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Stochastic Dominance and Moments of Distributions
Mathematics of Operations Research, 1980Stochastic dominance orders of all finite degrees are defined on the set of distribution functions on the nonnegative real numbers in terms of integrals of the distributions. It is proved that if F strictly nth-degree stochastically dominates G, and if the moments of F and G through order n are finite with μFk = ∫Xk dF (x), then (μF1, …, μFn) ≠ (μG1, …
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Marginal Conditional Stochastic Dominance
Management Science, 1994This paper introduces the concept of Marginal Conditional Stochastic Dominance (MCSD), which states the conditions under which all risk-averse individuals, when presented with a given portfolio, prefer to increase the share of one risky asset over that of another. MCSD rules also answer the question of whether all risk-averse individuals include a new
Haim Shalit, Shlomo Yitzhaki
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The Journal of Finance, 1982
IN THE LATE 1960s and 1970s, the Stochastic Dominance (SD) efficiency analysis framework was extensively developed and applied mainly to portfolio selection problems. The three basic decision criteria in this framework are the First, Second, and Third Degree Stochastic Dominance rules (hereafter FSD, SSD, and TSD, respectively). In most previous proofs
Kroll, Yoram, Levy, Haim
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IN THE LATE 1960s and 1970s, the Stochastic Dominance (SD) efficiency analysis framework was extensively developed and applied mainly to portfolio selection problems. The three basic decision criteria in this framework are the First, Second, and Third Degree Stochastic Dominance rules (hereafter FSD, SSD, and TSD, respectively). In most previous proofs
Kroll, Yoram, Levy, Haim
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Tractable Almost Stochastic Dominance
European Journal of Operational Research, 2012zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Andrey Lizyayev, Andrzej Ruszczynski
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The concept of stochastic dominance is defined, and its relation to welfare, poverty, and income inequality explained. A brief discussion is provided of how statistical inference may be performed for hypotheses relating to stochastic dominance.
Russell Davidson
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Multivariate Stochastic Dominance and Moments
Mathematics of Operations Research, 1991The sequence ≥nd of nth degree stochastic dominances for d-dimensional distribution functions is defined. It is shown that, under some regularity conditions, ≥nd implies ≥nd−1 for the (d − 1)-dimensional marginals. Also some necessary conditions for ≥nd are established.
G. L. O'Brien, SCARSINI, MARCO
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Stochastic dominance and optimal portfolio [PDF]
Economics Letters, 2001 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
K. Dachraoui, G. Dionne
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, 2008 The concept of stochastic dominance is defined, and its relation to welfare, poverty, and income inequality explained. A brief discussion is provided of how statistical inference may be performed for hypotheses relating to stochastic dominance.
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Generalized Almost Stochastic Dominance
Operations Research, 2013Almost stochastic dominance allows small violations of stochastic dominance rules to avoid situations where most decision makers prefer one alternative to another but stochastic dominance cannot rank them. While the idea behind almost stochastic dominance is quite promising, it has not caught on in practice.
Ilia Tsetlin +3 more
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Stochastic Dominance on Unidimensional Grids
Mathematics of Operations Research, 1995Special stochastic-dominance relations for probability distributions on a finite grid of evenly-spaced points are considered. The relations depend solely on iterated partial sums of grid-point probabilities and are very computer efficient. Their corresponding classes of utility functions for expected-utility comparisons consist of functions defined on
Peter C. Fishburn, Irving H. Lavalle
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