Financial Decision Making Using Computational Intelligence

  • Michael Doumpos
  • Constantin Zopounidis
  • Panos M. Pardalos

Part of the Springer Optimization and Its Applications book series (SOIA, volume 70)

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Caslav Bozic, Stephan Chalup, Detlef Seese
    Pages 71-101
  3. Christian L. Dunis, Jason Laws, Andreas Karathanasopoulos
    Pages 103-127
  4. Konstantinos F. Xylogiannopoulos, Panagiotis Karampelas, Reda Alhajj
    Pages 129-157
  5. Alexandros Agapitos, Michael O’Neill, Anthony Brabazon
    Pages 159-188
  6. David Quintana, Cristobal Luque, Jose Maria Valls, Pedro Isasi
    Pages 189-208
  7. Simone Villa, Fabio Stella
    Pages 209-232
  8. Grigory A. Bautin, Valery A. Kalyagin
    Pages 233-251
  9. Enriqueta Vercher, José D. Bermúdez
    Pages 253-280
  10. Stefania Corsaro, Pasquale Luigi De Angelis, Zelda Marino, Paolo Zanetti
    Pages 281-319
  11. Back Matter
    Pages 321-324

About this book

Introduction

Financial Decision Making Using Computational Intelligence covers all the recent developments in complex financial decision making through computational intelligence approaches. Computational intelligence has evolved rapidly in recent years and it is now one of the most active fields in operations research and computer science. The increasing complexity of financial problems and the enormous volume of financial data often make it difficult to apply traditional modeling and algorithmic procedures. In this context, the field of computational intelligence provides a wide range of useful techniques, including new modeling tools for decision making under risk and uncertainty, data mining techniques for analyzing complex data bases, and powerful algorithms for complex optimization problems.

 

This book presents the recent advances made in financial decision making using computational intelligence, covering both new methodological developments as well as new emerging application areas. This work covers a wide range of topics related to financial decision making, financial modeling, risk management, and financial engineering, including algorithmic trading, financial time-series analysis, asset pricing, portfolio management, auction markets, and insurance services. Practitioners in the financial industry as well as operations researchers, management scientists, and data analysts will find this publication highly useful.

Keywords

Computational intelligence Data mining Evolutionary computation & metaheuristics Financial risk management Operations research

Editors and affiliations

  • Michael Doumpos
    • 1
  • Constantin Zopounidis
    • 2
  • Panos M. Pardalos
    • 3
  1. 1.Dept. Production Engineering, and ManagementTechnical University of CreteChaniaGreece
  2. 2., Department of Production Engineering andTechnical University of CreteChaniaGreece
  3. 3., Department of Industrial and Systems EngUniversity of FloridaGainesvilleUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4614-3773-4
  • Copyright Information Springer Science+Business Media New York 2012
  • Publisher Name Springer, Boston, MA
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-1-4614-3772-7
  • Online ISBN 978-1-4614-3773-4
  • Series Print ISSN 1931-6828
  • About this book