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.

The Application of Expected-Utility Theory to the Choice of Investment Channels in a Defined-Contribution Retirement Fund

2009 ◽  
Vol 39 (2) ◽  
pp. 615-647 ◽  
Author(s):  
Shaun Levitan ◽  
Robert Thomson
Keyword(s):  
Expected Utility Theory ◽  
Assessment Method ◽  
Utility Functions ◽  
Risk Tolerance ◽  
Defined Contribution ◽  
Practical Application ◽  
Retirement Benefits ◽  
Channel Choice ◽  
Retirement Fund ◽  
Standard Risk

AbstractThis study examines the practical application of a system for the derivation of member utility functions for the purpose of recommending investment-channel choice to members of a defined-contribution retirement fund. The utility functions of post-retirement benefits from members of a defined-contribution fund are elicited. The risk aversion of each member is measured and the results are compared with a standard risk-tolerance assessment method.

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.

scholarly journals An Experimental Comparison of Risky and Riskless Choice—Limitations of Prospect Theory and Expected Utility Theory

2019 ◽  
Vol 11 (3) ◽  
pp. 34-67 ◽  
Author(s):  
Hui-Kuan Chung ◽  
Paul Glimcher ◽  
Agnieszka Tymula
Keyword(s):  
Prospect Theory ◽  
Empirical Evidence ◽  
Expected Utility ◽  
Utility Theory ◽  
Expected Utility Theory ◽  
Experimental Comparison ◽  
Reference Dependence ◽  
Empirical Results ◽  
Incentive Compatible ◽  
Gain Loss

Prospect theory, used descriptively for decisions under both risk and certainty, presumes concave utility over gains and convex utility over losses; a pattern widely seen in lottery tasks. Although such discontinuous gain-loss reference-dependence is also used to model riskless choices, only limited empirical evidence supports this use. In incentive-compatible experiments, we find that gain-loss reflection effects are not observed under riskless choice as predicted by prospect theory, even while in the same subjects gain-loss reflection effects are observed under risk. Our empirical results challenge the application of choice models across both risky and riskless domains. (JEL C91, D12, D81)

The Use of Utility Functions for Investment Channel Choice in Defined Contribution Retirement Funds. II: A Proposed System

2003 ◽  
Vol 9 (4) ◽  
pp. 903-958 ◽  
Author(s):  
R. J. Thomson
Keyword(s):  
Stochastic Model ◽  
Utility Function ◽  
Stochastic Models ◽  
Utility Functions ◽  
Retirement Income ◽  
Defined Contribution ◽  
Channel Choice ◽  
Retirement Funds

ABSTRACTIn this paper a system for recommending investment channel choices to members of defined contribution retirement funds is proposed. The system is interactive, using a member's answers to a series of questions to derive a utility function. The observed values are interpolated by means of appropriate formulae to produce a smooth utility function over the whole positive range of benefits at retirement. The resulting function, together with stochastic models of the returns on the available channels and of the annuity factor at exit, is then used to recommend an optimum apportionment of the member's investment. The proposed system is applied to the observed values of utility functions of post-retirement income elicited from members of retirement funds. Difficulties in the application are discussed and the results are analysed. The sensitivity of the recommendations to the parameters of the stochastic model 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 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.

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