An enormous number of statistical methods have been developed in quantitivefinance during the last decades. Nonparametric methods, bootstrapping timeseries, wavelets, estimation of diffusion coefficients are now almost standard instatistical applications. To implement these new methods the method developerusually uses a programming environment he is familiar with. Thus, suchmethods are only available for preselected software packages, but not for widelyused standard software packages like MS Excel. To apply these new methodsto empirical data a potential user faces a number of problems or it may evenbe impossible for him to use the methods without rewriting them in a differentprogramming language. Even if one wants to apply a newly developed methodto simulated data in order to understand the methodology one is confrontedwith the drawbacks described above. A very similar problem occurs in teachingstatistics at undergraduate level. Since students usually have their preferredsoftware and often do not have access to the same statistical software packagesas their teacher, illustrating examples have to be executable with standardtools.
In general, two statisticians are on either side of the distribution process ofnewly implemented methods, the provider (inventor) of a new technique (algorithm)and the user who wants to apply (understand) the new technique. Theaim of the XploRe Quantlet client/server architecture is to bring these statisticianscloser to each other. The XploRe Quantlet Client (XQC) represents thefront end - the user interface (UI) of this architecture allowing to access theXploRe server and its methods and data. The XQC is fully programmed inJava not depending on a specific computer platform. It runs on Windows andMac platforms as well as on Unix and Linux machines.
