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Natural Computing in Computational Finance

Volume 2

  • Book
  • © 2009

Overview

Editors:
  1. Anthony Brabazon

    1. University College Dublin, Belfield, Dublin, Ireland

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    You can also search for this editor in PubMed   Google Scholar

  2. Michael O’Neill

    1. University College Dublin, Belfield, Dublin, Ireland

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    You can also search for this editor in PubMed   Google Scholar

  • reports recent research results Computation Intelligence in Finance
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Computational Intelligence (SCI, volume 185)

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Table of contents (11 chapters)

  1. Front Matter

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  2. Natural Computing in Computational Finance (Volume 2): Introduction

    1. Natural Computing in Computational Finance (Volume 2): Introduction

      • Anthony Brabazon, Michael O’Neill
      Pages 1-5

  3. Part I Financial Modelling

    1. Front Matter

      Pages 7-7
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    2. Statistical Arbitrage with Genetic Programming

      • Philip Saks, Dietmar Maringer
      Pages 9-29

    3. Finding Relevant Variables in a Financial Distress Prediction Problem Using Genetic Programming and Self-organizing Maps

      • E. Alfaro-Cid, A. M. Mora, J. J. Merelo, A. I. Esparcia-Alcázar, K. Sharman
      Pages 31-49

    4. Ant Colony Optimization for Option Pricing

      • Sameer Kumar, Ruppa K. Thulasiram, Parimala Thulasiraman
      Pages 51-73

    5. A Neuro-Evolutionary Approach for Interest Rate Modelling

      • Robert Bradley, Anthony Brabazon, Michael O’Neill
      Pages 75-93

    6. Who’s Smart and Who’s Lucky? Inferring Trading Strategy, Learning and Adaptation in Financial Markets through Data Mining

      • Christopher R. Stephens, José Luis Gordillo, Enrique Martinéz Miranda
      Pages 95-114

  4. Part II Agent-Based Modelling

    1. Front Matter

      Pages 115-115
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    2. Financial Bubbles: A Learning Effect Modelling Approach

      • Tsung-Han Hsieh, Youwei Li, Donal G. McKillop
      Pages 117-135

    3. Evolutionary Computation and Artificial Financial Markets

      • Serafin Martinez-Jaramillo, Edward P. K. Tsang
      Pages 137-179

    4. Classical and Agent-Based Evolutionary Algorithms for Investment Strategies Generation

      • Rafał Dreżewski, Jan Sepielak, Leszek Siwik
      Pages 181-205

    5. Income Distribution and Lottery Expenditures in Taiwan: An Analysis Based on Agent-Based Simulation

      • Shu-Heng Chen, Bin-Tzong Chie, Hui-Fen Fan, Tina Yu
      Pages 207-223

    6. The Emergence of a Market: What Efforts Can Entrepreneurs Make?

      • Shuyuan Wu, Anthony Brabazon
      Pages 225-243

  5. Back Matter

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Keywords

About this book

Recent years have seen the widespread application of Natural Computing algorithms (broadly defined in this context as computer algorithms whose design draws inspiration from phenomena in the natural world) for the purposes of financial modelling and optimisation. A related stream of work has also seen the application of learning mechanisms drawn from Natural Computing algorithms for the purposes of agent-based modelling in finance and economics. In this book we have collected a series of chapters which illustrate these two faces of Natural Computing. The first part of the book illustrates how algorithms inspired by the natural world can be used as problem solvers to uncover and optimise financial models. The second part of the book examines a number agent-based simulations of financial systems.

This book follows on from Natural Computing in Computational Finance (Volume 100 in Springer’s Studies in Computational Intelligence series) which in turn arose from the success of EvoFIN 2007, the very first European Workshop on Evolutionary Computation in Finance & Economics held in Valencia, Spain in April 2007.

Editors and Affiliations

  • University College Dublin, Belfield, Dublin, Ireland

    Anthony Brabazon, Michael O’Neill

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