Buch, Englisch, 227 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 371 g
Buch, Englisch, 227 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 371 g
Reihe: Perspectives in Neural Computing
ISBN: 978-3-540-76098-6
Verlag: Springer
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Finanzsektor & Finanzdienstleistungen: Allgemeines
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Fuzzy-Systeme
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
Weitere Infos & Material
1 From Learning Systems to Financial Modelling.- 1.1 Introduction.- 1.2 Adaptive Systems and Financial Modelling.- 1.3 Time Series Analysis.- 1.4 Brief History of Neural Networks.- 1.5 Book Overview.- 1.6 Summary.- 2 Adaptive Systems and Financial Modelling.- 2.1 Financial Modelling.- 2.2 The Problems with Financial Modelling.- 2.3 Evidence Against the Efficiency Hypothesis.- 2.4 An Adaptive Systems Approach.- 2.5 Neural Nets and Financial Modelling.- 2.6 Genetic Algorithms in Finance.- 2.7 Summary.- 3 Feed-Forward Neural Network Modelling.- 3.1 Neural Net Search.- 3.2 MLP Training: The Model.- 3.3 MLP: Model Parameters.- 3.4 The Data.- 3.5 MLP: Training Parameters.- 3.6 Network Performance.- 3.7 Summary.- 4 Genetic Algorithms.- 4.1 Using Genetic Algorithms.- 4.2 Search Algorithms.- 4.3 GA Parameters.- 4.4 A Strategy for GA Search: Transmutation.- 4.5 Summary.- 5 Hypothesising Neural Nets.- 5.1 System Objectives.- 5.2 Hypothesising Neural Network Models.- 5.3 Occam’s Razor and Network Architecture.- 5.4 Testing Occam’s Razor.- 5.5 Strategies using Occam’s Razor.- 5.6 Validation.- 5.7 GA-NN Hybrids: Representations.- 5.8 Summary.- 6 Automating Neural Net Time Series Analysis.- 6.1 System Objectives.- 6.2 ANTAS.- 6.3 Primary Modelling.- 6.4 Secondary Modelling.- 6.5 Validation Modules.- 6.6 Control Flow.- 6.7 Summary.- 7 The Data: The Long Gilt Futures Contract.- 7.1 The Long Gilt Futures Contract.- 7.2 The LGFC Data.- 7.3 Secondary Data.- 7.4 Data Preparation.- 7.5 Data Treatment Modules.- 7.6 Efficient Market Hypothesis and the LGFC.- 7.7 Summary.- 8 Experimental Results.- 8.1 Experimental Design.- 8.2 Phase I — Primary Models.- 8.3 GA-RB Module and Combined Validation.- 8.4 Phase II — Secondary GA-RB Models.- 8.5 Phase III — Validation and Simulated LiveTrading.- 8.6 Controls: Analysis of ANTAS.- 8.7 ANTAS: Conclusions.- 8.8 Summary.- 9 Summary, Conclusions and Future Work.- 9.1 Motivations.- 9.2 Objectives: Neural Networks and Learning.- 9.3 Book Outline and Results.- 9.4 Conclusions.- 9.5 Future Work.- Appendices.- A Test Functions.- B ANTAS Outline Code.- C ANTAS Results.- References.