IDEAS home Printed from
MyIDEAS: Login to save this article or follow this journal

New Dea Performance Evaluation Indices And Their Applications In The American Fund Market



    (Faculty of Mathematics and Information Science, Wenzhou University, Wenzhou, Zhejiang Province, China)


    (Faculty of Science, Xi'an Jiaotong University, Xi'an, Shaanxi Province, China)

Registered author(s):

    The data envelopment analysis (DEA) method is a mathematical programming approach to evaluate the relative performance of portfolios. Considering that the risk input indicators of existing DEA performance evaluation indices cannot reflect the pervasive fat tails and asymmetry in return distributions of mutual funds, we originally introduce new risk measures CVaR and VaR into inputs of relevant DEA indices to measure relative performance of portfolios more objectively. To fairly evaluate the performance variation of the same fund during different time periods, we creatively treat them as different decision making units (DMUs). Different from available DEA applications which mainly investigate the American mutual fund performance from the whole market or industry aspect, we analyze in detail the effect of different input/output indicator combinations on the performance of individual funds. Our empirical results show that VaR and CVaR, especially their combinations with traditional risk measures, are very helpful for comprehensively describing return distribution properties such as skewness and leptokurtosis, and can thus better evaluate the overall performance of mutual funds.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL:
    Download Restriction: Access to full text is restricted to subscribers.

    File URL:
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Article provided by World Scientific Publishing Co. Pte. Ltd. in its journal Asia-Pacific Journal of Operational Research.

    Volume (Year): 25 (2008)
    Issue (Month): 04 ()
    Pages: 421-450

    in new window

    Handle: RePEc:wsi:apjorx:v:25:y:2008:i:04:p:421-450
    Contact details of provider: Web page:

    Order Information: Email:

    No references listed on IDEAS
    You can help add them by filling out this form.

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:wsi:apjorx:v:25:y:2008:i:04:p:421-450. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Tai Tone Lim)

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.