Advances in complete mixability
Giovanni Puccetti, Bin Wang, and Ruodu Wang
Source: J. Appl. Probab.
Volume 49, Number 2
The concept of complete mixability is relevant to some problems of optimal
couplings with important applications in quantitative risk management. In this
paper we prove new properties of the set of completely mixable distributions,
including a completeness and a decomposition theorem. We also show that
distributions with a concave density and radially symmetric distributions are
Full-text: Access denied (no subscription
We're sorry, but we are unable to provide
you with the full text of this article because we are not able to identify
you as a subscriber.
If you have a personal subscription to
this journal, then please login. If you are already logged in, then you
may need to update your profile to register your subscription. Read more about accessing full-text
Links and Identifiers
Permanent link to this document: http://projecteuclid.org/euclid.jap/1339878796
Digital Object Identifier: doi:10.1239/jap/1339878796
Zentralblatt MATH identifier: 06053721
Mathematical Reviews number (MathSciNet): MR2977805
Embrechts, P. and Puccetti, G. (2010). Risk aggregation. In Copula Theory and Its Applications (Lecture Notes Statist. 198), eds P. Bickel et al. Springer, Berlin, pp. 111–126.
Knott, M. and Smith, C. (2006). Choosing joint distributions so that the variance of the sum is small. J. Multivariate Anal. 97, 1757–1765.
Nelsen, R. B. and Úbeda-Flores, M. (2012). Directional dependence in multivariate distributions. Ann. Inst. Statist. Math. 64, 677–685.
Rüschendorf, L. and Uckelmann, L. (2002). Variance minimization and random variables with constant sum. In Distributions with Given Marginals and Statistical Modelling, Dordrecht, Kluwer, pp. 211–222.
Wang, B. and Wang, R. (2011). The complete mixability and convex minimization problems with monotone marginal densities. J. Multivariate Anal. 102, 1344–1360.
Wang, R., Peng, L. and Yang, J. (2011). Bounds for the sum of dependent risks and worst Value-at-Risk with monotone marginal densities. Preprint, Georgia Institute of Technology. \endharvreferences