IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v27y1996i3p267-270.html
   My bibliography  Save this article

On c-optimal random variables

Author

Listed:
  • Rüschendorf, Ludger

Abstract

A characterization is proved for random variables which are optimal couplings w.r.t. a general function c. It turns out that on very general probability spaces optimal couplings can be characterized by generalized subgradients of c-convex functions. An interesting application of optimal couplings are minimal lp-metrics.

Suggested Citation

  • Rüschendorf, Ludger, 1996. "On c-optimal random variables," Statistics & Probability Letters, Elsevier, vol. 27(3), pages 267-270, April.
    • Handle: RePEc:eee:stapro:v:27:y:1996:i:3:p:267-270
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0167-7152(95)00078-X
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Cuestaalbertos, J. A. & Ruschendorf, L. & Tuerodiaz, A., 1993. "Optimal Coupling of Multivariate Distributions and Stochastic Processes," Journal of Multivariate Analysis, Elsevier, vol. 46(2), pages 335-361, August.
    2. Smith, Cyril & Knott, Martin, 1992. "On Hoeffding-Fréchet bounds and cyclic monotone relations," Journal of Multivariate Analysis, Elsevier, vol. 40(2), pages 328-334, February.
    3. Rüschendorf, L. & Rachev, S. T., 1990. "A characterization of random variables with minimum L2-distance," Journal of Multivariate Analysis, Elsevier, vol. 32(1), pages 48-54, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Puccetti, Giovanni & Scarsini, Marco, 2010. "Multivariate comonotonicity," Journal of Multivariate Analysis, Elsevier, vol. 101(1), pages 291-304, January.
    2. Faugeras, Olivier P. & Rüschendorf, Ludger, 2021. "Functional, randomized and smoothed multivariate quantile regions," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
    3. Rippl, Thomas & Munk, Axel & Sturm, Anja, 2016. "Limit laws of the empirical Wasserstein distance: Gaussian distributions," Journal of Multivariate Analysis, Elsevier, vol. 151(C), pages 90-109.
    4. Silvana Pesenti & Sebastian Jaimungal, 2020. "Portfolio Optimisation within a Wasserstein Ball," Papers 2012.04500, arXiv.org, revised Jun 2022.
    5. Jan Bergenthum & Ludger Rüschendorf, 2006. "Comparison of Option Prices in Semimartingale Models," Finance and Stochastics, Springer, vol. 10(2), pages 222-249, April.
    6. Ludger Rüschendorf, 2012. "Worst case portfolio vectors and diversification effects," Finance and Stochastics, Springer, vol. 16(1), pages 155-175, January.
    7. Alfred Galichon & Damien Bosc, 2010. "Extreme dependence for multivariate data," Working Papers hal-03588294, HAL.
    8. Rüschendorf, Ludger & Uckelmann, Ludger, 2002. "On the n-Coupling Problem," Journal of Multivariate Analysis, Elsevier, vol. 81(2), pages 242-258, May.
    9. Tomonari Sei, 2011. "Gradient modeling for multivariate quantitative data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(4), pages 675-688, August.
    10. Alfred Galichon & Damien Bosc, 2010. "Extreme dependence for multivariate data," SciencePo Working papers hal-03588294, HAL.
    11. Malamud, Semyon & Cieslak, Anna & Schrimpf, Paul, 2021. "Optimal Transport of Information," CEPR Discussion Papers 15859, C.E.P.R. Discussion Papers.
    12. Damien Bosc & Alfred Galichon, 2014. "Extreme dependence for multivariate data," SciencePo Working papers hal-03470461, HAL.
    13. Yanqin Fan & Marc Henry, 2020. "Vector copulas," Papers 2009.06558, arXiv.org, revised Apr 2021.
    14. Olivier Paul Faugeras & Ludger Rüschendorf, 2021. "Functional, randomized and smoothed multivariate quantile regions," Post-Print hal-03352330, HAL.
    15. Damien Bosc & Alfred Galichon, 2014. "Extreme dependence for multivariate data," Quantitative Finance, Taylor & Francis Journals, vol. 14(7), pages 1187-1199, July.
    16. Valentina Masarotto & Victor M. Panaretos & Yoav Zemel, 2019. "Procrustes Metrics on Covariance Operators and Optimal Transportation of Gaussian Processes," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 172-213, February.
    17. Alfred Galichon & Damien Bosc, 2010. "Extreme dependence for multivariate data," SciencePo Working papers Main hal-03588294, HAL.
    18. Puccetti, Giovanni & Rüschendorf, Ludger & Vanduffel, Steven, 2020. "On the computation of Wasserstein barycenters," Journal of Multivariate Analysis, Elsevier, vol. 176(C).
    19. Silvana M. Pesenti, 2021. "Reverse Sensitivity Analysis for Risk Modelling," Papers 2107.01065, arXiv.org, revised May 2022.
    20. Faugeras, Olivier & Rüschendorf, Ludger, 2019. "Functional, randomized and smoothed multivariate quantile regions," TSE Working Papers 19-1039, Toulouse School of Economics (TSE), revised Jun 2021.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:stapro:v:27:y:1996:i:3:p:267-270. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.