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Evolutionary Computation in Economics and Finance

  • Book
  • © 2002

Overview

Editors:
  1. Shu-Heng Chen

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

  • First book focusing on the application of evolutionary computation to economics and finance
  • Historical review (chap. 1)
  • Brief survey with bibliography (more than 380 papers ever published in this field)
  • Information on websites, conferences, computer software
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 100)

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About this book

After a decade's development, evolutionary computation (EC) proves to be a powerful tool kit for economic analysis. While the demand for this equipment is increasing, there is no volume exclusively written for economists. This volume for the first time helps economists to get a quick grasp on how EC may support their research. A comprehensive coverage of the subject is given, that includes the following three areas: game theory, agent-based economic modelling and financial engineering. Twenty leading scholars from each of these areas contribute a chapter to the volume. The reader will find himself treading the path of the history of this research area, from the fledgling stage to the burgeoning era. The results on games, labour markets, pollution control, institution and productivity, financial markets, trading systems design and derivative pricing, are new and interesting for different target groups. The book also includes informations on web sites, conferences, and computer software.

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Table of contents (22 chapters)

  1. Front Matter

    Pages I-XII
    Download chapter PDF

  3. Games

    1. Front Matter

      Pages 29-29
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    2. Playing Games with Genetic Algorithms

      • Robert E. Marks
      Pages 31-44

    3. Genetic Algorithm Learning and Economic Evolution

      • Thomas Riechmann
      Pages 45-60

    4. Using Symbolic Regression to Infer Strategies from Experimental Data

      • John Duffy, Jim Engle-Warnick
      Pages 61-82

  4. Agent-Based Computation Economics

    1. Front Matter

      Pages 83-83
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    2. The Efficiency of an Artificial Double Auction Stock Market with Neural Learning Agents

      • Jing Yang
      Pages 85-105

    3. On AIE-ASM: Software to Simulate Artificial Stock Markets with Genetic Programming

      • Shu-Heng Chen, Chia-Husan Yeh, Chung-Chih Liao
      Pages 107-122

    4. Exchange Rate Volatility in the Artificial Foreign Exchange Market

      • Jasmina Arifovic
      Pages 123-134

    5. Using an Artificial Market Approach to Analyze Exchange Rate Scenarios

      • Kiyoshi Izumi, Kazuhiro Ueda
      Pages 135-157

    6. Emulating Trade in Emissions Permits: An Application of Genetic Algorithms

      • Rosalyn Bell, Stephen Beare
      Pages 159-173

    7. Cooperative Computation with Market Mechanism

      • Masayuki Ishinishi, Hiroshi Sato, Akira Namatame
      Pages 175-188

    8. Hysteresis in an Evolutionary Labor Market with Adaptive Search

      • Leigh Tesfatsion
      Pages 189-210

    9. Computable Learning, Neural Networks and Institutions

      • Francesco Luna
      Pages 211-232

    10. On Two Types of GA-Learning

      • Nicolaas J. Vriend
      Pages 233-243

    11. Evolutionary Computation and Economic Models: Sensitivity and Unintended Consequences

      • David B. Fogel, Kumar Chellapilla, Peter J. Angeline
      Pages 245-269

  5. Financial Engineering

    1. Front Matter

      Pages 271-271
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    2. Tinkering with Genetic Algorithms: Forecasting and Data Mining in Finance and Economics

      • George G. Szpiro
      Pages 273-286
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Editors and Affiliations

  • AI-ECON Research Center, Department of Economics, National Chengchi University, Taipei, Taiwan, R. O. China

    Shu-Heng Chen

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