derived Utility Functions predicted preferences for variance-risk and skewness-risk in macaques. The expected utilities calculated for various symmetrical and skewed gambles served to define formally the direction of stochastic dominance between gambles. In direct choices, the animals’ preferences followed both second-order (variance) and third-order (skewness) stochastic dominance. Specifically, for gambles with different variance but identical expected values (EVs), the monkeys preferred high-variance gambles at low EVs and low-variance gambles at high EVs; in gambles with different skewness but identical EVs and variances, the animals preferred positively over symmetrical and negatively skewed gambles in a strongly transitive fashion. Thus, the Utility Functions predicted the animals’ preferences for variance-risk and skewness-risk. Using these well-defined forms of risk, this study shows that monkeys’ choices conform to the internal reward valuations suggested by their Utility Functions. This result implies a representation of Utility in monkeys that accounts for both variance-risk and skewness-risk preferences.
Hans U. Gerber A.s.a. - One of the best experts on this subject based on the ideXlab platform.
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Utility Functions: From Risk Theory to Finance
North American Actuarial Journal, 1998Co-Authors: Hans U. Gerber A.s.a., Gérard PafumAbstract:This article is a self-contained survey of Utility Functions and some of their applications. Throughout the paper the theory is illustrated by three examples: exponential Utility Functions, power Utility Functions of the first kind (such as quadratic Utility Functions), and power Utility Functions of the second kind (such as the logarithmic Utility function). The postulate of equivalent expected Utility can be used to replace a random gain by a fixed amount and to determine a fair premium for claims to be insured, even if the insurer’s wealth without the new contract is a random variable itself. Then n companies (or economic agents) with random wealth are considered. They are interested in exchanging wealth to improve their expected Utility. The family of Pareto optimal risk exchanges is characterized by the theorem of Borch. Two specific solutions are proposed. The first, believed to be new, is based on the synergy potential; this is the largest amount that can be withdrawn from the system witho...
Peter Norman Sørensen - One of the best experts on this subject based on the ideXlab platform.
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Simple Utility Functions with Giffen Demand
Economic Theory, 2006Co-Authors: Peter Norman SørensenAbstract:Simple Utility Functions with the Giffen property are presented: locally, the demand curve for a good is upward sloping. The Utility Functions represent continuous, monotone, convex preferences.
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Simple Utility Functions with Giffen Demand
2004Co-Authors: Peter Norman SørensenAbstract:We present some simple Utility Functions whose Marshallian demand Functions possess the Giffen property: at some price-wealth pairs, the demand for a good marginally increases in response to an increase in its own price. The Utility Functions satisfy standard preference properties throughout the usual consumption set of nonnegative bundles: continuity, monotonicity, and convexity.
