Chebyshev inequalities with law-invariant deviation measures

  • Authors:

  • Bogdan Grechuk;Anton Molyboha;Michael Zabarankin

  • Affiliations:

  • Department of mathematical sciences, stevens institute of technology, castle point on hudson, hoboken, nj 07030 e-mail: bgrechuk@stevens.edu/ amolyboh@stevens.edu/ mzabaran@stevens.edu;Department of mathematical sciences, stevens institute of technology, castle point on hudson, hoboken, nj 07030 e-mail: bgrechuk@stevens.edu/ amolyboh@stevens.edu/ mzabaran@stevens.edu;Department of mathematical sciences, stevens institute of technology, castle point on hudson, hoboken, nj 07030 e-mail: bgrechuk@stevens.edu/ amolyboh@stevens.edu/ mzabaran@stevens.edu

  • Venue:
  • Probability in the Engineering and Informational Sciences
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

The consistency of law-invariant general deviation measures with concave ordering has been used to generalize the Rao–Blackwell theorem and to develop an approach for reducing minimization of law-invariant deviation measures to minimization of the measures on subsets of undominated random variables with respect to concave ordering. This approach has been applied for constructing the Chebyshev and Kolmogorov inequalities with law-invariant deviation measures—in particular with mean absolute deviation, lower semideviation and conditional value-at-risk deviation. Additionally, an advantage of the Kolmogorov inequality with certain deviation measures has been illustrated in estimating the probability of the exchange rate of two currencies to be within specified bounds.