Giora Hanoch

Bio: Giora Hanoch is an academic researcher from Hebrew University of Jerusalem. The author has contributed to research in topics: Probability distribution & Portfolio optimization. The author has an hindex of 3, co-authored 3 publications receiving 1348 citations.

The Efficiency Analysis of Choices Involving Risk

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.

Efficient Portfolio Selection with Quadratic and Cubic Utility.

Abstract: Decisions about investment, or portfolio selection, are regarded as choices among alternative probability distributions of returns, where the optimal choice is determined by maximization of the expected value of an investor's utility function.' In the real world, investors' utility functions and investment probability distributions of returns may assume highly complex or irregular forms. However, most theoretical discussions of choice under risk have dealt with relatively simple forms, for example, quadratic utility functions and normal probability distributions, in order to make more manageable the description and testing of investment decision rules.2 This paper presents optimal efficiency criteria for portfolio selection when the utility function is quadratic in money returns and for a variety of kinds of information about the distribution of returns. In addition, it provides an optimal criterion for cubic utility. By efficiency criteria we mean conditions for dominance, or preference among risks, which apply to all investors whose utility functions are of a given general class (e.g., quadratic), independent of specific individual tastes or specific parameters of the utility function. Our main conclusions are: first, that the common procedures and criteria for quadratic utility, of which the simple mean-variance criterion is the best known and most widely used,3 are insufficient and may be improved considerably. The criteria given in the following section are all weaker sufficient conditions for dominance, relative to the mean-variance criterion, and thus they are more effective. Second, we claim that a cubic utility may be preferable, in some respects, to the quadratic form and is also amenable to a complete efficiency analysis, with some interesting implications. * The authors wish to thank Merton Miller and A. Beja for valuable comments and criticism on a first draft.

Relative Effectiveness of Efficiency Criteria for Portfolio Selection

Abstract: Individual decisions about investment may be regarded as choices among alternative probability distributions of net returns. It is assumed that these distributions are completely known and independent of initial wealth positions, and that individuals determine the preferred portfolio of investment in accordance with a given, consistent set of preferences.

Stochastic dominance and expected utility: survey and analysis

Abstract: While Stochastic Dominance has been employed in various forms as early as 1932, it has only been since 1969-1970 that the notion has been developed and extensively employed in the area of economics, finance, agriculture, statistics, marketing and operations research. In this survey, the first-, second-and third-order stochastic dominance rules are discussed with an emphasis on the development in the area since the 1980s.