Natural Computing in Computational Finance

  • Anthony Brabazon
  • Michael O’Neill

Part of the Studies in Computational Intelligence book series (SCI, volume 100)

Table of contents

  1. Front Matter
    Pages I-X
  2. Optimisation

  3. Model Induction

  4. Agent-based Modelling

    1. Biliana Alexandrova-Kabadjova, Edward Tsang, Andreas Krause
      Pages 233-251
    2. Xue-Zhong He, Philip Hamill, Youwei Li
      Pages 253-269
    3. Rafał Dreżewski, Leszek Siwik
      Pages 271-299
  5. Back Matter
    Pages 301-303

About this book

Introduction

Natural Computing in Computational Finance is a innovative volume containing fifteen chapters which illustrate cutting-edge applications of natural computing or agent-based modeling in modern computational finance. Following an introductory chapter the book is organized into three sections. The first section deals with optimization applications of natural computing demonstrating the application of a broad range of algorithms including, genetic algorithms, differential evolution, evolution strategies, quantum-inspired evolutionary algorithms and bacterial foraging algorithms to multiple financial applications including portfolio optimization, fund allocation and asset pricing. The second section explores the use of natural computing methodologies such as genetic programming, neural network hybrids and fuzzy-evolutionary hybrids for model induction in order to construct market trading, credit scoring and market prediction systems. The final section illustrates a range of agent-based applications including the modeling of payment card and financial markets. Each chapter provides an introduction to the relevant natural computing methodology as well as providing a clear description of the financial application addressed.

The book was written to be accessible to a wide audience and should be of interest to practitioners, academics and students, in the fields of both natural computing and finance.

Keywords

agent-based model agent-based modeling algorithm algorithms differential evolution evolution evolutionary algorithm fuzzy genetic programming model modeling natural computing network optimization programming

Editors and affiliations

  • Anthony Brabazon
    • 1
  • Michael O’Neill
    • 2
  1. 1.School of Business Quinn SchoolUniversity College DublinDublin 4Ireland
  2. 2.Natural Computing Research and Applications School of Computer Science and InformaticsUniversity College DublinDublin 4Ireland

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-77477-8
  • Copyright Information Springer-Verlag Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-77476-1
  • Online ISBN 978-3-540-77477-8
  • Series Print ISSN 1860-949X
  • About this book