Stochastic ordering of Gini indexes for multivariate elliptical risks

Bara Kim, Jeongsim Kim

Research output: Contribution to journalArticle

Abstract

In this paper, we show that the conjecture, made by Samanthi et al. (2016), on the ordering of Gini indexes of multivariate normal risks with respect to the strength of dependence, is not true. By using the positive semi-definite ordering of covariance matrices, we can obtain the usual stochastic order of the Gini indexes for multivariate normal risks. This can be generalized to multivariate elliptical risks. We also investigate the monotonicity of the Gini indexes in the usual stochastic order when the covariance (dispersion, resp.) matrices of multivariate normal (elliptical, resp) risks increase componentwise. In addition, we derive a large deviation result for the Gini indexes of multivariate normal risks.

Original languageEnglish
Pages (from-to)151-158
Number of pages8
JournalInsurance: Mathematics and Economics
Volume88
DOIs
Publication statusPublished - 2019 Sep 1

Fingerprint

Gini Index
Stochastic Ordering
Multivariate Normal
Usual Stochastic Order
Positive semidefinite
Large Deviations
Covariance matrix
Monotonicity
Stochastic ordering
Gini index

Keywords

  • Elliptical distribution
  • Gini index
  • Large deviation
  • Positive semi-definite
  • Usual stochastic order

ASJC Scopus subject areas

  • Statistics and Probability
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty

Cite this

Stochastic ordering of Gini indexes for multivariate elliptical risks. / Kim, Bara; Kim, Jeongsim.

In: Insurance: Mathematics and Economics, Vol. 88, 01.09.2019, p. 151-158.

Research output: Contribution to journalArticle

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