IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v270y2018i3p826-836.html
   My bibliography  Save this article

Estimation and asymptotics for buffered probability of exceedance

Author

Listed:
  • Mafusalov, Alexander
  • Shapiro, Alexander
  • Uryasev, Stan

Abstract

This paper studies statistical properties of empirical (sample) estimates of the buffered probability of exceedance (bPOE). The estimation procedure is based on one dimensional minimization representation of the bPOE. Convergence rates and asymptotic properties of the suggested estimation procedures are investigated. Theoretical predictions are validated with numerical experiments, including a special case of exponential distribution, and a study proposing bPOE modification of minimum volume ellipsoid problem.

Suggested Citation

  • Mafusalov, Alexander & Shapiro, Alexander & Uryasev, Stan, 2018. "Estimation and asymptotics for buffered probability of exceedance," European Journal of Operational Research, Elsevier, vol. 270(3), pages 826-836.
  • Handle: RePEc:eee:ejores:v:270:y:2018:i:3:p:826-836
    DOI: 10.1016/j.ejor.2018.01.021
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221718300420
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2018.01.021?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mikhail Zhitlukhin, 2018. "Monotone Sharpe ratios and related measures of investment performance," Papers 1809.10193, arXiv.org, revised May 2021.
    2. Yongqiao Wang & He Ni & Stan Uryasev, 2023. "Buffered-ranking intervals for virtual profit efficiency analysis," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(4), pages 1149-1181, December.
    3. Pertaia, Giorgi & Prokhorov, Artem & Uryasev, Stan, 2022. "A new approach to credit ratings," Journal of Banking & Finance, Elsevier, vol. 140(C).
    4. Matthew Norton & Valentyn Khokhlov & Stan Uryasev, 2021. "Calculating CVaR and bPOE for common probability distributions with application to portfolio optimization and density estimation," Annals of Operations Research, Springer, vol. 299(1), pages 1281-1315, April.

    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:ejores:v:270:y:2018:i:3:p:826-836. 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.

    We have no bibliographic references for this item. You can help adding them by using 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/locate/eor .

    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.