Working with the XQC

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.