Hessian orders and multinormal distributions

Marco Scarsini and Alexandro Arlotto
Additional contact information
Alexandro Arlotto: OPIM Department - University of Pennsylvania

Post-Print from HAL

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 H. 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: 2009-11
References: Add references at CitEc
Citations: View citations in EconPapers (9)

Published in Journal of Multivariate Analysis, 2009, Vol.100,nº10, pp.2324-2330. ⟨10.1016/j.jmva.2009.03.009⟩

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Journal Article: Hessian orders and multinormal distributions (2009)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-00491679

DOI: 10.1016/j.jmva.2009.03.009

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().