IDEAS home Printed from
   My bibliography  Save this paper

Liquidity Risk Estimation Using Fuzzy Measure Theory


  • Sebastián Alberto Rey


  • Javier Ignacio García-Fronti


  • María Teresa Casparri



One of the most relevant issues in the risk analysis of the financial institutions´ investments is to determine the capital allocation in order to maintain its solvency and liquidity in adverse situations. The portfolio risk analysis is necessary for assuring the right selection of that capital to be allocated. Each portfolio has a market risk. This risk is directly related to the losses that can be caused by adverse fluctuations of the portfolio asset prices. In this sense, it is necessary to construct a measure able to quantify the potential losses associated with that exposure. The classical Value-at-Risk measures the pure market risk; therefore, it does not bear some considerations. If a financial institution uses this classical framework to determine the quantity of capital to allocate in order to face its obligations with a certain level of confidence, then the institution does not take into account the partial or total portfolio liquidation consequences at the claim moment. To take into account these consequences is crucial because the number of assets to be sold in the market has an important influence in the price at which the transaction will be made. This influence is determined by the market liquidity at that moment. When these problems take place the financial institution could have liquidity problems to cancel its obligations. This paper develops and applies a Value-at-Risk model regarding prices fluctuations and potential market liquidity problems. Due to uncertainty of market liquidity in the future, the model includes Fuzzy Measure Theory . The first section of the paper presents some fundamental concepts of Fuzzy Measure Theory and Extreme Value Theory . The second section presents a “fuzzified” risk valuation model under the classical assumption of normal distribution for the investment returns; and, taking into consideration the Argentinean financial crisis, also presents the model under an Extreme Value Theory distribution. Both alternatives are applied to a portfolio of Repsol-YPF stocks so as to estimate the risk assumed by the holder.

Suggested Citation

  • Sebastián Alberto Rey & Javier Ignacio García-Fronti & María Teresa Casparri, 2005. "Liquidity Risk Estimation Using Fuzzy Measure Theory," Finance 0504012, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpfi:0504012
    Note: Type of Document - pdf; pages: 17. PDF file

    Download full text from publisher

    File URL:
    Download Restriction: no

    More about this item


    Liquidity risk; Argentina; fuzzy measure;

    JEL classification:

    • G - Financial Economics

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:wpa:wuwpfi:0504012. 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: (EconWPA). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.