Chen S.-H. (ed.) Genetic Algorithms and Genetic Programming in Computational Finance

Kluwer, 2002. — 491.The applications of genetic algorithms and genetic programming to computation finance have been seen over the last decade in various journal publications, chapters in books, and magazine articles. Their relevance to computational finance is further strengthened when these tools are already deployed and used in many financial firms. Given the trend, these tools seem to deserve an independent place in computation finance. In fact, over the last few years, we have already recognized organizations of conferences' special sessions which were entirely devoted to financial applications of genetic algorithms and genetic programming. Nonetheless, a volume exclusively devoted to this subject has not been seen since the publication of Genetic Algorithms and Investment Strategies by Richard Bauer in 1994. Even in that book, genetic programming was not included. All the way back to 1994, financial applications of John Koza's genetic programming were indeed just getting underway.
In the year 2000, Allard Winterink, a then senior publishing editor of Kluwer Academic Publishers, brought the idea to me of publishing a special volume on this subject. Allard's enduring efforts to put forward this project and invite my involvement are very impressive. His enthusiastic support facilitates the launch of this project.
Ten chapters of the volume are based on a selection of papers presented at the 6th International Conference of the Society for Computational Economics on Computing in Economics and Finance (SCE'2000), which was held at Universitat Pompeu Fabra, Barcelona, Catalonia, Spain on July 6-8, 2000. In addition to the conference papers, we also invited other leading scholars on the subject of this volume to contribute chapters. All proposed articles were then reviewed together with the conference papers and most of them were asked to revise. Five submissions which failed to meet the standard of the volume are therefore not included in this volume, which finally ended up with the 19 contributed chapters of this volume plus one introduction chapter by the editor. Many thanks is due to all the authors for cooperating with the production of the volume.An Overview
Part I Introduction
Genetic Algorithms in Economics and Finance
Genetic Programming: A Tutorial
Part II Forecasting
GP and the Predictive Power of Internet Message Traffic
Genetic Programming of Polynomial Models for Financial Forecasting
NXCS: Hybrid Approach to Stock Indexes Forecasting
Part III Trading
EDDIE for Financial Forecasting
Forecasting Market Indices Using Evolutionary Automatic Programming
Genetic Fuzzy Expert Trading System for NASDAQ Stock Market Timing
Part IV Miscellaneous Applications Domains
Portfolio Selection and Management
Intelligent Cash Flow: Planning and Optimization Using GA
The Self-Evolving Logic of Financial Claim Prices
Using GP to Predict Exchange Rate Volatility
EDDIE for Stock Index Options and Futures Arbitrage
Part V Agent-Based Computational Finance
A Model of Boundedly Rational Consumer Choice
Price Discovery in Agent-Based Computational Modeling of the Artificial Stock Market
Individual Rationality as a Partial Impediment to Market Efficiency
A Numerical Study on the Evolution of Portfolio Rules
Adaptive Portfolio Managers in Stock Markets
Learning and Convergence to Pareto Optimality
The New Evolutionary Computational Paradigm