Natural Computing in Computational Finance
Anthony Brabazon, Michael O'Neill
Springer Science & Business Media, May 9, 2008 - Mathematics - 303 pages
Natural Computing in Computational Finance is a innovative volume containing fifteen chapters which illustrate cutting-edge applications of natural computing or agent-based modeling in modern computational finance. Following an introductory chapter the book is organized into three sections. The first section deals with optimization applications of natural computing demonstrating the application of a broad range of algorithms including, genetic algorithms, differential evolution, evolution strategies, quantum-inspired evolutionary algorithms and bacterial foraging algorithms to multiple financial applications including portfolio optimization, fund allocation and asset pricing. The second section explores the use of natural computing methodologies such as genetic programming, neural network hybrids and fuzzy-evolutionary hybrids for model induction in order to construct market trading, credit scoring and market prediction systems. The final section illustrates a range of agent-based applications including the modeling of payment card and financial markets. Each chapter provides an introduction to the relevant natural computing methodology as well as providing a clear description of the financial application addressed.
The book was written to be accessible to a wide audience and should be of interest to practitioners, academics and students, in the fields of both natural computing and finance.
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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 RiskOptimal Portfolios
Evolutionary Stochastic Portfolio Optimization
Nonlinear Principal Component Analysis of the Implied Volatility Smile using a Quantuminspired Evolutionary Algorithm
Estimation of an EGARCH Volatility Option Pricing Model using a Bacteria Foraging Optimisation Algorithm
Strong Typing Variable Reduction and Bloat Control for Solving the Bankruptcy Prediction Problem Using Genetic Programming
Using Kalmanﬁltered 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
Evolutionary Learning of the Optimal Pricing Strategy in an Artiﬁcial Payment Card Market
Can Trend Followers Survive in the LongRun? Insights from AgentBased Modeling
CoEvolutionary MultiAgent System for Portfolio Optimization
Other editions - View all
Natural Computing in Computational Finance, Volume 2
Anthony Brabazon,Michael O'Neill
Limited preview - 2009