Genetic Algorithms and Genetic Programming in Computational Finance / Edition 1

Genetic Algorithms and Genetic Programming in Computational Finance / Edition 1

by Shu-Heng Chen, Chen
     
 

ISBN-10: 0792376013

ISBN-13: 9780792376019

Pub. Date: 07/31/2002

Publisher: Springer US

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,

Overview

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 sk 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.

Product Details

ISBN-13:
9780792376019
Publisher:
Springer US
Publication date:
07/31/2002
Edition description:
2002
Pages:
489
Product dimensions:
6.10(w) x 9.25(h) x 0.04(d)

Table of Contents

List of Figures. List of Tables. Preface. 1. An Overview; S.-H. Chen. Part I: Introduction. 2. Genetic Algorithms in Economics and Finance; A.E. Drake, R.E. Marks. 3. Genetic Programming: A Tutorial; S.-H. Chen, et al. Part II: Forecasting. 4. GP and the Predictive Power of Internet Message Traffic; J.D. Thomas, K. Sycara. 5. Genetic Programming of Polynomial Models for Financial Forecasting; N.Y. Nikolaev, H. Iba. 6. NXCS: Hybrid Approach to Sk Indexes Forecasting; G. Armano, et al. Part III: Trading. 7. EDDIE for Financial Forecasting; E.P.K. Tsang, J. Li. 8. Forecasting Market Indices Using Evolutionary Automatic Programming; O'Neil, et al. 9.Genetic Fuzzy Expert Trading System for NASDAQ Sk Market Timing; S.S. Lam, et al. Part IV: Miscellaneous Applications Domains. 10. Portfolio Selection and Management; J.G.L. Lazo, et al. 11. Intelligent Cash Flow: Planning and Optimization Using GA; M.A.C. Pacheco, et al. 12. The Self-Evolving Logic of Financial Claim Prices; T.H. Noe, J. Wang. 13. using GP to Predict Exchange Rate Volatility; C.J. Neely, P.A. Weller. 14. EDDIE for Sk Index Options and Futures Arbitrage; S. Markose, et al. Part V: Agent-Based Computational Finance. 15. A Model of Boundedly Rational Consumer Choice; T. Riechmann. 16. Price Discovery in Agent-Based Computational Modeling of the Artificial Sk Market; S.-H. Chen, C.-C. Liao. 17. Individual Rationality as a Partial Impediment to Market Efficiency; S.-H. Chen, et al. 18. A Numerical Study on the Evolution of Portfolio Rules; G. Caldarelli, et al. 19. Adaptive Portfolio Managers in Sk Markets; K.Y. Szeto. 20. Learning and Convergence to Pareto Optimality; C.R. Birchenhall, J.-S. Lin. Part VI: Retrospect and Prospect. 21. The New Evolutionary Computational Paradigm; S.M. Markose. Index.

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