IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-03281789.html
   My bibliography  Save this paper

Estimation of fuzzy portfolio efficiency via an improved DEA approach

Author

Listed:
  • Helu Xiao
  • Tiantian Ren

    (LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

  • Teng Ren

Abstract

DEA (Data Envelopment Analysis) is a nonparametric approach that has been used to estimate fuzzy portfolio efficiency. In this paper, we propose an approach under the fuzzy theory framework that can both improve the DEA frontier and suggest a replicable benchmark for investors. We first construct an improved DEA model using the proposed approach and then investigate the relationships among the evaluation model based on a portfolio frontier, the traditional DEA model and the improved DEA model. We show the convergence of the improved DEA model under the fuzzy framework. The simulation indicates that the improved DEA frontier is closer to the portfolio frontier than to the traditional DEA frontier. More importantly, we incorporate the diversification DEA model and improved DEA model to analyze the performance of China's open-end fund. The empirical results indicate that the improved DEA model not only provides a quicker way to assess the investment funds compared to the diversification DEA model but also makes up for the shortcoming of the traditional DEA model, which overestimates the fuzzy portfolio efficiency.

Suggested Citation

  • Helu Xiao & Tiantian Ren & Teng Ren, 2020. "Estimation of fuzzy portfolio efficiency via an improved DEA approach," Post-Print hal-03281789, HAL.
    • Handle: RePEc:hal:journl:hal-03281789
    DOI: 10.1080/03155986.2020.1734904
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Xiao, Helu & Zhou, Zhongbao & Ren, Teng & Liu, Wenbin, 2022. "Estimation of portfolio efficiency in nonconvex settings: A free disposal hull estimator with non-increasing returns to scale," Omega, Elsevier, vol. 111(C).
    2. Zhou, Zhongbao & Gao, Meng & Xiao, Helu & Wang, Rui & Liu, Wenbin, 2021. "Big data and portfolio optimization: A novel approach integrating DEA with multiple data sources," Omega, Elsevier, vol. 104(C).
    3. Ji, Zhengsen & Niu, Dongxiao & Li, Wanying & Wu, Gengqi & Yang, Xiaolong & Sun, Lijie, 2022. "Improving the energy efficiency of China: An analysis considering clean energy and fossil energy resources," Energy, Elsevier, vol. 259(C).

    More about this item

    Statistics

    Access and download statistics

    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:hal:journl:hal-03281789. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.