Natural Computing in Computational Finance

Optimisation.- Natural Computing in Computational Finance: An Introduction.- Constrained Index Tracking under Loss Aversion Using Differential Evolution.- An Evolutionary Approach to Asset Allocation in Defined Contribution Pension Schemes.- Evolutionary Strategies for Building Risk-Optimal Portfolios.- Evolutionary Stochastic Portfolio Optimization.- Non-linear Principal Component Analysis of the Implied Volatility Smile using a Quantum-inspired Evolutionary Algorithm.- Estimation of an EGARCH Volatility Option Pricing Model using a Bacteria Foraging Optimisation Algorithm.- Model Induction.- Fuzzy-Evolutionary Modeling for Single-Position Day Trading.- Strong Typing, Variable Reduction and Bloat Control for Solving the Bankruptcy Prediction Problem Using Genetic Programming.- Using Kalman-filtered Radial Basis Function Networks for Index Arbitrage in the Financial Markets.- On Predictability and Profitability: Would GP Induced Trading Rules be Sensitive to the Observed Entropy of Time Series?.- Hybrid Neural Systems in Exchange Rate Prediction.- Agent-based Modelling.- Evolutionary Learning of the Optimal Pricing Strategy in an Artificial Payment Card Market.- Can Trend Followers Survive in the Long-Run% Insights from Agent-Based Modeling.- Co-Evolutionary Multi-Agent System for Portfolio Optimization.

Anthony Brabazon [B. Comm (UCD), DPA (UCD), Dip Stats (Dub), MS (Statistics) (Stanford), MS (Operations Research) (Stanford), MBA (Heriot-Watt), DBA (Kingston), FCA, ACMA] lectures at University College Dublin. His research interests include mathematical decision models, evolutionary computation, and the application of computational intelligence to the domain of finance. He has published in excess of 100 papers in journals, conferences and professional publications, and has been a member of the programme committee at both EuroGP and GECCO conferences, as well as acting as reviewer for several journals. He has also acted as consultant to a wide range of public and private companies in several countries. He currently serves as a member of the CCAB (Ireland) Consultative Committee on Accounting Standards, and is a former Secretary and Treasurer of the Irish Accounting and Finance Association. Prior to joining UCD, he worked in the banking sector, and for KPMG.
Michael O'Neill [BSc. (UCD), PhD (UL)] is a lecturer in the Department of Computer Science and Information Systems at the University of Limerick. He has over 70 publications on biologically inspired algorithms (BIAs). He coauthored the Springer title "Grammatical Evolution -- Evolutionary Automatic Programming in an Arbitrary Language", Genetic Programming Series, 2003, 160 pp., ISBN 1-4020-7444-1. He is one of the two original developers of the Grammatical Evolution algorithm, research that spawned an annual invited tutorial at the largest evolutionary computation conference and an international workshop, and is also on a number of relevant organising committees (e.g., GECCO 2005). Michael is a regular reviewer for the leading evolutionary computation (EC) journals, namely IEEE Trans. on Evolutionary Computation, MIT Press's Evolutionary Computation, and Springer's Genetic Programming and Evolvable Hardware journal.