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.
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