Natural Computing in Computational Finance

By Michael O'Neill

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.

• Format: Paperback
• Language: English
• ISBN: 3642096204
• ISBN13: 9783642096204
• Release Date: October 2010
• Publisher: Springer
• Length: 303 Pages
• Weight: 0.98 lbs.
• Dimensions: 0.7" x 6.1" x 9.2"