Genetic Algorithms and Genetic Programming in Computational Finance

  • Shu-Heng Chen

Table of contents

  1. Front Matter
    Pages i-xxi
  2. Genetic Algorithms and Genetic Programming in Computational Finance: An Overview of the Book

  3. Introduction

    1. Front Matter
      Pages 27-27
    2. Shu-Heng Chen, Tzu-Wen Kuo, Yuh-Pyng Shieh
      Pages 55-77
  4. Forecasting

    1. Front Matter
      Pages 79-79
    2. James D. Thomas, Katia Sycara
      Pages 81-102
    3. Nikolay Y. Nikolaev, Hitoshi Iba
      Pages 103-123
    4. Giuliano Armano, Michele Marchesi, Andrea Murru
      Pages 125-158
  5. Trading

    1. Front Matter
      Pages 159-159
    2. Edward P. K. Tsang, Jim Li
      Pages 161-174
    3. Michael O’Neill, Anthony Brabazon, Conor Ryan
      Pages 175-195
    4. Sze Sing Lam, Kai Pui Lam, Hoi Shing Ng
      Pages 197-217
  6. Miscellaneous Applications Domains

    1. Front Matter
      Pages 219-219
    2. Juan G. Lazo Lazo, Marco Aurélio C. Pacheco, Marley Maria R. Vellasco
      Pages 221-238
    3. Marco Aurélio C. Pacheco, Marley Maria R. Vellasco, Maíra F. de Noronha, Carlos Henrique P. Lopes
      Pages 239-247
    4. Thomas H. Noe, Jun Wang
      Pages 249-262
    5. Christopher J. Neely, Paul A. Weller
      Pages 263-279
    6. Sheri Markose, Edward Tsang, Hakan Er
      Pages 281-308
  7. Agent-Based Computational Finance

    1. Front Matter
      Pages 309-309

About this book

Introduction

After a decade of development, genetic algorithms and genetic programming have become a widely accepted toolkit for computational finance. Genetic Algorithms and Genetic Programming in Computational Finance is a pioneering volume devoted entirely to a systematic and comprehensive review of this subject. Chapters cover various areas of computational finance, including financial forecasting, trading strategies development, cash flow management, option pricing, portfolio management, volatility modeling, arbitraging, and agent-based simulations of artificial stock markets. Two tutorial chapters are also included to help readers quickly grasp the essence of these tools. Finally, a menu-driven software program, Simple GP, accompanies the volume, which will enable readers without a strong programming background to gain hands-on experience in dealing with much of the technical material introduced in this work.

Keywords

Arbitrage Finance Sage Simulation agents algorithms automatic programming cash flow genetic programming linear optimization modeling optimization

Editors and affiliations

  • Shu-Heng Chen
    • 1
  1. 1.Department of EconomicsNational Chengchi UniversityTaiwan

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4615-0835-9
  • Copyright Information Kluwer Academic Publishers 2002
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-5262-4
  • Online ISBN 978-1-4615-0835-9
  • About this book