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Springer Computational Intelligence in Economics and Finance - Springer

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Description

This Springer volume explores the application of computational intelligence methodologies to economics and finance forecasting, addressing challenges like non-linear relationships, behavioral changes, and domain-specific segmentation. Edited by Chen and Wang, the book covers traditional approaches including fuzzy logic, neural networks, and genetic algorithms, alongside cutting-edge technologies such as rough sets, support vector machines, wavelets, and ant colony optimisation. The collection demonstrates how advanced computational techniques enhance prediction accuracy and decision-making in financial markets and economic analysis, making it an essential resource for researchers, academics, and finance professionals seeking to understand and implement these sophisticated methodologies.

Key Features

Covers traditional computational intelligence methods including fuzzy logic, neural networks, and genetic algorithms applied to financial forecasting.

Includes recent technological approaches like rough sets, support vector machines, wavelets, and ant colony optimisation for advanced analysis.

Addresses specific economics and finance challenges such as non-linear relationships and behavioural changes in market data.

Edited by leading researchers Chen and Wang, providing expert perspectives on computational intelligence in financial applications.

Published by Springer, part of the Advanced Information Processing series for academic and professional finance study.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
16 September 2003
Listed Since
23 December 2006

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No barcode data available

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