Document Type

Journal Article

Department/Unit

Department of Economics

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

2010

Source Publication Title

Journal of Inequalities and Applications

Volume

2010

Start Page

1

End Page

10

Publisher

Hindawi

Peer Reviewed

1

Copyright

Creative Commons Attribution License

DOI

10.1155/2010/619423

Link to Publisher's Edition

http://dx.doi.org/10.1155/2010/619423

ISSN (print)

10255834

Included in

Economics Commons

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