Geodesic
Multivariate stochastic dominance for multivariate normal distribution
Kybernetika, Tome 54 (2018) no. 6, pp. 1264-1283
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Stochastic dominance is widely used in comparing two risks represented by random variables or random vectors. There are general approaches, based on knowledge of distributions, which are dedicated to identify stochastic dominance. These methods can be often simplified for specific distribution. This is the case of univariate normal distribution, for which the stochastic dominance rules have a very simple form. It is however not straightforward if these rules are also valid for multivariate normal distribution. We propose the stochastic dominance rules for multivariate normal distribution and provide a rigorous proof. In a computational experiment we employ these rules to test its efficiency comparing to other methods of stochastic dominance detection.
Stochastic dominance is widely used in comparing two risks represented by random variables or random vectors. There are general approaches, based on knowledge of distributions, which are dedicated to identify stochastic dominance. These methods can be often simplified for specific distribution. This is the case of univariate normal distribution, for which the stochastic dominance rules have a very simple form. It is however not straightforward if these rules are also valid for multivariate normal distribution. We propose the stochastic dominance rules for multivariate normal distribution and provide a rigorous proof. In a computational experiment we employ these rules to test its efficiency comparing to other methods of stochastic dominance detection.
DOI : 10.14736/kyb-2018-6-1264
Classification : 91B16, 91B28
Keywords: multivariate stochastic dominance; multivariate normal distribution; stochastic dominance rules 
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Petrová, Barbora. Multivariate stochastic dominance for multivariate normal distribution. Kybernetika, Tome 54 (2018) no. 6, pp. 1264-1283. doi: 10.14736/kyb-2018-6-1264

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