scholarly journals UTILITY THEORY FRONT TO BACK — INFERRING UTILITY FROM AGENTS' CHOICES

2014 ◽  
Vol 17 (03) ◽  
pp. 1450018 ◽  
Author(s):  
ALEXANDER M. G. COX ◽  
DAVID HOBSON ◽  
JAN OBłÓJ
Keyword(s):  
Utility Function ◽  
Utility Theory ◽  
Consistency Condition ◽  
Maximization Problem ◽  
Consumption Pattern ◽  
Investment Strategies ◽  
Inverse Approach ◽  
To Come ◽  
Utility Maximization Problem ◽  
Stochastic Setting

We pursue an inverse approach to utility theory and associated consumption and investment problems. Instead of specifying a utility function and deriving the actions of an agent, we assume that we observe the actions of the agent (i.e. consumption and investment strategies) and ask if it is possible to derive a utility function for which the observed behavior is optimal. We work in continuous time both in a deterministic and stochastic setting. In the deterministic setup, we find that there are infinitely many utility functions generating a given consumption pattern. In the stochastic setting of a geometric Brownian motion market it turns out that the consumption and investment strategies have to satisfy a consistency condition (PDE) if they are to come from a classical utility maximization problem. We show further that important characteristics of the agent such as risk attitudes (e.g., DARA) can be deduced directly from the agent's consumption and investment choices.

scholarly journals Dual Formulation of the Utility Maximization Problem Under Transaction Costs

2001 ◽  
Vol 11 (4) ◽  
pp. 1353-1383 ◽  
Author(s):  
Griselda Deelstra ◽  
Huyên Pham ◽  
Nizar Touzi
Keyword(s):  
Transaction Costs ◽  
Utility Maximization ◽  
Maximization Problem ◽  
Dual Formulation ◽  
Utility Maximization Problem

scholarly journals The Methodical Approach to Integrated Multi-criteria Assessment of Intellectual Capital

2021 ◽  
Vol 5 (520) ◽  
pp. 281-288
Author(s):  
O. V. Stepanova ◽  
Keyword(s):  
Utility Function ◽  
Intellectual Capital ◽  
Utility Theory ◽  
Factors Affecting ◽  
Management By Objectives ◽  
Methodical Approach ◽  
Components Analysis ◽  
Capital Development ◽  
Integral Indicator

The article is aimed at developing scientific-methodological recommendations for the integrated multi-criteria assessment of intellectual capital. Achieving this goal requires solving the following tasks: analysis of the theoretical principles of intellectual capital; analysis of intellectual capital components; analysis of methods for assessment of intellectual capital; development of a multi-criteria model of integrated assessment of intellectual capital on the basis of program-target approach and utility theory. In line with the conception of management by objectives, as well as in accordance with both the systemic and the program-target approaches, the objectives of enterprise are formulated taking into account the growth, renewal and efficient use of intellectual capital. Based on the analysis of available publications, a classification of factors affecting intellectual capital is compiled. Using the structure of intellectual capital and graph theory, the «tree of purposes» of intellectual capital is built, which represents an unoriented, bound graph, the verticals (nodes) of which are purposes, and the ribs (arcs) are the links between them. A system of criteria – indicators that affect the achievement of the objectives is formulated. As a criterion for optimality of achieving the objective, it is proposed to use the multi-criteria utility function. It is noted that in order to assess intellectual capital, it is advisable to use the additive utility function, which makes it possible to compute the integral indicator of intellectual capital. This, in turn, allows to analyze the growth, renewal and efficiency of the intellectual capital of enterprise over a number of years, as well as compare enterprises with each other.

scholarly journals Comparing utility functions between risky and riskless choice in rhesus monkeys

2021 ◽  
Author(s):  
Philipe M. Bujold ◽  
Simone Ferrari-Toniolo ◽  
Leo Chi U Seak ◽  
Wolfram Schultz
Keyword(s):  
Utility Function ◽  
Utility Theory ◽  
Utility Maximization ◽  
Choice Behavior ◽  
Expected Utility Theory ◽  
Utility Functions ◽  
Random Utility Maximization ◽  
Risky Choices ◽  
Neuronal Mechanisms ◽  
Subjective Value

AbstractDecisions 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 option’s 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.

CHOQUET INTEGRAL MODELS AND INDEPENDENCE CONCEPTS IN MULTIATTRIBUTE UTILITY THEORY

2000 ◽  
Vol 08 (04) ◽  
pp. 385-415 ◽  
Author(s):  
T. MUROFUSHI ◽  
M. SUGENO
Keyword(s):  
Utility Function ◽  
Utility Theory ◽  
Choquet Integral ◽  
Fuzzy Measure ◽  
Multiattribute Utility ◽  
Preference Relations ◽  
Multiattribute Utility Theory ◽  
A Value ◽  
Utility Independence

This paper discusses multiattribute preference relations compatible with a value/utility function represented by the Choquet integral with respect to a fuzzy measure, and shows that the additivity of the fuzzy measure is equivalent to each of mutual preferential independence, mutual weak difference independence, mutual difference independence, mutual utility independence, and additive independence.

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