No theory of structural exchange rate determination has yet been found that performs well in prediction experiments. Only very seldom has the simple random walk model been significantly outperformed. Referring to three, sometimes highly nonlinear, monetary and nonmonetary structural exchange...

We present a novel regression method that combines projection pursuit regression with feed forward neural networks. The algorithm is presented and compared to standard neural network learning. Connectionist projection pursuit regression (CPPR) is applied to modelling the U.S. average...

In the economics literature on exchange rate determination, no theory has yet been found that performs well in out-of-sample prediction experiments. Until today, the simple random walk model has never been significantly outperformed. We have identified a set of fundamental long-run exchange rate...

Correctness, transparency and effectiveness are the principalattributes of knowledge derived from databases. In current data miningresearch there is a focus on efficiency improvement of algorithms forknowledge discovery. However important limitations of data mining canonly be dissolved by the...

In this paper, we describe an extension of the datamining framework with automated causal diagnosis, offering the possibility to automatically detect and explain exceptional values to support business decision tasks. This functionality can be built into the conventional OLAP (On-Line Analytical...

The purpose of OLAP (On-Line Analytical Processing) systems is to provide a framework for the analysis of multidimensional data. Many tasks related to analysing multidimensional data and making business decisions are still carried out manually by analysts (e.g. financial analysts, accountants,...