scholarly journals Can Expected Utility Theory Explain Gambling?

2002 ◽  
Vol 92 (3) ◽  
pp. 613-624 ◽  
Author(s):  
Roger Hartley ◽  
Lisa Farrell
Keyword(s):  
Expected Utility ◽  
Capital Markets ◽  
Utility Theory ◽  
Time Preference ◽  
Expected Utility Theory ◽  
Utility Functions ◽  
Finite Set ◽  
Lending Rates ◽  
Previous Claim

We investigate the ability of expected utility theory to account for simultaneous gambling and insurance. Contrary to a previous claim that borrowing and lending in perfect capital markets removes the demand for gambles, we show expected utility theory with nonconcave utility functions can explain gambling. When the rates of interest and time preference are equal, agents seek to gamble unless income falls in a finite set of values. When they differ, there is a range of incomes where gambles are desired. Different borrowing and lending rates can account for persistent gambling provided the rates span the rate of time preference.

Housing Market Search Behavior and Expected Utility Theory: 1. Measuring Preferences for Housing

1982 ◽  
Vol 14 (5) ◽  
pp. 681-698 ◽  
Author(s):  
T R Smith ◽  
W A V Clark
Keyword(s):  
Los Angeles ◽  
Housing Market ◽  
Expected Utility ◽  
Utility Theory ◽  
House Price ◽  
Expected Utility Theory ◽  
Utility Functions ◽  
Future Search ◽  
Space Construction ◽  
Market Search

This is the first of two papers examining housing market search in a Los Angeles market. In this paper, we derive and analyze utility functions for housing for each individual in two groups of subjects. The utility functions are derived from an experimental setting, in which house price, floor space, construction quality, and neighborhood quality are varied. The functions are found to be essentially compatible with a linear model. They are used to predict the ratings of real houses and the ratings of the expected value of future search. These ratings are compared with actual ratings obtained from subjects during search. The results suggest that the actual or predicted ratings may be employed in a direct test of a simple expected utility theory of search, and further research along these lines appears justified.

The Use of Utility Functions for Investment Channel Choice in Defined Contribution Retirement Funds. I: Defence

2003 ◽  
Vol 9 (3) ◽  
pp. 653-709 ◽  
Author(s):  
R.J. Thomson
Keyword(s):  
Empirical Evidence ◽  
Expected Utility ◽  
Utility Theory ◽  
Expected Utility Theory ◽  
Utility Functions ◽  
Defined Contribution ◽  
Channel Choice ◽  
Retirement Fund ◽  
Retirement Funds

ABSTRACTThis paper addresses the use of expected utility theory for the recommendation of an apportionment between investment channels of a member's interest in a defined contribution retirement fund. Such usage is defended against arguments that have been levelled against expected utility theory and empirical evidence is discussed.

scholarly journals On the futility of estimating utility functions: Why the parameters we measure are wrong, and why they do not generalize

2019 ◽  
Author(s):  
Neil Stewart ◽  
Emina Canic ◽  
Timothy L Mullett
Keyword(s):  
Parameter Estimation ◽  
Risk Aversion ◽  
Prospect Theory ◽  
Expected Utility ◽  
Utility Theory ◽  
Expected Utility Theory ◽  
Utility Functions ◽  
Parameter Estimates ◽  
Risky Choices ◽  
Long Time

We have known for a long time that people’s risky choices depart systematically from expected utility theory,and also from related models like prospect theory. But it is still common to use expected utility theory orprospect theory to estimate parameters like risk aversion from sets of risky choices. We have also known fora long time that when parameters are estimated, a systematic departure between the model and the datacauses biased parameter estimates. Here we show how the bias in parameter estimation interacts with the setof choices presented to participants. We find that estimates of risk aversion vary greatly between choice setseven though no real differences in risk aversion exist. We find parameters do not generalise at all betweenchoice sets, even when the sets are random draws from a master choice set.

scholarly journals Cumulative Prospect Theory Version with Fuzzy Values of Outcome Estimates

Risks ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 72
Author(s):  
Oleg Uzhga-Rebrov ◽  
Peter Grabusts
Keyword(s):  
Prospect Theory ◽  
Expected Utility ◽  
Utility Theory ◽  
Expected Utility Theory ◽  
Cumulative Prospect Theory ◽  
Development History ◽  
Decisions Under Risk ◽  
History Of ◽  
Main Factors ◽  
Theoretical Foundations

Choosing solutions under risk and uncertainty requires the consideration of several factors. One of the main factors in choosing a solution is modeling the decision maker’s attitude to risk. The expected utility theory was the first approach that allowed to correctly model various nuances of the attitude to risk. Further research in this area has led to the emergence of even more effective approaches to solving this problem. Currently, the most developed theory of choice with respect to decisions under risk conditions is the cumulative prospect theory. This paper presents the development history of various extensions of the original expected utility theory, and the analysis of the main properties of the cumulative prospect theory. The main result of this work is a fuzzy version of the prospect theory, which allows handling fuzzy values of the decisions (prospects). The paper presents the theoretical foundations of the proposed version, an illustrative practical example, and conclusions based on the results obtained.

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