Titlebook: Natural Computing in Computational Finance; Anthony Brabazon (Head of Research),Michael O’Neil Book 2008 Springer-Verlag Berlin Heidelberg

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Anthony Brabazon (Head of Research),Michael O’NeilReports recent research results on natural computation in computational economics and finance.Includes supplementary material:

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Natural Computing in Computational Finance978-3-540-77477-8Series ISSN 1860-949X Series E-ISSN 1860-9503

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https://doi.org/10.1007/978-3-540-77477-8agent-based model; agent-based modeling; algorithm; algorithms; differential evolution; evolution; evoluti

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Evolutionary Strategies for Building Risk-Optimal Portfoliosk measures and proposes three evolutionary algorithms to solve the optimization problem. In order to validate the approach proposed, results of a number of experiments using data from the Paris Stock Exchange are presented.

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Co-Evolutionary Multi-Agent System for Portfolio Optimizationiversity. In this chapter the concept and a formal model of an agent-based realization of a predator-prey coevolutionary algorithm is presented. The resulting system is applied to the problem of effective portfolio building and is compared to classical multi-objective evolutionary algorithms.

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Natural Computing in Computational Finance: An Introductionems and phenomena that occur in the natural world. The inspiration for natural computing methodologies typically stem from real-world phenomena which exist in high-dimensional, noisy and uncertain, dynamic environments. These are characteristics which fit well with the nature of financial markets. P

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An Evolutionary Approach to Asset Allocation in Defined Contribution Pension Schemesfolio asset allocation approach is far from being appropriate since the asset allocation problem faced by defined contribution pension schemes is fundamentally different. There have been many attempts to solve the problem analytically. However, most of these analytical solutions fail to incorporate