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Computational Intelligence in Economics and Finance

  • Book
  • © 2004

Overview

Editors:
  1. Shu-Heng Chen

    1. AI-ECON Research Center Department of Economics, National Chengchi University, Taipei, Taiwan

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  2. Paul P. Wang

    1. Department of Electrical and Computer Science, Duke University, Durham, USA

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Advanced Information Processing (AIP)

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Table of contents (23 chapters)

  1. Front Matter

    Pages I-XXII
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  2. Introduction

    1. Front Matter

      Pages 1-1
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    2. Computational Intelligence in Economics and Finance

      • Shu-Heng Chen, Paul P. Wang
      Pages 3-55

  3. Fuzzy Logic and Rough Sets

    1. Front Matter

      Pages 57-57
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    2. Intelligent System to Support Judgmental Business Forecasting: the Case of Estimating Hotel Room Demand

      • Mounir Ben Ghalia, Paul P. Wang
      Pages 59-92

    3. Fuzzy Investment Analysis Using Capital Budgeting and Dynamic Programming Techniques

      • Cengiz Kahraman, Cafer Erhan Bozdağ
      Pages 93-128

    4. Rough Sets Theory and Multivariate Data Analysis in Classification Problems: a Simulation Study

      • Michael Doumpos, Constantin Zopounidis
      Pages 129-147

  4. Artificial Neural Networks and Support Vector Machines

    1. Front Matter

      Pages 149-149
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    2. Forecasting the Opening Cash Price Index in Integrating Grey Forecasting and Neural Networks: Evidence from the SGX-DT MSCI Taiwan Index Futures Contracts

      • Tian-Shyug Lee, Nen-Jing Chen, Chih-Chou Chiu
      Pages 151-170

    3. A Support Vector Machine Model for Currency Crises Discrimination

      • Claudio M. Rocco, José Alí Moreno
      Pages 171-181

    4. Saliency Analysis of Support Vector Machines for Feature Selection in Financial Time Series Forecasting

      • Lijuan Cao, Francis E. H. Tay
      Pages 182-199

  5. Self-organizing Maps and Wavelets

    1. Front Matter

      Pages 201-201
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    2. Searching Financial Patterns with Self-organizing Maps

      • Shu-Heng Chen, Hongxing He
      Pages 203-216

    3. Effective Position of European Firms in the Face of Monetary Integration Using Kohonen’s SOFM

      • Raquel Flórez López
      Pages 217-233

    4. Financial Applications of Wavelets and Self-organizing Maps

      • Dimitrios Moshou, Herman Ramon
      Pages 234-249

  6. Sequence Matching and Feature-Based Time Series Models

    1. Front Matter

      Pages 251-251
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    2. Pattern Matching in Multidimensional Time Series

      • Arnold Polanski
      Pages 253-261

    3. Structural Pattern Discovery in Time Series Databases

      • Weiqiang Lin, Mehmet A. Orgun, Graham J. Williams
      Pages 262-287

    4. Are Efficient Markets Really Efficient?: Can Financial Econometric Tests Convince Machine-Learning People?

      • Shu-Heng Chen, Tzu-Wen Kuo
      Pages 288-296

    5. Nearest-Neighbour Predictions in Foreign Exchange Markets

      • Fernando Fernández-Rodríguez, Simón Sosvilla-Rivero, Julián Andrada-Félix
      Pages 297-325
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Keywords

About this book

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.

Editors and Affiliations

  • AI-ECON Research Center Department of Economics, National Chengchi University, Taipei, Taiwan

    Shu-Heng Chen

  • Department of Electrical and Computer Science, Duke University, Durham, USA

    Paul P. Wang

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