Authors:
- Delivers theoretical and practical knowledge on finance and evolutionary economics
- Presents an overview of evolutionary methods for computational finances and provides workable simulators for end-users
- Written by leading experts in the field
Part of the book series: Adaptation, Learning, and Optimization (ALO, volume 11)
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Table of contents (7 chapters)
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Front Matter
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Back Matter
About this book
“Practical Applications of Evolutionary Computation to Financial Engineering” presents the state of the art techniques in Financial Engineering using recent results in Machine Learning and Evolutionary Computation. This book bridges the gap between academics in computer science and traders and explains the basic ideas of the proposed systems and the financial problems in ways that can be understood by readers without previous knowledge on either of the fields. To cement the ideas discussed in the book, software packages are offered that implement the systems described within.
The book is structured so that each chapter can be read independently from the others. Chapters 1 and 2 describe evolutionary computation. The third chapter is an introduction to financial engineering problems for readers who are unfamiliar with this area. The following chapters each deal, in turn, with a different problem in the financial engineering field describing each problem in detail and focusing on solutions based on evolutionary computation. Finally, the two appendixes describe software packages that implement the solutions discussed in this book, including installation manuals and parameter explanations.
Authors and Affiliations
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School of Engineering, Dept. Information &, University of Tokyo, Tokyo, Japan
Hitoshi Iba
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School of Frontier Sciences, Department of Frontier Informatics, The University of Tokyo, Tokyo, Japan
Claus C. Aranha
Bibliographic Information
Book Title: Practical Applications of Evolutionary Computation to Financial Engineering
Book Subtitle: Robust Techniques for Forecasting, Trading and Hedging
Authors: Hitoshi Iba, Claus C. Aranha
Series Title: Adaptation, Learning, and Optimization
DOI: https://doi.org/10.1007/978-3-642-27648-4
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Berlin Heidelberg 2012
Hardcover ISBN: 978-3-642-27647-7Published: 18 February 2012
Softcover ISBN: 978-3-662-52022-2Published: 23 August 2016
eBook ISBN: 978-3-642-27648-4Published: 15 February 2012
Series ISSN: 1867-4534
Series E-ISSN: 1867-4542
Edition Number: 1
Number of Pages: XII, 248
Topics: Computational Intelligence, Artificial Intelligence, Finance, general