Journal ArticleDOI
The Efficiency Analysis of Choices Involving Risk
Giora Hanoch,Haim Levy +1 more
TLDR
In this paper, an analysis of the first step of the decision-making process of an individual decision maker among alternative risky ventures is presented, in terms of a single dimension such as money, both for the utility functions and for the probability distributions.Abstract:
Publisher Summary The choice of an individual decision maker among alternative risky ventures may be regarded as a two-step procedure. The decision maker chooses an efficient set among all available portfolios, independently of his tastes or preferences. Then, the decision maker applies individual preferences to this set to choose the desired portfolio. The subject of this chapter is the analysis of the first step. It deals with optimal selection rules that minimize the efficient set by discarding any portfolio that is inefficient in the sense that it is inferior to a member of the efficient set, from point of view of each and every individual, when all individuals' utility functions are assumed to be of a given general class of admissible functions. The analysis presented in the chapter is carried out in terms of a single dimension such as money, both for the utility functions and for the probability distributions. However, the results may easily be extended, with minor changes in the theorems and the proofs, to the multivariate case. The chapter explains a necessary and sufficient condition for efficiency, when no further restrictions are imposed on the utility functions. It presents proofs of the optimal efficiency criterion in the presence of general risk aversion, that is, for concave utility functions.read more
Citations
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Journal ArticleDOI
Crossing points of distributions and a theorem that relates them to second order stochastic dominance
TL;DR: In this paper, the authors give formal definitions for crossing points in pairs of distributions and give a detailed proof of a theorem that relates those points to the second order stochastic dominance (SSD).
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Four-decision tests for stochastic dominance, with an application to environmental psychophysics
TL;DR: In this paper, the authors show that if the survival function of a random variable X lies to the right of the survival functions of another random variable Y, then X is said to stochastically dominate Y.
Journal ArticleDOI
Incorporating Risk into Eucalyptus Species—Site Selection Decisions
TL;DR: In this article, the mean-variance and expected value rules, along with stochastic dominance analysis are used to show how risk can be included in species-site selection decisions.
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A risk programming analysis of cattle procurement by beef packers
TL;DR: In this paper, the authors present a firm decision model focusing on large and important industries, such as cattle feeders and cattle packing, to predict trends in relative generating concern among cattle feeder and importance of alternative arrangements, and others about trends in the relative importance evaluating policies.
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Shrinkage estimation with general loss functions: an application of stochastic dominance theory
TL;DR: In this article, a recommended shrinkage factor interval is calculated for gaussian, unbiased estimators based on stochastic dominance theory over a broad class of loss functions, and the unbiased estimator is found to be dominated by shrunken estimators over a number of loss function classes.
References
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Journal ArticleDOI
Capital asset prices: a theory of market equilibrium under conditions of risk*
TL;DR: In this paper, the authors present a body of positive microeconomic theory dealing with conditions of risk, which can be used to predict the behavior of capital marcets under certain conditions.
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The Utility Analysis of Choices Involving Risk
TL;DR: In this paper, the authors suggest that an important class of reactions of individuals to risk can be rationalized by a rather simple extension of orthodox utility analysis, i.e., individuals frequently must, or can, choose among alternatives that differ, among other things, in the degree of risk to which the individual will be subject.
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The Existence of Probability Measures with Given Marginals
TL;DR: In this article, the existence of probability distributions with given marginals is studied under typically weaker assumptions, than those which are required by the use of Theorem 1, and necessary and sufficient conditions for a sequence of probability measures to be the sequence of distributions of a martingale, an upper semi-martingale or of partial sums of independent random variables.