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Computational Intelligence in Economics and Finance

  • Shu-Heng Chen
  • Paul P. Wang

Part of the Advanced Information Processing book series (AIP)

Table of contents

  1. Front Matter
    Pages I-XXII
  2. Introduction

    1. Front Matter
      Pages 1-1
    2. Shu-Heng Chen, Paul P. Wang
      Pages 3-55
  3. Fuzzy Logic and Rough Sets

  4. Artificial Neural Networks and Support Vector Machines

  5. Self-organizing Maps and Wavelets

    1. Front Matter
      Pages 201-201
    2. Shu-Heng Chen, Hongxing He
      Pages 203-216
    3. Dimitrios Moshou, Herman Ramon
      Pages 234-249
  6. Sequence Matching and Feature-Based Time Series Models

    1. Front Matter
      Pages 251-251
    2. Arnold Polanski
      Pages 253-261
    3. Weiqiang Lin, Mehmet A. Orgun, Graham J. Williams
      Pages 262-287
    4. Fernando Fernández-Rodríguez, Simón Sosvilla-Rivero, Julián Andrada-Félix
      Pages 297-325
  7. Evolutionary Computation, Swarm Intelligence and Simulated Annealing

    1. Front Matter
      Pages 327-327
    2. Shu-Heng Chen, Tzu-Wen Kuo
      Pages 329-347
    3. Fernando Álvarez, Néstor Carrasquero, Claudio Rocco
      Pages 348-357
    4. Graham Kendall, Jane M. Binner, Alicia M. Gazely
      Pages 358-368
    5. Chunfeng Wang, Xin Zhao, Li Kang
      Pages 369-386
  8. State Space Modeling of Time Series

    1. Front Matter
      Pages 403-403
    2. Andrew Hughes Hallett, Christian R. Richter
      Pages 420-435
  9. Agent-Based Models

  10. Back Matter
    Pages 467-480

About this book

Introduction

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.

Keywords

Artificial Intelligence Business Forecasting Finance Financial Data Mining Financial Engineering Pattern Matching Prediction Rough Sets Theory Self-Organizing Maps Simulation Wavelets classification databases knowledge management modeling

Editors and affiliations

  • Shu-Heng Chen
    • 1
  • Paul P. Wang
    • 2
  1. 1.AI-ECON Research Center Department of EconomicsNational Chengchi UniversityTaipeiTaiwan
  2. 2.Department of Electrical and Computer ScienceDuke UniversityDurhamUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-662-06373-6
  • Copyright Information Springer-Verlag Berlin Heidelberg 2004
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-07902-3
  • Online ISBN 978-3-662-06373-6
  • Buy this book on publisher's site