The covariance sign of transformed random variables with applications to economics and finance

Martín Egozcue, Luis Fuentes García, Wing Keung WONG, Riardas Zitikis*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)


A number of problems in economics, finance and insurance rely on determining the sign of the covariance of two transformations of a random variable. The classical Chebyshev's inequality offers a powerful tool for solving the problem, but it assumes that the transformations are monotonic, which is not always the case in applications. For this reason, in the present paper, we establish new results for determining the covariance sign and provide further insights into the area. Unlike many previous works, our method of analysis, which is probabilistic in its nature, does not rely on the classical Höffding's representation of the covariance or on any of its numerous extensions and generalizations. We motivate our research with several problems arising in economics, finance and insurance.

Original languageEnglish
Pages (from-to)291-300
Number of pages10
JournalIMA Journal of Management Mathematics
Issue number3
Publication statusPublished - Jul 2011

Scopus Subject Areas

  • Management Information Systems
  • Modelling and Simulation
  • Economics, Econometrics and Finance(all)
  • Strategy and Management
  • Management Science and Operations Research
  • Applied Mathematics

User-Defined Keywords

  • Chebyshev's inequality
  • covariance inequality
  • decision under risk


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