Biologically Inspired Algorithms for Financial Modelling

• Methodologies.- Neural Network Methodologies.- Evolutionary Methodologies.- Grammatical Evolution.- The Particle Swarm Model.- Ant Colony Models.- Artificial Immune Systems.- Model Development.- Model Development Process.- Technical Analysis.- Case Studies.- Overview of Case Studies.- Index Prediction Using MLPs.- Index Prediction Using a MLP-GA Hybrid.- Index Trading Using Grammatical Evolution.- Adaptive Trading Using Grammatical Evolution.- Intra-day Trading Using Grammatical Evolution.- Automatic Generation of Foreign Exchange Trading Rules.- Corporate Failure Prediction Using Grammatical Evolution.- Corporate Failure Prediction Using an Ant Model.- Bond Rating Using Grammatical Evolution.- Bond Rating Using AIS.- Wrap-up.

From the reviews: "Anthony Brabazon and Michael O'Neill ... have just published an interesting book that introduces a wide range of biologically inspired algorithms and their applications in financial modelling. ... This book is a well-written, easy to read, brief introduction to the state-of-the-art biologically inspired algorithms." (Mak Kaboudan, Genetic Programming and Evolvable Machines, Vol. 7, 2006) "The objective of this book is to provide an introduction to biologically inspired algorithms and some tightly scoped practical examples in finance. ... provides some new insights and alternative tools for the financial modelling toolbox. ... The goal and objective of the book is to provide practical examples using these evolutionary algorithms and it does that decently ... . Overall I found the book very enlightening ... and it has provided ideas and alternative ways to think about solutions." (Brad G. Kyer, SIGACT News, Vol. 40 (4), 2009)