Natural Computing in Computational Finance
Volume 4
Editors: Brabazon, Anthony, O'Neill, Michael, Maringer, Dietmar (Eds.)
Free Preview- Recent research in Natural Computing in Computational Finance
- Carefully edited book
- Written by leading experts in the field
Buy this book
- About this book
-
This book follows on from Natural Computing in Computational Finance Volumes I, II and III. As in the previous volumes of this series, the book consists of a series of chapters each of
which was selected following a rigorous, peer-reviewed, selection process. The chapters illustrate the application of a range of cutting-edge natural computing and agent-based methodologies in computational finance and economics.
The applications explored include option model calibration, financial trend reversal detection, enhanced indexation, algorithmic trading, corporate payout determination and agent-based modeling of liquidity costs, and trade strategy adaptation. While describing cutting edge applications, the chapters are
written so that they are accessible to a wide audience. Hence, they should be of interest to academics, students and practitioners in the fields of computational finance and economics.
which was selected following a rigorous, peer-reviewed, selection process. The chapters illustrate the application of a range of cutting-edge natural computing and agent-based methodologies in computational finance and economics.
The applications explored include option model calibration, financial trend reversal detection, enhanced indexation, algorithmic trading, corporate payout determination and agent-based modeling of liquidity costs, and trade strategy adaptation. While describing cutting edge applications, the chapters are
written so that they are accessible to a wide audience. Hence, they should be of interest to academics, students and practitioners in the fields of computational finance and economics.
The applications explored include option model calibration, financial trend reversal detection, enhanced indexation, algorithmic trading, corporate payout determination and agent-based modeling of liquidity costs, and trade strategy adaptation. While describing cutting edge applications, the chapters are
written so that they are accessible to a wide audience. Hence, they should be of interest to academics, students and practitioners in the fields of computational finance and economics.
written so that they are accessible to a wide audience. Hence, they should be of interest to academics, students and practitioners in the fields of computational finance and economics.
- Table of contents (10 chapters)
-
-
Natural Computing in Computational Finance (Volume 4): Introduction
Pages 1-8
-
Calibrating Option Pricing Models with Heuristics
Pages 9-37
-
A Comparison between Nature-Inspired and Machine Learning Approaches to Detecting Trend Reversals in Financial Time Series
Pages 39-59
-
A Soft Computing Approach to Enhanced Indexation
Pages 61-77
-
Parallel Evolutionary Algorithms for Stock Market Trading Rule Selection on Many-Core Graphics Processors
Pages 79-92
-
Table of contents (10 chapters)
Buy this book
Services for this Book
Recommended for you
Bibliographic Information
- Bibliographic Information
-
- Book Title
- Natural Computing in Computational Finance
- Book Subtitle
- Volume 4
- Editors
-
- Anthony Brabazon
- Michael O'Neill
- Dietmar Maringer
- Series Title
- Studies in Computational Intelligence
- Series Volume
- 380
- Copyright
- 2012
- Publisher
- Springer-Verlag Berlin Heidelberg
- Copyright Holder
- Springer-Verlag GmbH Berlin Heidelberg
- eBook ISBN
- 978-3-642-23336-4
- DOI
- 10.1007/978-3-642-23336-4
- Hardcover ISBN
- 978-3-642-23335-7
- Softcover ISBN
- 978-3-662-51998-1
- Series ISSN
- 1860-949X
- Edition Number
- 1
- Number of Pages
- X, 202
- Topics
