IDEAS home Printed from
   My bibliography  Save this paper

Working with the XQC


  • Wolfgang Härdle
  • Heiko Lehmann


An enormous number of statistical methods have been developed in quantitive finance during the last decades. Nonparametric methods, bootstrapping time series, wavelets, estimation of diffusion coefficients are now almost standard in statistical applications. To implement these new methods the method developer usually uses a programming environment he is familiar with. Thus, such methods are only available for preselected software packages, but not for widely used standard software packages like MS Excel. To apply these new methods to empirical data a potential user faces a number of problems or it may even be impossible for him to use the methods without rewriting them in a different programming language. Even if one wants to apply a newly developed method to simulated data in order to understand the methodology one is confronted with the drawbacks described above. A very similar problem occurs in teaching statistics at undergraduate level. Since students usually have their preferred software and often do not have access to the same statistical software packages as their teacher, illustrating examples have to be executable with standard tools. In general, two statisticians are on either side of the distribution process of newly implemented methods, the provider (inventor) of a new technique (algorithm) and the user who wants to apply (understand) the new technique. The aim of the XploRe Quantlet client/server architecture is to bring these statisticians closer to each other. The XploRe Quantlet Client (XQC) represents the front end - the user interface (UI) of this architecture allowing to access the XploRe server and its methods and data. The XQC is fully programmed in Java not depending on a specific computer platform. It runs on Windows and Mac platforms as well as on Unix and Linux machines.

Suggested Citation

  • Wolfgang Härdle & Heiko Lehmann, 2005. "Working with the XQC," SFB 649 Discussion Papers SFB649DP2005-010, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  • Handle: RePEc:hum:wpaper:sfb649dp2005-010

    Download full text from publisher

    File URL:
    Download Restriction: no


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

    Cited by:

    1. Wolfgang Härdle & Sigbert Klinke & Uwe Ziegenhagen, 2006. "e-Learning Statistics - A Selective Review," SFB 649 Discussion Papers SFB649DP2006-024, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    More about this item


    XploRe Quantlet Client; quantitive finance; application; applet;

    JEL classification:

    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

    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:hum:wpaper:sfb649dp2005-010. 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: (RDC-Team). 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.