Computational Intelligence in Economics and Finance [electronic resource] /

Due to the ability to handle specific characteristics of economics and finance forecasting problems like e.g. non-linear relationships, behavioral changes, or knowledge-based domain segmentation, we have recently witnessed a phenomenal growth of the application of computational intelligence methodologies in this field. In this volume, Chen and Wang collected not just works on traditional computational intelligence approaches like fuzzy logic, neural networks, and genetic algorithms, but also examples for more recent technologies like e.g. rough sets, support vector machines, wavelets, or ant algorithms. After an introductory chapter with a structural description of all the methodologies, the subsequent parts describe novel applications of these to typical economics and finance problems like business forecasting, currency crisis discrimination, foreign exchange markets, or stock markets behavior.

Bibliographic Details

Main Authors:	Chen, Shu-Heng. editor., Wang, Paul P. editor., SpringerLink (Online service)
Format:	Texto biblioteca
Language:	eng
Published:	Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2004
Subjects:	Finance., Mathematical statistics., Artificial intelligence., Application software., Game theory., Econometrics., Economics., Artificial Intelligence (incl. Robotics)., Finance, general., Probability and Statistics in Computer Science., Computer Appl. in Administrative Data Processing., Game Theory, Economics, Social and Behav. Sciences.,
Online Access:	http://dx.doi.org/10.1007/978-3-662-06373-6
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