Advanced Search
MyIDEAS: Login

Value-at-risk forecasts under scrutiny—the German experience

Contents:

Author Info

  • Stefan Jaschke
  • Gerhard Stahl
  • Richard Stehle
Registered author(s):

    Abstract

    We present an analysis of the VaR forecasts and the P&L series of all 12 German banks that used internal models for regulatory purposes throughout the period from the beginning of 2001 to the end of 2004. One task of a supervisor is to estimate the 'recalibration factor', i.e. by how much a bank over- or underestimates its VaR. The Basel traffic light approach to backtesting, which maps the count of exceptions in the trailing year to a multiplicative penalty factor, can be viewed as a way to estimate the 'recalibration factor'. We introduce techniques that provide a much more powerful inference on the recalibration factor than the Basel approach based on the count of exceptions. The notions 'return on VaR (RoVaR)' and 'well-behaved forecast system' are keys to linking the problem at hand to the established literature on the evaluation of density forecasts. We perform extensive bootstrapping analyses allowing (1) an assessment of the accuracy of our estimates of the recalibration factor and (2) a comparison of the estimation error of different scale and quantile estimators. Certain robust estimators turn out to outperform the more popular estimators used in the literature. Empirical results for the non-public data are compared to the corresponding results for hypothetical portfolios based on publicly available market data. While these comparisons have to be interpreted with care since the banks' P&L data tend to be more contaminated with errors than the major market indices, they shed light on the similarities and differences between banks' RoVaRs and market index returns.

    Download Info

    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: http://www.tandfonline.com/doi/abs/10.1080/14697680600999104
    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.

    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal Quantitative Finance.

    Volume (Year): 7 (2007)
    Issue (Month): 6 ()
    Pages: 621-636

    as in new window
    Handle: RePEc:taf:quantf:v:7:y:2007:i:6:p:621-636

    Contact details of provider:
    Web page: http://www.tandfonline.com/RQUF20

    Order Information:
    Web: http://www.tandfonline.com/pricing/journal/RQUF20

    Related research

    Keywords: Banking supervision; VaR; Exploratory data analysis; Backtesting;

    References

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

    Citations

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

    Cited by:
    1. Sibbertsen, Philipp & Stahl, Gerhard & Luedtke, Corinna, 2008. "Measuring Model Risk," Hannover Economic Papers (HEP) dp-409, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Lists

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

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:taf:quantf:v:7:y:2007:i:6:p:621-636. 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: (Michael McNulty).

    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.