Genetic Algorithms and Genetic Programming in Computational Finance

✍ Scribed by Shu-Heng Chen (auth.), Shu-Heng Chen (eds.)

• Publisher: Springer US
• Year: 2002
• Tongue: English
• Leaves: 490
• Edition: 1
• Category: Library

✦ Synopsis

After a decade of development, genetic algorithms and genetic programming have become a widely accepted toolkit for computational finance. Genetic Algorithms and Genetic Programming in Computational Finance is a pioneering volume devoted entirely to a systematic and comprehensive review of this subject. Chapters cover various areas of computational finance, including financial forecasting, trading strategies development, cash flow management, option pricing, portfolio management, volatility modeling, arbitraging, and agent-based simulations of artificial stock markets. Two tutorial chapters are also included to help readers quickly grasp the essence of these tools. Finally, a menu-driven software program, Simple GP, accompanies the volume, which will enable readers without a strong programming background to gain hands-on experience in dealing with much of the technical material introduced in this work.

✦ Table of Contents

Front Matter....Pages i-xxi
Genetic Algorithms and Genetic Programming in Computational Finance: An Overview of the Book....Pages 1-26
Front Matter....Pages 27-27
Genetic Algorithms In Economics and Finance: Forecasting Stock Market Prices And Foreign Exchange — A Review....Pages 29-54
Genetic Programming: A Tutorial With The Software Simple GP....Pages 55-77
Front Matter....Pages 79-79
GP and the Predictive Power of Internet Message Traffic....Pages 81-102
Genetic Programming of Polynomial Models for Financial Forecasting....Pages 103-123
NXCS: Hybrid Approach to Stock Indexes Forecasting....Pages 125-158
Front Matter....Pages 159-159
Eddie for Financial Forecasting....Pages 161-174
Forecasting Market Indices Using Evolutionary Automatic Programming....Pages 175-195
Genetic Fuzzy Expert Trading System for Nasdaq Stock Market Timing....Pages 197-217
Front Matter....Pages 219-219
Portfolio Selection and Management Using a Hybrid Intelligent and Statistical System....Pages 221-238
Intelligent Cash Flow: Planning and Optimization Using Genetic Algorithms....Pages 239-247
The Self-Evolving Logic of Financial Claim Prices....Pages 249-262
Using a Genetic Program to Predict Exchange Rate Volatility....Pages 263-279
Evolutionary Decision Trees for Stock Index Options and Futures Arbitrage....Pages 281-308
Front Matter....Pages 309-309
A Model of Boundedly Rational Consumer Choice....Pages 311-333
Price Discovery in Agent-Based Computational Modeling of the Artificial Stock Market....Pages 335-356
Individual Rationality as a Partial Impediment to Market Efficiency....Pages 357-377
A Numerical Study on the Evolution of Portfolio Rules....Pages 379-395
Adaptive Portfolio Managers in Stock Markets: An Approach Using Genetic Algorithms....Pages 397-419
Learning and Convergence to Pareto Optimality....Pages 421-439
Front Matter....Pages 441-441
The New Evolutionary Computational Paradigm of Complex Adaptive Systems....Pages 443-484
Back Matter....Pages 485-489

✦ Subjects

Economic Theory; Operation Research/Decision Theory; Finance/Investment/Banking