
arXiv: 1910.07158
AbstractFor two n-dimensional elliptical random vectors X and Y, we establish an identity for $\mathbb{E}[f({\bf Y})]- \mathbb{E}[f({\bf X})]$, where $f\,{:}\, \mathbb{R}^n \rightarrow \mathbb{R}$ satisfies some regularity conditions. Using this identity we provide a unified method to derive sufficient and necessary conditions for classifying multivariate elliptical random vectors according to several main integral stochastic orders. As a consequence we obtain new inequalities by applying the method to multivariate elliptical distributions. The results generalize the corresponding ones for multivariate normal random vectors in the literature.
supermodular order, multivariate normal distribution, Mathematics - Statistics Theory, Statistics Theory (math.ST), FOS: Economics and business, Risk Management (q-fin.RM), FOS: Mathematics, Inequalities; stochastic orderings, increasing convex order, multivariate elliptical distribution, usual stochastic order, Quantitative Finance - Risk Management
supermodular order, multivariate normal distribution, Mathematics - Statistics Theory, Statistics Theory (math.ST), FOS: Economics and business, Risk Management (q-fin.RM), FOS: Mathematics, Inequalities; stochastic orderings, increasing convex order, multivariate elliptical distribution, usual stochastic order, Quantitative Finance - Risk Management
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