This paper proposes parameterized multivariate stochastic dominance (PMSD) rules under different distributional assumptions for a class of non-satiable risk-seeking investors. In particular, it determines the PMSD rules for both stable symmetric and Student's t distributions. Methodologically, the PMSD rules for ordering are based on comparison of i) location parameters, ii) dispersion parameters, and iii) either stability indices or degrees of freedom. In addition, it presents the main steps for evaluating such rules. This paper confirms that return tail behavior plays a crucial role in determining non-satiable investors' optimal choices
This paper surveys the use of stochastic dominance to decision making under uncertainty. The first p...
The paper proposes a multivariate comparison among different financial markets, using risk/variabili...
Traditional stochastic dominance rules are so strict and qualitative conditions that generally a sto...
In this study, we investigate whether sector-weighted portfolios based on alternative parametric ass...
We propose a multivariate stochastic dominance relation aimed at ranking different financial markets...
This paper first extends some well-known univariate stochastic dominance results to multivariate sto...
This paper first extends some well-known univariate stochastic dominance results to multiv...
This paper first extends some well-known univariate stochastic dominance results to multiv...
Marginal Conditional Stochastic Dominance (MCSD) developed by Shalit and Yitzhaki (1994) gives the c...
Stochastic dominance permits a partial ordering of alternatives (probability distributions on conseq...
Stochastic dominance permits a partial ordering of alternatives (probability distributions on conseq...
Stochastic dominance permits a partial ordering of alternatives (probability distributions on conseq...
summary:Stochastic dominance is widely used in comparing two risks represented by random variables o...
Stochastic dominance permits a partial ordering of alternatives (probability distributions on conseq...
Stochastic dominance permits a partial ordering of alternatives (probability distributions on conseq...
This paper surveys the use of stochastic dominance to decision making under uncertainty. The first p...
The paper proposes a multivariate comparison among different financial markets, using risk/variabili...
Traditional stochastic dominance rules are so strict and qualitative conditions that generally a sto...
In this study, we investigate whether sector-weighted portfolios based on alternative parametric ass...
We propose a multivariate stochastic dominance relation aimed at ranking different financial markets...
This paper first extends some well-known univariate stochastic dominance results to multivariate sto...
This paper first extends some well-known univariate stochastic dominance results to multiv...
This paper first extends some well-known univariate stochastic dominance results to multiv...
Marginal Conditional Stochastic Dominance (MCSD) developed by Shalit and Yitzhaki (1994) gives the c...
Stochastic dominance permits a partial ordering of alternatives (probability distributions on conseq...
Stochastic dominance permits a partial ordering of alternatives (probability distributions on conseq...
Stochastic dominance permits a partial ordering of alternatives (probability distributions on conseq...
summary:Stochastic dominance is widely used in comparing two risks represented by random variables o...
Stochastic dominance permits a partial ordering of alternatives (probability distributions on conseq...
Stochastic dominance permits a partial ordering of alternatives (probability distributions on conseq...
This paper surveys the use of stochastic dominance to decision making under uncertainty. The first p...
The paper proposes a multivariate comparison among different financial markets, using risk/variabili...
Traditional stochastic dominance rules are so strict and qualitative conditions that generally a sto...