Hessian orders and multinormal distributions

Alessandro Arlotto and Marco Scarsini

Journal of Multivariate Analysis, 2009, vol. 100, issue 10, 2324-2330

Abstract: Several well known integral stochastic orders (like the convex order, the supermodular order, etc.) can be defined in terms of the Hessian matrix of a class of functions. Here we consider a generic Hessian order, i.e., an integral stochastic order defined through a convex cone of Hessian matrices, and we prove that if two random vectors are ordered by the Hessian order, then their means are equal and the difference of their covariance matrices belongs to the dual of . Then we show that the same conditions are also sufficient for multinormal random vectors. We study several particular cases of this general result.

Keywords: Hessian; orders; Multivariate; normal; distribution; Convex; cones; Dual; space; Completely; positive; order (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (9)

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