B. Chopard M. Oussaidene, M. Tomassini and O. Pictet
We have selected a problem which presents a considerable interest from the point of view of financial predictions and which, also, is representative of a class of very hard optimization problems. More precisely, this application concerns the construction of search algorithms for indicators of the future price movements of currency exchange rates by treating very large data sets of time series data.
We propose to address this particular problem in the framework of the parallel genetic programming and to elaborate a basic library of programs for solving efficiently other optimization problems such as those which are common in practical industrial and economical applications.