Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)
By Anthony Brabazon and Michael O'Neill

"Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)" is published by Springer in February 10, 2006, it has 275 pages and the language of the book is English.
“Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)” Metadata:
- Title: ➤ Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)
- Authors: Anthony BrabazonMichael O'Neill
- Language: English
- Number of Pages: 275
- Publisher: Springer
- Publish Date: February 10, 2006
“Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)” Subjects and Themes:
- Subjects: ➤ Mathematical models - Finance - Computer simulation - Information theory - Banks and banking - Operations research - Computer science - Computer algorithms - Neural networks (computer science) - Theory of Computation - Quantitative Finance - Simulation and Modeling - Operations Research/Decision Theory - Finance /Banking - Computer Applications
Edition Specifications:
- Format: Hardcover
- Weight: 15.2 ounces
- Dimensions: 9.5 x 6.3 x 0.8 inches
Edition Identifiers:
- The Open Library ID: OL9055668M - OL18346942W
- Library of Congress Control Number (LCCN): 2005936099
- ISBN-13: 9783540262527
- ISBN-10: 3540262520
- All ISBNs: 3540262520 - 9783540262527
AI-generated Review of “Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)”:
"Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)" Description:
The Open Library:
Predicting the future for financial gain is a difficult, sometimes profitable activity. The focus of this book is the application of biologically inspired algorithms (BIAs) to financial modelling. In a detailed introduction, the authors explain computer trading on financial markets and the difficulties faced in financial market modelling. Then Part I provides a thorough guide to the various bioinspired methodologies – neural networks, evolutionary computing (particularly genetic algorithms and grammatical evolution), particle swarm and ant colony optimization, and immune systems. Part II brings the reader through the development of market trading systems. Finally, Part III examines real-world case studies where BIA methodologies are employed to construct trading systems in equity and foreign exchange markets, and for the prediction of corporate bond ratings and corporate failures. The book was written for those in the finance community who want to apply BIAs in financial modelling, and for computer scientists who want an introduction to this growing application domain.
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