Biologically Inspired Algorithms for Financial Modelling by Anthony Brabazon
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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Robot Evolution
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An Introduction to Metaheuristics for Optimization
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Deep Neural Evolution
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Lectures on Intelligent Systems
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Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms
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Coevolutionary Computation and Its Applications
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Visions of DNA Nanotechnology at 40 for the Next 40
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Cartesian Genetic Programming
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Bioinspired Computation in Combinatorial Optimization
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Self-organising Software
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Swarm Intelligence
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Evolution as Computation
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Algorithmic Bioprocesses
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General-Purpose Optimization Through Information Maximization
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Nature Inspired Optimisation for Delivery Problems
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Experimental Research in Evolutionary Computation
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Hyper-Heuristics: Theory and Applications
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Modelling in Molecular Biology
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Advances in Metaheuristics for Hard Optimization
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Foraging-Inspired Optimisation Algorithms
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Mobility in Process Calculi and Natural Computing
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Automating the Design of Data Mining Algorithms
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Contemporary Evolution Strategies
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Theory and Principled Methods for the Design of Metaheuristics
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Discrete and Topological Models in Molecular Biology
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Massively Parallel Evolutionary Computation on GPGPUs
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Multimodal Optimization by Means of Evolutionary Algorithms
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Computation in Living Cells
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Sensitivity Analysis for Neural Networks
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Reservoir Computing
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)| SKU | Unavailable |
| ISBN 13 | 9783642065736 |
| ISBN 10 | 3642065732 |
| Title | Biologically Inspired Algorithms for Financial Modelling |
| Author | Anthony Brabazon |
| Series | Natural Computing Series |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Springer |
| Year published | 2010-02-12 |
| Number of pages | 277 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |