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Article
Gruss Type Bounds for the Covariance of Transformed Random Variables
Journal of Inequalities and Applications (2010)
  • Martin Egozcue
  • Luis Fuentes García
  • Wing Keung Wong
  • Ricardas Zitikis, UWO
Abstract

A number of problems in Economics, Finance, Information Theory, Insurance, and generally in decision making under uncertainty rely on estimates of the covariance between (transformed) random variables, which can, for example, be losses, risks, incomes, financial returns, and so forth. Several avenues relying on inequalities for analyzing the covariance are available in the literature, bearing the names of Chebyshev, Grüss, Hoeffding, Kantorovich, and others. In the present paper we sharpen the upper bound of a Grüss-type covariance inequality by incorporating a notion of quadrant dependence between random variables and also utilizing the idea of constraining the means of the random variables.

Publication Date
February 4, 2010
Citation Information
Martin Egozcue, Luis Fuentes García, Wing Keung Wong and Ricardas Zitikis. "Gruss Type Bounds for the Covariance of Transformed Random Variables" Journal of Inequalities and Applications Vol. 2010 Iss. ID619423 (2010)
Available at: http://works.bepress.com/luis_fuentesgarcia/6/